Automation * Controls * Technology

Do Panelview backlights impact the overall energy efficiency of a manufacturing facility.

2024-09-18T15:54:00.000-04:00

The role of Panelview backlights in improving machine safety and reducing operator errors is significant. Here are a few key ways they contribute:

1. Enhanced Visibility: Bright and clear backlighting ensures that operators can easily read displays and controls, even in low-light or high-glare environments, reducing the risk of misreading information.

2. Color Coding: Backlights can be programmed to change color based on the machine’s status (e.g., green for normal operation, red for an error). This immediate visual cue helps operators quickly identify and respond to issues, minimizing mistakes and enhancing safety.

3. Attention to Alarms: Bright, flashing backlights can draw attention to critical alarms and warnings, ensuring that operators notice and address urgent issues promptly.

4. Fatigue Reduction: Proper lighting can reduce eye strain and fatigue, which are common causes of operator error. Clear, well-lit displays help maintain operator alertness and accuracy over long shifts.

5. Training and Consistency: Standardized backlighting across different machines and panels helps create a consistent user experience, making it easier for operators to learn and remember control layouts and functions, thereby reducing errors.

https://tek-supply.com/collections/panelviews

Allen Bradley Panelview Common Maintenance Issue

2024-08-07T09:11:00.003-04:00

A common issue many of us face with our Allen Bradley PanelView Display 1000 units - a dim or dead backlight! But with a little patience and the rightful tools, you can bring your HMI back to life. Here's a quick guide on how to replace the backlight:

1. **Safety First**: Before anything else, ensure the PanelView is powered off and disconnected from any power sources. Safety glasses and gloves aren’t a bad idea either!

2. **Access the Backlight**: Carefully open the back of the PanelView 1000 by removing the screws. Remember, organization is key - keep those screws safe for reassembly.

3. **Identify the Backlight**: Once inside, locate the backlight assembly. It’s usually connected to the display module and not too hard to spot.

4. **Remove the Faulty Backlight**: Gently disconnect the old backlight. This might involve unplugging connectors or removing securing tapes, depending on your model.

5. **Install the New Backlight**: Take your new backlight (make sure it’s the correct type for your PanelView model) and connect it where the old one was. Ensure the connections are secure.

6. **Reassemble and Test**: Put everything back together, power it up, and voilà! Your PanelView 1000 should be shining bright like the first day you got it.

A dim display doesn't mean the end of your PanelView’s life. With a new backlight, it can continue to be a vital part of your operations.

Has anyone else tried this repair? Drop your tips, questions, or success stories below! Let’s keep our equipment in top shape together.

#IndustrialAutomation #PanelView1000 #DIYRepair #AllenBradley

Additive Manufacturing: 3D Printer Runs Eight Times Faster Than Others

2019-03-06T19:13:00.007-05:00

Screw Extrusion Additive Manufacturing (SEAM) technology from the Fraunhofer Institute for Machine Tools and Forming Technology IWU is a high-speed system that is said to take only 18 min. to produce a plastic component that is 30-cm high. The extruder is installed above a construction platform that can be swiveled in six axes by using a motion system akin to that of a machine tool. Plastic is deposited in layers on the construction platform.

The motion system ensures that the construction panel slides along under the nozzle in such a way that the previously programmed component shape is produced. The table can be moved at a speed of one meter/sec in the X-, Y- and Z-axes, and can also be tilted by up to 45°. This reportedly enables SEAM to print eight times faster than conventional processes, enormously reducing the production times for plastic components.

2711-NL3 Backlight Bradley Panelview 600

Every hour, up to 7 kg of plastic are pressed through the hot nozzle with a diameter of one mm. Comparable 3D printing processes, such as Fused Deposition Modeling or Fused Filament Modeling, usually run at a rate of 50 g of plastic per hour. Instead of expensive FLM filament, SEAM processes free-flowing, cost-effective standard plastic granulate into resilient, fiber-reinforced components that are several meters in size. This method reportedly allows material costs to be reduced by a factor of 200.

SEAM allows researchers to implement complex geometries without supporting structures. The new system even makes it possible to print on existing injection-molded components, even curved structures. In tests, Fraunhofer IWU ran materials ranging from TPEs to 50% carbon filled high-performance plastics. Fraunhofer IWU says these materials cannot be processed on traditional 3D printers.

The SEAM process was developed at the Chemnitz Institute.

from ptonline.com

Bumps in the Road to Smart Manufacturing

2019-03-06T19:07:00.001-05:00

My childhood was spent listening to songs piped out of an AM transistor radio, selected at the whim of a DJ. Today my 4-year-old grandson merely needs to tell his virtual assistant named Alexa the music he would like to hear. Technology has changed so dramatically in my lifetime that it’s hard to envision a future state when there isn’t the kind of exponential growth we’ve seen since the mid-1990s.

Arguably the most significant technological advance for American business—the Industrial Internet of Things (IIoT), which holds the promise of unimagined productivity gains and untold benefits to consumers—isn’t assured. That’s the essence of a new study, “Smart Factories: Issues of Information Governance,” produced by the Manufacturing Policy Initiative (MPI) out of Indiana University’s School of Public and Environmental Affairs.

MPI Director Keith Belton’s original purpose in creating this collection of analyses—written by experts from academia and industry, and which my organization had a role in developing—was to determine the key policy solutions that could help spur the growth of smart manufacturing. But after conferring with top manufacturing experts in MAPI’s community of leaders, he realized that smart manufacturing in this country faces some bumps in the road.

Allen Bradley Panelview 2711-NL7
What prevents its immediate adoption? First, the technologies necessary to create a thoroughly integrated cyber-physical system are still in the early stages of development, and the expertise to operate and maintain these systems is still being cultivated. In addition, manufacturing investment cycles are long—existing factories will likely take years to adopt new “smart” technologies. Most important is the need for rules around the collection, flow, and analysis of digital information—in effect, information governance through the collective action of public and private organizations. As Dr. Belton puts it, “Get the rules right, and the promise of smart manufacturing will become a reality. Get the rules wrong, and smart manufacturing will never fully materialize. Information governance matters.”

Here are some of the biggest challenges outlined by the authors:

How do you hold AI accountable? AI has come a long way in a short time—from Deep Blue’s defeat of chess champion Gary Kasparov in 1997, to the first licensed self-driven car in 2012, to the use of generative design as an auxiliary to additive printing in recent years. But significant technical challenges still exist, which can lead to important legal, ethical, and public policy questions. For example, how to assign liability when AI makes a mistake? What kind of government oversight is needed when AI is used for security uses? Machine learning is fast, but it’s far from perfect, and the public and private sectors need to clarify the rules governing smart machines.

Who will develop the technical standards? There is no IIoT without the adoption of global technical standards. After all, smart factories will be built upon the integration of IT and OT, which will require uniformity to allow for the widespread acceptance and use of specific technologies. IIoT is complicated, with hundreds of standards already in existence or in development, and potentially thousands more to come. Considering that rapidly developing technologies often outpace the slower standards development process—and considering the decentralized U.S. standards system, where hundreds of standards developing organizations create standards—the need for public-private coordination becomes all the more apparent.

Do the benefits outweigh the risks? No one doubts the benefits of smart manufacturing. And yet developing an integrated IT and OT system that is hooked up to the internet is like leaving your house keys resting on your front porch. Once companies take the plunge, rogue nations, criminal organizations, and hacktivists all potentially have access to their factory floor and supply chains. Thus, companies spend more and more time and money on cybersecurity risk management, including the training of employees, building security into devices at the start and monitoring outside service providers. There will continue to be uncertainty until a collective framework can be developed that allows for governments, companies and experts to coordinate their approaches to cyber risks.

As Dr. Belton concludes, collective action is needed to create an environment conducive to investment in smart manufacturing. Manufacturers working with third-party providers can initiate some solutions, but in most areas, only coordinated public-private action will provide the certainty that drives investment.

Stephen Gold is president and CEO, MAPI (Manufacturers Alliance for Productivity and Innovation).

from industryweek.com

IoT Utilization Skyrockets in Industrial Automation Applications

2019-03-06T18:57:00.004-05:00

Internet of Things (IoT) continues to gain traction in all kinds of industries and applications. Industrial Automation is one such industry that’s seen a big increase in IoT utilization—a very big increase.

Industrial Automation refers to the use of various control devices like computers, robots, and information technologies for handling and controlling different processes and machines in an industry. It’s also done with a reduced need for human intervention, resulting in a more automated control performance.

The Internet of Things is the network of physical objects and devices around the world that are connected to the internet and specifically meant to collect and share data. In industrial automation, those connected devices are the computers, machines and robots mentioned above.

The growth of IoT in Industrial Automation is highlighted in a recent report by Berg Insight that found that the installed base of wireless IoT devices in Industrial Automation reached 21.3 million in 2018. That growth shows no signs of slowing as that number is expected to reach 50.3 million by 2023.

Wireless IoT solutions are great for parts of facilities that are hard to reach, cost prohibitive to connect with wired installations or have frequent modifications to workflows and layouts. In factory automation, wireless IoT can be used to control devices such as cranes and automated guided vehicles (AGVs) in material handling applications. They can also be used in process automation to connect instruments that enable plant operators to monitor and optimize processes in hazardous areas, which helps to ensure worker safety.

"Robust connectivity is critical to support industrial IoT use cases surrounding predictive maintenance and digital twins," said Fredrik Stalbrand, IoT Analyst at Berg Insight. He went on to explain that installation and maintenance of wireless solutions are more flexible and economical compared to wired technologies, enabling reconfigurable manufacturing system design.

2711-NL2 Backlight Replacement for Allen Bradley Panelview 900

Berg Insight’s report also estimated that annual shipments of wireless devices for industrial automation applications reached 4.6 million units worldwide in 2018, which

accounts for approximately 6 percent of all new connected nodes. That number is expected to reach 9.9 million in 2023, which is more evidence of the rapid growth of IoT in Industrial Automation.

While the adoption of wireless IoT solutions in industrial automation can help with everything from improved waste removal, refining supply chains to creating lean operations on the factory floor, there’s more: data. Big data. Data resides everywhere in manufacturing. Wireless IoT solutions work to gather and communicate that data so that it can be analyzed and utilized effectively. There is valuable data in Enterprise Resource Planning (ERP) systems, Product Lifecycle Management (PLM) systems, Manufacturing Execution Systems (MES) and Supplier Relationship Management (SRM) systems, as well as all the documents like spreadsheets and other files that a company accumulates. There is also data to be collected and utilized from outside the business from sources like vendors and even sales.

Industrial automation companies that continue to adopt IoT strategies stand the best chance to overcome organizational, process, data and system silos by automating the collection of data across divisions and operations. They’ll be positioned to better analyze and utilize all that data helping to ensure more efficient and profitable operations.

from engineering.com

What is the role of industrial automation in a ‘Smart Factory’?

2019-02-27T18:11:00.003-05:00

An expert panel discussion at this year’s Manufacturing Automation and Robotics Summit explored what role physical technology has in creating intelligent, connected factories of the future.

What parts of production processes are best suited to automation? – image courtesy of Depositphotos.

UK manufacturing businesses are having to respond to the convergence of powerful trends in labour supply, supply chain consolidation and optimising the balance between quality and cost – a situation in which industrial automation lies at the very centre.

The sold-out Manufacturing Automation and Robotics Summit tackled these challenges head-on, helping the 80 senior manufacturing executives in attendance to define:

What parts of their production process are best suited to automation, and what kind
Where their industry peers are seeing the greatest automation opportunities and successes
How the technology landscape has evolved, and continues to, and how best to take advantage

The summit took place at Aston Villa Football Club in Birmingham and was deftly chaired by Duncan McFarlane, Professor of Industrial Information Engineering at University of Cambridge’s Institute for Manufacturing (IfM).

McFarlane also chaired the morning expert panel discussion comprising:

Steven Carter – Digital Manufacturing Integration Lead, Rolls-Royce
Ed Preston – Global Automation Leader, GKN Aerospace
Alan Newman – Advanced Manufacturing Engineering & Technical Director, De La Rue

What are the most exciting innovations you’re seeing?

Steven Carter: The disruption generated by combining the power and affordability of data analytics and the insights it provides, in conjunction with low-cost robotics and open-source software.

The sold-out Manufacturing Automation and Robotics Summit gathered together 80 senior manufacturing executives – image courtesy of The Manufacturer.

Ed Preston: The new business models being created thanks to the availability of powerful yet affordable connectivity and automation, both from established manufacturers and disruptive start-ups.

Alan Newman: The significant reduction in the cost of industrial automation and robotics which means the technologies are no longer only applicable for high-volume operations. Also, how automation and robotics is becoming ever-more seamlessly and invisibly integrated into our personal and professional lives.

What are the common mistakes around deployment?

SC: Projects being too short-term in focus, rather than looking far enough out, and not considering how it might impact your upstream/ downstream processes such as part validation or quality assurance. Also, not considering the human factors – something which often isn’t included in the technical specifications. How will this impact the individuals? Would spending a ‘day in the life of’ one of your production operatives change your approach?

EP: Project teams only looking at the outward cost of the robot or automation system, rather than the total cost of ownership which may include changes to the surrounding infrastructure (such as strengthening the foundation beneath a machine weighing several tonnes) or the hiring of a crane to move it into place. The cost of the actual technology may have come down significantly, but the cost of actually integrating and maintaining it hasn’t necessarily. If you’re struggling to justify the business case, you need to look high and low for the potential benefits, i.e. improved worker health & safety, reduced defects, lower tooling costs.

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AN: Too much focus being placed on the hard, financial gains, rather than the ‘softer’ benefits such as employee satisfaction levels and workplace culture. Both of which are absolutely vital and the key to having a successful, productive, innovative, flexible, growing business.

How can industrial automation be used as a strategic tool to achieve your business growth objectives, as opposed to being yet another point solution?

SC: Again, spend a ‘day in the life of’ your production operatives. Look at the potential quality, health & safety and operator experience benefits – applicable in both high and low-volume production – and how that adds value to your business. A better experience for your workers will create a significant amount of value-add across the business.

Better experiences for workers will create a significant amount of value-add across your business.

EP: Automation and robotics represent a useful tool with which to not only engage the next generation; but tasks around programming and functionality engineering are also exciting projects for your current workers to become involved with –increasing their motivation and output.

AN: The technologies allow you to maximise your workflow and output within a given space, which means productivity can increase without the need for an expensive factory extension or relocation. Industrial automation can also be a factor in retaining or establishing production in a high-labour cost country.

Should we automate absolutely everything or are there limits?

EP: For every potential implementation or project, ask ‘Will this benefit this process and my business overall in a tangible and timely manner?’. It’s as simple as that.

AN: Guiding every decision should be an understanding that ROI and business improvements – whatever they may be, hard or soft, upstream or downstream – are being delivered and can be sustained.

SC: It would be naive to think you can – and should – automate absolutely anything and everything. You need to put together a robust business case and really drill down into the potential benefits

from themanufacturer.com

What Jenga can teach robots about industrial automation

2019-02-12T17:23:00.001-05:00

A team of MIT engineers developed a system that robots can use to play Jenga. This classic game is pretty simple -- players must remove individual blocks from a stacked tower without knocking the tower over. Even though the rules are simple, Jenga requires a unique combination of physical skill and mental strategy. By mastering the game, the robot overcomes many of the challenges in manipulation that it would encounter in an industrial setting.

This skillset, a combination of approach and agility, could translate nicely in the real world, where robots are used to manufacture and assemble things like electronic products.

The MIT engineers customized an ABB IRB 120 robotic arm, outfitting it with a soft-pronged gripper, a force-sensing wrist cuff, and an external camera. Just like when humans play Jenga, the robot pushes against a block to determine if it can be removed without toppling the tower. While we just our senses of touch and sight, the robot used its camera for vision and the wrist cuff for tactile feedback.

The researchers published their findings in the latest issue of Science Robotics. The paper's lead author Nima Fazeli tells ZDNet, "The robot has to deal with real-world noisy sensors and partial information. Critically, the robot cannot know the state of the tower (how blocks move) without physically interacting with it. For this, it needs to combine its two complementary senses of sight and touch, much like we do."

With more experience, the robot learned how to get better at playing Jenga (in other words, how to get better at manipulating precarious objects). But reassembling a Jenga tower is time-consuming and difficult, Fazeli says, so the engineers developed algorithms and approaches that only require small amounts of data. Instead of collecting large data-sets, which would require rebuilding the tower tens of thousands of times, the robot trained on 300 or so attempts. This efficient approach involved clustering together similar behaviors and outcomes. Then the robot developed a model for each data cluster so predict how a block would behave, depending on how it looked and felt.'

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The goal of the project isn't to create a Jenga master, but to improve the way artificial intelligence interacts with the physical world. "Taking this to an application, we look toward industrial automation," Fazeli explains. Specifically, this technique could be useful for assembly and disassembly , where robots need to figure out how to put parts together.

Fazeli says, "We believe that the ability to create useful abstractions, much like this robot does for the interactions between Jenga pieces, and the ability to reason about physics in the domain of sight and touch are an important step towards robots effectively and quickly learning useful manipulation skills that they can deploy in industrial setting."

from zdnet.com

Multiple 3D methods ease industrial automation applications

2019-01-08T14:53:00.000-05:00

Many 3D vision techniques are used for robot guidance and industrial inspection applications.

More often than not, it is necessary to empower robots with the ability to become autonomous, identify, pick and place parts and collaboratively work with human operators. To accomplish this requires that such systems employ a number of machine vision techniques including photogrammetry, stereo vision, structured light, Time of Flight (TOF) and laser triangulation techniques to perform the task of localizing and measuring objects.

Figure 1: 6 River Systems’ collaborative automation warehouse robot, known as Chuck, uses TiM LiDAR sensors from SICK to build a map of the environment and lead warehouse associates to the correct location to pick products.

SCENES AND OBJECTS

Depending on the application, the vision system may be either scene-related or object related. In scene-related applications, the camera is generally mounted on a mobile robot and algorithms such as simultaneous localization and mapping (SLAM) are used to construct or update a map of the surrounding environment.

In object-related tasks, a camera, cameras, laser or TOF system is attached to the end-effector of an industrial robot allowing new images to be captured as the end-effector is moved. Of course, with different tasks, different kinds of 3D imaging systems may be required.

In scene-related applications, the robot needs to be aware of the surroundings and whether any objects or people are present to hinder its path. In applications such as these, it may also be necessary to add a capacity to pick and place objects. Examples of such applications include self-driving cars, warehouse pick-and-fetch robots and military-based robotic systems designed to identify, for example, suspicious objects.

Unlike object-related tasks that are designed to perform specific pick-and-place functions, these systems must also incorporate methods to localize and map their local space and, once located, must perform a specific function such as fruit picking. In one sense, these systems add an extra sophistication to robotics systems and to do so, a number of different hardware and software options can be used.

Figure 2: At the Southwest Jiaotong University, Dong Zhan and his colleagues have designed and built a dynamic railway tunnel 3D clearance inspection based on a multi-camera and structured-light vision system.

MAPPING THE ENVIRONMENT

To build a map of the surrounding environment, the problem of scene mapping is solved by incorporating LiDAR scanning range finders from companies such as SICK (Minneapolis, MN, USA; www.sick.com) and Velodyne (San Jose, CA, USA; https://velodynelidar.com), onto robots or autonomous vehicles.

At 6 River Systems (Waltham, MA, USA; https://6river.com), for example, the company’s collaborative automation warehouse robot known as Chuck uses TiM LiDAR sensors from SICK to build a map of the environment and lead warehouse associates to the correct location to pick products (Figure 1). In a similar application, RK Logistics Group (Fremont, CA, USA; www.rklogisticsgroup.com), partnered with Fetch Robotics (San Jose, CA, USA; www.fetchrobotics.com) to increase employee productivity by automating the task of transporting products from one part of the RK Logistics’ warehouse to another (see “Autonomous mobile robots target logistics applications,” Vision Systems Design, May 2018; http://bit.ly/VSD-AMR). Fetch Robotics’ Freight autonomous mobile robot employs a SICK TIM571 LiDAR scanning range finder interfaced to its on-board computer over an Ethernet switch. Using TOF measurement, the TIM571 emits an 850nm laser pulse which is scanned over a 220° field of view (FOV) using a moving mirror.

To evaluate the most optimal system for autonomous vehicles, Simona Nobili and her colleagues at the Ecole Centrale Nantes (Nantes, France; www.ec-nantes.fr) have analyzed two common LiDAR configurations: the first based on three planar SICK LMS151 LiDAR sensors and the other on a Velodyne 3D LiDAR VLP-16 sensor. Implementing a SLAM algorithm, the systems they developed used three SICK LMS151 sensors placed at 50 cm from the ground level on a Renault Zoe ZE electric car and a Renault Fluence equipped with a 16-channel Velodyne LiDAR PUCK (VLP-16) placed above the roof.

In their research, the researchers found that maps built with VLP-16 data were more robust against common medium-term environment changes such as cars parked on the roadside and that single sensor implementations such as these were easier to install and calibrate (see “16 channels Velodyne versus planar LiDARs based perception system for Large Scale 2D-SLAM,” http://bit.ly/VSD-VEL).

3D MEASUREMENTS

Of course, many machine vision applications only require object-related tasks such as 3D measurements to be performed. Here, depending on the nature of the product to be inspected, several different methods exist, one of the most commonly used being structured laser light analysis or laser line profiling. In this method, a structured laser light is either moved across an object or allowed to impinge on the object as it moves along conveyor.

Single lines of the reflected laser light are then digitized by an industrial camera and the distance of each surface point is computed to obtain a 3D profile of the object. In order to build a system like this, developers have the option of using single laser line sources from companies such as Coherent (Santa Clara, CA, USA; www.coherent.com) and Z-Laser (Freiburg, Germany; www.z-laser.com) and separate cameras with which to digitize the reflected light. Such systems are used in numerous machine vision applications including electronics inspection, dimensional parts analysis and automotive tire tread inspection.

One of the more novel applications of this technology has been to accurately produce 3D measurements of railway tunnels. In a system developed at the Southwest Jiaotong University (Chengdu, China; https://english.swjtu.edu.cn/), Dong Zhan and his colleagues built a dynamic railway tunnel 3D clearance inspection based on a multi-camera and structured-light vision system (Figure 2).

To capture 3D images of the tunnel, seven MVC1000SAM GE60 1280 × 1024 industrial cameras from Microview (Beijing, China; http://www.microview.com.cn) with 5-mm focal length lenses from Kowa (Aichi, Japan; www.kowa.co.jp) are used to capture seven reflected laser lines from Z-Laser Model ZM18 structured lasers, while another two cameras and lasers are used to monitor the rail.

Installed on the front of a train, captured images are then triggered by the optical encoder to capture a 2D laser map of the tunnel. Image processing software is then used to reconstruct the surface of the tunnel (http://bit.ly/VSD-MSVS).

In such systems, it is vitally important to calibrate the camera systems used. Realizing this, developers of such laser/camera systems have developed products that embed both cameras and lasers and are supplied pre-calibrated. Here, such products as the DSMax 3D laser displacement sensor from Cognex (Natick, MA, USA: www.cognex.com), the LJ-V Series laser profilometer from Keyence (Osaka, Japan; www.keyence.com) and the Gocator 3D laser line profile sensors from LMI Technologies (Burnaby, BC, Canada; www.lmi3d.com) all offer systems integrators an easy way to configure laser-based 3D profiling systems.

STEREO CAMERAS

While both scanning range finders and laser-based implementations represent active methods of 3D imaging, passive methods that use one or two cameras can be equally as effective. Often two calibrated cameras are used to identify single points in 3D space and this information is used to generate a depth map. However, this need not be the case.

By mounting a single camera onto a robot arm’s end effector, for example, and moving the camera in 3D space, two separate images can be captured, and a depth map generated from them. Two companies that have developed this capability are Motoman (Miamisburg, OH, USA; www.motoman.com) and Robotic Vision Technology (RVT; Bloomfield Hills, MI, USA; http://roboticvisiontech.com).

For its part, Motoman’s MotoSight 3D CortexVision simplifies the use of 3D vision in robotic guidance applications using a single camera mounted to the robot. In operation, the system takes multiple images and automatically refines the position of the camera to optimally locate the part. (see “Robot Guidance,” Vision Systems Design, November 2008; http://bit.ly/1pUVMUG).

RVT uses a similar concept to locate parts in 3D space. In RVT’s eVisionFactory software, an AutoTrain feature automatically moves a robot and camera through multiple image positions as it measures features of the part being imaged. While single-camera systems can be used to locate parts in 3D space, the positional accuracy of the robot will determine how accurately specific objects can be located in 3D space.

Just as active laser and camera systems need to be accurately calibrated, so too do dual-camera configurations. Like active/laser camera systems that are offered as products that embed both cameras and lasers and are supplied pre-calibrated, so too are passive stereo systems. These often employ two (or more) stereo vision cameras and are pre-calibrated, saving systems developers the task. The most well-known of these 3D stereo camera systems are the Bumblebee series from FLIR Integrated Imaging Solutions (Richmond, BC, Canada; www.flir.com/mv), the SV-M-S1 from Ricoh (Tokyo, Japan; https://industry.ricoh.com) and the ZED from Stereolabs (San Francisco, CA, USA; www.stereolabs.com).

While the SV-M-S1 and ZED use a fixed two-camera implementation, the XB3 Bumblebee series from FLIR Integrated Imaging Solutions is a three-sensor multi-baseline stereo camera design that features 1.3 MPixel CCD image sensors. Because three sensors are used, the unit can operate with an extended baseline that provides greater precision at longer ranges and a narrow baseline that improves close range matching.

While widely used in 3D imaging and robotics applications, such systems are not effective when the object being imaged has low texture or is without texture. In cases such as these, it becomes necessary to project a light onto the object to highlight these structures. Projected texture stereo vision cameras such as the Ensenso 3D camera series from IDS Imaging Development Systems (Obersulm, Germany; https://en.ids-imaging.com

IDS Imaging Development Systems’ Ensenso 3D camera features two integrated CMOS sensors and a projector that casts high-contrast textures onto the object to be captured by using a pattern mask. The result is a more detailed disparity map and a more complete and homogeneous depth information of the scene:

TIME OF FLIGHT

One alternative method to overcome the problems of imaging relatively texture-less objects is to use Time of Flight (TOF) sensors, which work by illuminating a scene with a modulated light source and observing the reflected light. The phase shift between the illumination and the reflection is measured and translated to distance.

These are often deployed in robotic applications since they are relatively compact, lightweight and operate at high frame rates. In such TOF systems, modulated infrared light from the system is reflected from an object and captured by an image sensor. The phase difference between the emitted and received light and the amplitude values then provide distance information and a grayscale image of the scene.

Several companies develop these devices, some of the most well-known being Basler (Ahrensburg, Germany; www.baslerweb.com), ifm electronic (Essen, Germany; www.ifm.com), Infineon Technologies (Neubiberg, Germany; www.infineon.com) and Odos Imaging (Edinburgh, UK; www.odos-imaging.com) – a company recently acquired by Rockwell Automation (Milwaukee, WI, USA; www.rockwellautomation.com).

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While active and passive systems such as structured light, TOF and stereo imaging remain the most popular means to perform 3D imaging, other methods such as shape-from-shading can also be used.

By imaging a part sequentially from different angles, these images can be computed to generate the slope of the surface and its topography. This is the principle behind the Trevista system from Stemmer Imaging (Puchhein, Germany; www.stemmer-imaging.de), which has been used by Swoboda (Wiggensbach, Germany; www.swoboda.de ) to inspect automotive components (see “Shape from shading images steering components,” http://bit.ly/VSD-SFS).

from vision-systems.com

How will ergonomics enable the future of industrial automation?

2019-01-03T18:17:00.002-05:00

The scientific knowledge and methods used in ergonomics and human factors provides the ability to understand users, consumers and systems; to design new manufacturing technology, develop innovative and marketable products and services; improve operational efficiency; manage the ageing workforce; and improve health and safety.

Ergonomics and human factors have always been important to manufacturing. Ever since the industrial revolution forced people and machinery together in large-scale mass-production factory environments, sociotechnical problems began to emerge and have had to be dealt with. A similar need is arising in industry today with the uptake of Industry 4.0 technologies like collaborative robots (cobots) and reconfigurable production lines.

Although manufacturing engineers and managers have traditionally focused on developing technical systems to replace people, there is now an increasing recognition that even in highly advanced and automated production processes, people are still essential for various roles and therefore an equivalent understanding of human/social systems must be developed.

Recently, the rhetoric around automation has cooled. Rather than the ‘robots are going to take all our jobs’ hysteria, there now appears to be an acceptance that automation will be good for the workplace. What’s the reason for this?

“I think we’re getting closer to the reality of what robots and automation are going to do,” explains David Golightly from the Human Factors Research Group at the University of Nottingham. “I think there’s two elements to that: Some of it is we’re getting a better perception of the benefits and the limits of automation.”

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He adds that certain factors aren’t going to be replaced very easily. For example, resilient, flexible problem-solving behaviours. “You’re always going to need to work with your automation, whether that’s an automated control system or robots, there’s always going to have to be that human, creative, more responsive element in collaboration with the automation to make it work,” Golightly adds.

He also believes that there is a realisation that many jobs will be created in their own right. Products, robotics and automation all generate data about how they’re performing and the various systems that they interact with. All that data can be analysed to improve the performance of the robot or product, the automation itself, or the system as a whole.

“A lot of it is in a very raw form, so from a user-centred design perspective it needs to be improved to present it to people,” Golightly says. “Nonetheless, there’s a huge opportunity coming along in terms of jobs and roles associated with the effective use of automation.”

Are these new jobs going to be higher skilled and higher paying? Golightly assumes so, but he adds: “We’re not going to have very skilled data analysts replacing everyone. I think people on the shopfloor are going to be upskilled in order to manage, on a local supervisory level, what’s going on with the automation. There’s talk about ergonomics and human factors and the increasing relevance of supervisory roles. I don’t mean a dull monitoring role, I mean an active, problem-solving, supervisory role and the designing of systems that actually support supervision in a constructive way.”

Automation has been introduced piecemeal over decades. This has proven problematic because, usually, only the simple or mundane parts of certain processes have been automated, leaving the more complex bits to the human operators. This means that there are certain parts of the process at which humans are out of practice as they haven’t performed them in a long time.Programming robots to perform the more complex parts of the processes is also incredibly difficult. Introducing cobots into this environment is a real challenge, especially if the robot needs to communicate its movements to a human working nearby as well as understanding the human’s movements in real time, so as not to slow production.

Golightly suggests: “Think about co-operation and collaboration and start from what are the human and robot trying to achieve together? What is the aim of the system? And from that think about how the human and the robot are going to work together, to collaborate, that’s not just an afterthought.”

Industry 4.0 is allowing manufacturing spaces to change from fixed production lines to reconfigurable and adaptive as mass-customisation becomes more prevalent. If one component in the production line breaks, the production line can be reconfigured to continue. The challenge here is that automation equipment will have to physically move to keep things running, again requiring precise communication between cobot and human.

“If you’re going to realise the opportunity that Industry 4.0 and flexible manufacturing offers, you have to design systems that are going to cooperate with humans. You have to make that a core aspect to the design, whether that’s physical design to support cooperation, or whether it’s more of the cognitive and the software design to support cooperation and collaboration.”

Human factors and ergonomics is all about making processes and products user-centred, putting the user – their needs, capabilities and safety – at the heart of the process.

“One thing that’s interesting, in my experience of working in product design with design engineers,” says Golightly. “Is a lot of them do that intuitively anyway, that’s why they’re drawn to it as a discipline – they are already thinking about people and how they’re going to use their products.”

Going forward, Golightly sees human factors teams become an increasingly important part of an organisation’s makeup, not just in the manufacturing industry but also in transport, healthcare, education, the creative industries, natural environments and urban settlements. He also envisages it becoming a core part of engineering and product design courses.

from eurekamagazine.co.uk

Ten Manufacturing Technology Predictions for 2019

2018-12-05T20:55:00.003-05:00

Running as lean and fast as they can to capitalize on every growth opportunity in 2018, manufacturers are taking bold steps to digitally transform operations in 2019. According to a recent survey of 151 North American manufacturers conducted by Decision Analyst on behalf of IQMS, technologies that bring greater insights and mobility are at the top of the list for enabling their transformation. These include real-time monitoring, analytics, business intelligence (BI), mobile enterprise resource planning (ERP), and quality management applications. Notably, the manufacturers that already are orchestrating these technologies in response to long-standing challenges, are growing at least 10 percent faster than their peers.

Manufacturers participating in the survey shared, not only about what they’re doing today, but also their plans for the coming year. These priorities were also reflected in interviews conducted at manufacturers’ facilities in the last few months. Based on combined observations from these companies, following are ten manufacturing technology predictions for 2019.

1. The era of smart machines is here, and it will make 2019 a pivotal year in enabling manufacturers to attain lights-on production. Industrial equipment manufacturers are fighting price wars with undifferentiated products today, often undercut on deals by offshore machinery providers. To survive, these manufacturing firms are aggressively pursuing a more intensive software-centric product development approach. The result is more affordable industrial machinery capable of running unattended for two or more production shifts. That’s going to make it possible for small and mid-tier manufacturers to attain lights-out manufacturing for the first time.

2. Real-time monitoring adoption accelerates beyond light sticks to Wi-Fi enabled shop floor networks and Internet of Things (IoT) enabled smart machines. In 2019, the clear business case for real-time monitoring across every manufacturing segment will drive widespread adoption. Among manufacturers surveyed, 81 percent reported that real-time monitoring is improving their business. And 52 percent of all manufacturers are relying on real-time monitoring to improve scheduling accuracy. All survey participants are gaining multiple benefits from real-time monitoring including better inventory control (48 percent), improved production plan performance (40 percent), and greater flexibility in managing production lines. Figure 1 summarizes insights on real-time monitoring use gained from the study.

3. More manufacturers will rely on analytics and BI to capitalize on data streams captured through real-time monitoring in improving production and capacity planning. As noted in Figure 2, 73 percent of manufacturers surveyed now consider analytics and BI applications essential for increasing production capacity through better resource planning. And manufacturers growing 10 percent or more per year are integrating their analytics and BI with mobile ERP and quality to gain more accurate financial visibility into shop floor production. These firms are looking beyond embedded offerings to a full-featured analytics footprint that can scale as their business grows. Collectively, these factors will drive greater adoption of analytics and BI in 2019.

4. The pervasiveness of mobile ERP and quality management apps deployments across manufacturing sites will accelerate in 2019, strengthened by advances in integration, usability, and higher-speed cellular network growth. Manufacturers see mobile ERP access as an enabling technology that provides greater data accuracy, improves operational efficiencies, and reduces production delays. (See Figure 3.) In a series of conversations, automotive, industrial equipment, and plastics manufacturers, observed that mobile ERP applications also are enabling them to better manage product configuration lifecycles. Having mobile apps that reflect the current state of customized product configurations across product lifecycle management (PLM), ERP, manufacturing execution system (MES), and customer relationship management (CRM) systems is a major competitive advantage, they note. Not only does this visibility provide greater operational efficiencies; it also reduces production delays and enables alerts that can save days and weeks of lost time.

5. More manufacturing supply chains will go through a digitally-driven transformation aimed at prioritizing and optimizing their performance from the customer’s perspective. One of the major benefits of orchestrating analytics, BI, mobile ERP, and supplier quality management applications toward customer-centric goals is the ability to gain greater speed and scale in fulfilling orders. The path to growth for many manufacturers starts by being able to offer short-notice production runs. By digitally transforming supply chains, manufacturers will be able to have greater inventory and parts availability to the assembly, component and parts level. Achieving greater supplier collaboration by orchestrating these four technologies together is improving customer responsiveness today and will accelerate in 2019.

6. Rapid price reductions on smart machines will enable manufacturers to digitally transform legacy processes and pursue new digital models that weren’t in reach before. For many smaller and mid-tier manufacturers, 2019 will be the year they can afford smart production machines to help replace time-consuming legacy processes that stood in the way of pursuing new digital business models. With legacy production systems replaced by smart machines, quick-response business models that allow manufacturers to scale their product lines and add new ones will be in reach.

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7. Manufacturers looking to escape costly price wars and premature commoditization of their products will fast-track smart, connected products. It’s not just industrial manufacturers facing price wars and commoditized product pressures. Manufacturers across several markets are dropping prices in the hopes of finding more sales, but this drains margin dollars. Forward-thinking manufacturers are shifting their product strategies to smart, connected products now, and those adopting IoT into their product strategies predict that in two years, 67 percent of their entire product portfolios will be smart, connected products. The cumulative revenue growth rate for manufacturing from smart, connected products is projected to grow by 16.22 percent from 2017 to 2022 according to Capgemini’s report, Digital Engineering: The new growth engine for discrete manufacturers.

8. With the proliferation of IoT endpoints across supply chains and production centers, the manufacturing industry realizes every identity is a new security perimeter. For many manufacturers, the integration of information technologies (IT) and operational technologies (OT) is the highest priority with little afterthought given to security. The challenge in 2019 will be protecting every threat surface and endpoint across the proliferating series of IoT-enabled supply chains and production networks. The manufacturing industry is going to experience several breaches in 2019, and it will take one that shuts down a production line to make the concept of Zero Trust Security (ZTS) a reality. ZTS begins with Next-Gen Access (NGA) that verifies every access attempt to every resource on a network along with machine learning to assign risk scores to every login attempt.

9. Industrial IoT (IIoT) platform pilots will target inconsistent, incomplete data structures at the machine, line, factory, and company IT levels with the goal of increasing productivity. Look for IIoT platform providers to offer pilots at little to no cost, so they have a chance to prove they can solve one of manufacturing’s greatest challenges: inconsistent, inflexible legacy data structures from the shop floor to the top floor. IIoT’s potential is in normalizing data across each level of production and attaining 360-degree process transparency. For IIoT to prove it has the security and scale to support daily production, it will need to solve the massive data structures issues that are slowing manufacturers’ growth.

10. IoT early adopters in manufacturing will be five times as likely to generate revenue from their IoT initiatives compared to peers. In 2019, there will be a widening gap between those manufacturers generating revenue from their IoT projects—including smart, connected products—and those that don’t. Look for IoT early adopters to dominate their industries on the ingenuity, scale, and pace of new product development, especially in the area of smart, connected products that rely on IoT sensors to communicate data. For manufacturers who focus on IoT as a growth strategy, 2019 will be a breakaway year compared to many of their peers who are still looking at IoT only for cost reduction

from manufacturing.net

Global Industrial Automation Market 2018-2023: Focus on 5G, Edge Computing, Robotics, and Industrial Internet of Things (IIoT)

2018-11-27T12:52:00.002-05:00

The "Industrial Automation Market: 5G, Edge Computing, Robotics, and Industrial Internet of Things (IIoT) 2018 - 2023" report has been added to ResearchAndMarkets.com's offering.

Industrial Internet of Things (IIoT) solutions are poised to transform many industry verticals including healthcare, retail, automotive, and transport. For many industries, IIoT will significantly improve reliability, production, and customer satisfaction. While IIoT will initially improve existing processes and augmented current infrastructure, the ultimate goal will be to realize entirely new and dramatically improved products and services.

Emerging areas for industrial robotics include Robotics as a Service, Cloud Robotics, and General Purpose Robotics. The fifth generation (5G) of wireless technology will provide the communications and bandwidth necessary to allow various industries to leverage the next phase of robotics evolution. Industrial users will capitalize upon new and enhanced 5G enabled robotics capabilities to enable new use cases and improved work flow.

Many business processes will change as enterprise becomes more savvy about the flexibility of robotics uninhibited by bandwidth constraints.

Cloud Robotics is distinguished from the general field of electromechanical automation through its use of Teleoperation as well as reliance upon various Cloud Computing technologies such as computing and storage as well as the emerging cloud-based business models enabling Robotics as a Service. In addition, Cloud Robotics will benefit greatly from Edge Computing technologies, such as Mobile Edge Computing, as well as commercial introduction of 5G.

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One of the important advantages of the Cloud Robotics market is the ability to make robotics and industrial automation equipment available to a much wider spectrum of users. One of the ways in which this is accomplished is via open APIs, which enable abstraction of the robotics control plane from the application user interface. This means that customers do not need to use proprietary user interfaces for robotic controllers.

An essential component of 5G networks in support of industrial automation, Mobile Edge Computing (MEC) facilitates optimization of fifth generation network resources including focusing communications and computational capacity where it is needed the most. Without MEC, 5G would continue to rely upon back-haul to centralized cloud resource for storage and computing, diminishing much of the otherwise positive impact of latency reduction enabled by 5G.

This research evaluates the telecom and IT ecosystem in support of MEC including communications and computing infrastructure providers, managed services vendors, carriers and OTT providers. Our MEC analysis includes a focus on company strategies and offerings relative to current and anticipated future market needs. It also provides quantitative analysis of the Mobile Edge Computing market including segmentation by industry vertical, region of the world, application and services.

This research is critical to identifying opportunities for R&D, technology integration, and development of new solutions and applications across industry segments. Our findings, insights, data and forecasts are also a key part of capitalizing upon the market for new and enhanced hardware, software, platforms, and services for emerging IoT networks and systems.

This research also evaluates enabling technologies and the market outlook for 5G Network slicing. It provides analysis of the market opportunities including Configuration Management, Performance Management, Service Level Agreements, and more. It also includes 5G Network Slicing by specific use cases such as Smart Manufacturing, which includes Remote Monitoring, Supply Chain Management, Asset Management, Real-Time Monitoring, and Network Monitoring.

In addition, it provides an assessment of major segments such as 5G Network Slicing in consumer, enterprise, and industrial IoT. It provides global forecasts for each area covered as well as regional estimates for 5G Network Slicing by Segment, RF Band, Application, and Industry Vertical through 2023.

This research also evaluates the Cloud Robotics market including technologies, companies, strategies, use cases, and solutions. The report provides global and regional forecasts for Cloud Robotics apps, services, and components from 2018 to 2023. Forecasts include the market outlook for Cloud Services support of Cloud Robotics including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and Robotics as a Service (RaaS).

Forecasting for Cloud Robotics by deployment model is also included covering Public Cloud, Private Cloud, Hybrid Cloud, and Community Cloud. It includes detailed forecasts for robotics by robot type, components, capabilities, solutions, and connectivity for 2018 to 2023.

Select Research Findings:

Global Cloud Robotics Market will reach $16.1 billion USD by 2023
Certain industries will become early beneficiaries of 5G enabled robotics
5G Network Slicing support of Smart Manufacturing will reach $425.3 billion by 2023
The 5G enabled autonomous robot market is expected to reach $14.6 billion by 2023
North America will lead the 5G enabled autonomous robot market with 41% revenue share

Research Benefits:

Forecasts for 5G IoT, Network Slicing, Edge Computing, Robotics, and IIoT to 2023
Understand the role of network slicing and edge computing in industrial automation
Identify key investment areas for Robotics as a Service and Cloud Robotics Platforms
Understand the relationship between Teleoperation, Robotics, and Cloud Computing

For more information about this report visit https://www.researchandmarkets.com/research/bxh3pp/global_industrial?w=4

from businesswire.com

25,000 robots and counting: Welcome to the fastest-growing segment of industrial automation

2018-10-02T17:54:00.004-04:00

credit: mc-mc.com

Collaborative robots, usually called cobots, are now the fastest growing segment of industrial automation and are expected to make up 34% of all industrial robot sales (a ten-fold increase) by 2025. Universal Robots (UR), the company that helped pioneer the market -- one that was largely nonexistent a decade ago -- just announced its 25,000th cobot sale.

The news coincides with the start of the International Manufacturing Technology Show (IMTS), which began today.

Universal Robots has a 60 percent share of the cobot market, but rapid maturity in the sector has attracted plenty of rivals. In a topsy turvy scramble for share that parallels the hardware wars in personal computing, now-established brands like UR, ABB, Fanuc, and Rethink Robotics are competing with one another while newer entries like Locus and Vecna fill out the sector.

The exhibitor hall at IMTS is crammed with human-scale robots that can safely operate outside cages and alongside humans, doing everything from welding and pick & place to ferrying cargo around warehouses and across factory floors. The accelerated pace of adoption has created a large secondary market for robotic grippers and end effectors, as well as alliances between hardware companies and UX developers who are helping lower the barriers to entry to program and operate these robots.

Cobots are designed to work with humans and not replace them, as publicity and marketing teams at these companies are quick to point out.

"The cobots didn't replace any employees," says Peter Felke, President of Kay Manufacturing, which purchased UR's 25,000th unit, in a joint statement with UR. "We were able to meet increased production demand with our existing work force, and we saved twenty minutes of operator time per hour, all while improving our ergonomic work environment and freeing up our staff to handle more value-added tasks."

At this phase, that's probably to be expected. Faced with a tight labor market and booming economy, small and mid-sized manufacturers are turning to cobots to help get the most out of their skilled workforce. But it's also impossible to miss the economic argument being touted, which usually takes the form of an annual labor cost savings.

Kay Manufacturing estimates that figure at $150,000 with their new UR cobot. So far, that cost savings is enabling companies like Kay to take on more demand. As the market matures, and as the currently strong economy inevitably slows in years ahead, demand for manufactured goods will also slow.

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In that scenario, it's easy to imagine that technology investment will start to become more of an either/or proposition where workers are concerned.

At this stage, at least, the point is academic. Employment is strong and the industrial automation market is red hot. Neither is likely to change in the foreseeable future.

In the murky yonder, though, there are genuine labor challenges brewing. Milestones like this will likely be seen as bellwethers in the postmortem.

from zdnet.com

3D Printing: A Game-Changer for the Automotive Manufacturing Industry

2018-07-19T19:51:00.003-04:00

Technology and innovation are reshaping industries across the world at a breathless and breakneck speed. 3D printing or additive manufacturing is one technology that has revolutionized the automotive industry. Significant advances in the field over the past decade have transformed the design, development, manufacturing, and distribution processes in the sector. They have made way for novel designs, lighter and safer products, shorter lead times, and lower costs.

Hence, 3D printing has become the darling of the automotive world, enhancing the functionality and value of existing products in every way. The concept seems new but has been around for more than 30 years. It involves a process where 3D design data described in a digital file is used to develop a component by depositing materials in layers. The materials used in 3D printing include a wide range of metals, plastics, and composite materials.

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The market for automotive 3D printing has been experiencing phenomenal growth over the years since the advent of the technology. A report by Allied Market Research states that the automotive 3D printing industry is likely to reach $2.73 billion by 2023, growing at a CAGR of 19.7 percent from 2017 to 2023. The need for efficient management of logistics, as well as reduced manufacturing time and associated costs, is driving the demand for the industry. Therefore, 3D printing exhibits wide applications within the sector for prototyping and tooling, research and development, and product innovation. On the other hand, the market faces certain challenges such as high cost of 3D printing software and the dearth of skilled labor.

The additive manufacturing field is highly competitive and, therefore, large and small players in the space focus on specific capabilities that can lead to greater competitiveness. Some of these capabilities include fewer design restrictions and direct production of final components by eliminating the need for new tooling. Currently, several developments are taking place in the industry as follows:

• Local Motors installs world’s largest composite 3D printer

Local Motors, a vehicle manufacturing company based in Arizona, recently completed the installation of a composite 3D printer called the Thermwood LSAM at its Knoxville, Tenn., micro-factory. Considered the largest in the world and spanning 10 feet by 40 feet, the machine will be used to print components for the company’s innovative Olli vehicle, an autonomous 3D printed shuttle bus. The Thermwood LSAM system was developed with the intention of manufacturing large-scale structures and parts using composite materials and an additive approach.

Credit:3D-Printed Olli by LMILocal Motors recently completed installation of a composite 3D printer — considered the largest in the world — at its Knoxville, Tenn., micro-factory that will be used to print components for the company’s Olli vehicle, an autonomous 3D printed shuttle bus.
• Audi adopts Stratasys 3D printing
In June 2018, German automobile manufacturer Audi announced that its Pre-Series Center and Plastics 3D Printing Center in Ingolstadt, Germany, adopted Stratasys 3D printing methods. Stratasys’ J750 full-color, multi-material 3D printer is used to produce full-color physical models of automotive parts, reduce the time needed for prototyping, and accelerate the design verification process. The design verification process is crucial in automotive manufacturing as it determines the approval or denial of new design concepts before a new vehicle is developed. According to Audi, it has achieved prototyping lead time reductions by up to 50 percent for certain parts with full-color, multi-material printing capabilities. One of the components that has benefitted from the printer is tail light covers of the vehicle. The covers were typically prototyped using milling or molding and had to be made in multiple parts.

• Wipro3D launches center for metal 3D printing
In March 2018, Wipro3D, the additive manufacturing unit of Wipro Infrastructure Engineering, introduced a state-of-the-art solution and experience center for metal 3D printing in Bengaluru, India. The first-of-its-kind center which measures 12,000 square feet was inaugurated by Wipro Chairman Azim Premji. Equipped with leading-edge build technology, post-processing, research, characterization, and validation facilities, the center is the country’s foremost fully integrated metal additive manufacturing facility, recommended with AS9100 Rev D certification.

• AMFG launches AI software platform for industrial 3D printing
In June 2018, a novel software platform that employs artificial intelligence to automate additive manufacturing production was launched by AMFG, a leader of automation software for industrial 3D printing. The AI capabilities of the company provide manufacturers with complete production automation for end-use parts, including scheduling automation, printability analyses, and post-processing automation.

• Coherent acquires O.R. Lasertechnologie GmbHIn May 2018, Coherent Inc., a leading provider of laser and laser-based solutions, acquired O.R. Lasertechnologie GmbH, a company that manufactures high-precision tools for laser additive manufacturing with the aim of increasing the former company’s product portfolio in additive manufacturing. The acquisition provides Coherent with a complementary product line that increases its solutions portfolio in additive manufacturing. Moreover, the deal allows the latter’s products to seamlessly integrate with the former’s current offering. O.R. mainly deals with direct metal deposition and selective layer-melting technologies and systems cutting, welding, marking, and engraving serving industries such as automotive, dental, aerospace, and others.
from areadevelopment.com

Global sales of industrial robots log staggering rise

2018-07-19T19:35:00.001-04:00

Sales of industrial robots shot up a staggering 31 percent last year.

That's according to new data from the International Federation of Robotics, a major industry trade group. The data confirms previous anecdotal reports, as well as data from the Association for Advancing Automation (A3).

The biggest growth came from China, where sales rose 58 percent. Sales growth in the U.S. was modest by comparison, reaching just 6 percent.

The strongest growth sectors were the metal industry, the electronics industry, and, somewhat surprisingly, the food industry.

Automation has been a growing trend in fast food, with companies like Domino's and Miso Robotics racing to automate food preparation and delivery amid increasing wages industrywide.

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Despite previous indications, demand for automation in the automotive industry, which has been the pillar of industrial automation since the 1950s, continues to be strong.

Global demand in the automotive industry rose 21 percent.

"The growth of industrial robots continues at an impressive pace worldwide," says Junji Tsuda, President of the International Federation of Robotics. "Key trends such as digitalisation, simplification and human-robot collaboration will certainly shape the future and drive forward rapid development."

Falling prices account for some of the growth, but another factor is the increasing accessibility and ease-of-use of collaborative robots.

Many tabletop models used in a variety of industries have become intuitive to set up and easily programmable through demonstration.

Sales growth for task-agnostic, flexible industrial robots is expected to continue throughout 2018 and beyond.

from zdnet.com

Industrial automation market will approach $210bn in 2018

2018-07-19T16:13:00.000-04:00

The global market for industrial automation equipment was worth an estimated $202.2bn in 2017, and is predicted to grow by 3.8% this year to reach $209.8bn, and by a further 4% during 2019 to hit $218.2bn, according to the latest analysis by IHS Markit. It says that the growth is being driven by the strong global economy, and by the expanding production of increasingly automated machines.

According to IHS, rising industrial production typically follows a stronger world economy. It reports that the global GDP (gross domestic product) expanded by 3.2% during 2017, and forecasts that it will increase by a further 3.4% in both 2018 and 2019.

The forecaster expects that total industrial capital expenditure will grow by 6% in 2018 (double the 2017 figure), before dropping to 4% in 2019.

In 2017, many smart manufacturing initiatives began to emerge, especially in countries such as the US, Germany and China. However, IHS Markit predicts that until these projects start to achieve returns, many multinational end-users will only accept trials of new technologies that are funded by equipment vendors.

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It expects some companies to close their doors to new proof-of-concept smart manufacturing projects in 2018, until existing and ongoing projects have been completed, or show a return on investment.

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The analyst says that during 2017, automation equipment accounted for 37.1% of the total global automation market, followed by power transmission equipment on 32.9%, and motors and motor controls on 30%.

from drivesncontrols.com

Industrial Automation: How Important It Is to Choose the Right Motion Control Components

2018-07-19T15:05:00.001-04:00

Industrial automation dates back to the use of relatively simpler pneumatic and hydraulic systems for basic motion control operations. Over the last few decades, however, industrial automation has come a long way, especially after the arrival of the internet, robotics, and now artificial intelligence. From manufacturing to transport, advanced motion control systems have now made it possible to achieve this level of industrial automation.

Some of the smart devices used in motion control systems can directly communicate with other machines or make their own decisions. Still, the essential components of a motion control unit such as motion controller, motor, feedback device, and amplifier remain the same, although they have become smaller and smarter. This may seem obvious, but designers have to choose the right components with the precise configurations to get the desired performance from a system.

Navigating through a Complex Web of Choices

With the advancement in technology, designers have to choose from a wide variety of microprocessors, programmable logic technology, power semiconductors, motors, amplifiers, mechanical elements, sensors, and application software. Naturally, the choice goes well beyond merely selecting high-end components. It also involves studying if the selected components will work harmoniously in the desired system.

Thousands of vendors are trying to sell sophisticated motion control components. But, not all of them are made equal. Failure to verify the interdependency and compatibility of the various parts of the system can waste valuable time and money. Consequently, only the designers with a clear understanding of the basics of motion control will be able to design such systems.

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Maintaining High Precision Speed and Motion at Nanometer Level

Industrial automation across all sectors is demanding smaller and smarter precision motion control. However, as the size of the motion control system continues to shrink, maintaining high precision speed and motion at the nanometer level becomes increasingly challenging.

The market is flooded with new nano-precision mechanisms, novel position sensing, and force feedback technologies every day. But, only selecting the right components and positioning them accurately can help you overcome this problem. This, in turn, requires a clear understanding of motion control fundamentals. However, this also means, motion control engineers and designers have access to motion technologies that can fit a broader spectrum of industrial applications.

Dealing with Functional Safety Issues

When it comes to motion control systems, operator safety is a central design issue. In most motion control systems such as presses, conveyors, or assembly lines human operators have to interact with moving components directly. That’s why designers and engineers must assess the risks posed by the parts of a system before going ahead with the design idea.

Sometimes, however, using inherently safe components isn’t enough. An additional layer of safety components such as electrical or pneumatic safety circuits is also required. Some examples of such safety features include safe exhaust to release excess pressure, safe stop to prevent potentially hazardous movements, and safe speed limits to move actuators at safer speeds. But, care should be taken that the safety mechanism itself shouldn’t trigger a potentially hazardous movement.

Designers can ask the suppliers or manufacturers for guidance about the safety components and assemblies that meet the specific performance level requirements. Without the understanding of the motion control basics, one can’t design motion control devices with appropriate safety features.

Lowering Designing and Ownership Costs

Machine breakdown and unplanned downtimes have always hampered productivity. The sole purpose of industrial automation is to save the time, effort, and money wasted due to such downtimes. In fact, with the advancement of technology, the need for durable and affordable industrial automation has also gone up.

What is the point of achieving high-precision performance if the cost is prohibitive? On the other hand, compromising on the quality of components to reduce costs can result in safety risks and lower productivity. If you have a clear understanding of how motion control basics work, you will be able to design a system that lasts longer and costs less.

Conclusion

Industrial automation is on the rise, and it primarily depends on motion control systems. That’s why it is necessary to design durable, high performance, and affordable motion control devices which, in turn, is only possible if you have a thorough understanding of how the fundamentals work. These basics can help you navigate the complex and ever-changing landscape of automation technology. Hopefully, this infographic will help you understand the relationship between industrial automation and motion control basics.

from roboticstomorrow.com

Consumer Support for Self-Driving Cars Is Up, But Remains Below 50%

2018-05-30T20:30:00.000-04:00

Consumer interest in self-driving cars is up despite recent fatalities involving models from Uber and Tesla (TSLA - Get Report) , but less than half of Americans are willing to use the emerging technology, a new Massachusetts Institute of Technology survey finds.

"The key here is that this technology is an evolution, not a revolution -- this is going to take time to evolve," said researcher Bryan Reimer, who unveiled the study Wednesday at a Boston-area conference sponsored by MIT's AgeLab and the New England Motor Press Association.

MIT and NEMPA have surveyed consumers for three straight years to gauge how likely Americans are to buy self-driving vehicles, which tech companies like Alphabet and automakers like General Motors are spending big bucks to develop. Last year's survey found only lukewarm consumer interest in the technology, with 48% saying they would never purchase a self-driving car.

But this year's poll found signs of improving support. For instance, just 33.6% of this year's roughly 3,500 survey respondents said they aren't willing to use self-driving cars. By contrast, 40.1% of survey respondents said they'd be interested in doing so, while 26.3% weren't sure.

Support also rose across all age groups except drivers older than 74. For example, 33% of 25- to 34-year-olds felt comfortable with self-driving cars, up from 20% a year ago.

"There's a much more positive outlook that what we observed a year ago despite several tragic events," Reimer said.

He called the generally rising support "phenomenal" given that MIT conducted its latest survey just days after Uber made headlines over a fatal crash involving a self-driving test car. Tesla has also had deadly crashes involving its autopilot function, in which vehicles operate themselves but humans are supposed to take over in emergencies.

Negative news stories about these accidents have been a major pothole for self-driving cars on the road to public acceptance. For example, MIT's latest poll found that among the 55.7% of respondents who said something had impacted their view of the technology in the past year, 79% cited crashes and 43% referenced the Uber fatality specifically.

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But the poll also found that 58.4% of respondents said they'd use autonomous cars if they were no longer able to drive, while 64.9% would do so if auto companies make the vehicles as safe as human-driven ones.

"I do believe highly automated vehicles are the future," Reimer said. "The only question is how many years it's going to take us to get there."

from thestreet.com

Researchers create the first 3D-printed corneas to combat blindness

2018-05-30T20:05:00.001-04:00

Researchers at the University Of Newcastle have announced they’ve managed to 3D print corneas – the outermost part of the human eye.

Dr Steve Swioklo (left) and Prof Che Connon (right) watching a cornea being printed.

This is incredible, life-changing news for a lot of folks. Worldwide, 10 million people require surgery to prevent corneal blindness from diseases like trachoma. On top of this, almost 5 million are completely blind due to corneal scarring from accidents or illnesses.

This high-tech method of producing corneas could end all that.

It works by taking stem cells from a health donor’s cornea and mixing it together with a gel, creating what researchers have deemed “bio-ink.”

“Our unique gel – a combination of alginate and collagen – keeps the stem cells alive whilst producing a material which is stiff enough to hold its shape, but soft enough to be squeezed out the nozzle of a 3D printer,” Che Connon, Professor of Tissue Engineering at The University of Newcastle, said.

The 3D bio-printer was described as “low-cost” and only took 10 minutes to print a cornea.

To customize a cornea for a specific person, the scientists are able to scan a patient’s eye, before creating one that matched the individual’s size and shape.

There’s a drawback though: the tech isn’t ready for mass-use just yet.

Professor Connon says: “Our 3D printed corneas will now have to undergo further testing and it will be several years before we could be in the position where we are using them for transplants.”

Still, it’s good to see a 3D-printing project with lots of potential. About five years ago, the technology was regarded as the next big thing, but it hasn’t quite lived up to expectations since. This project shows there’s still a lot of hope for 3D-printing and is a better case study of its potential than, you know, recreating your own face.

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To conclude, I have to circle back to the opening line of the release, specifically about how “the technique could be used in the future to ensure an unlimited supply of corneas.”

Imagine that, unlimited corneas. Everywhere. Two, nay four, seven, ten in each eye. Corneas on toast, corneas covering your car. Printing your own corneas and then throwing them away only to print some more just because you can. Fields stretching into the distance, bathed in a golden light that bounces off nothing but corneas. A cornucopia of corneas. Corneas for everyone. Corneas forever.

Sounds like my kind of world.

from thenextweb.com

Global deployment of industrial robots to double by 2020

2018-05-30T18:48:00.001-04:00

By the year 2020, the number of industrial robots in use in factories around the world will have doubled from 1.47 million robots in 2014 to more than 3 million in 2020, according to the International Federation of Robotics (IFR).

The rise in the global deployment of industrial robots, according to the IFR, is a result of increased adoption of industrial automation by both companies and nations.

"Automation is changing the way we work and, to an increasing extent, the way we live," stated a position paper from the IFR. "Automation improves productivity and enables companies, and nations, to remain or become competitive. It enables new business models focused on providing new goods and services and helps companies improve the efficiency and flexibility of supplying those goods and services. Economists agree that increased productivity is key to improving Gross Domestic Product, the value of goods and services produced in a country, and in turn, jobs and wages."

Junji Tsuda, president of the International Federation of Robotics, also commented: "IT like robotics process automation is by far the biggest contributor in transforming people's jobs. "Companies and governments must collaborate to ensure workers have the skills that the technological change requires."

Another key indicator of the rise in robotics is an increased focus on training and education. An automatica survey (automatica trend index 2018) of 7,000 employees across seven countries (USA, China, Japan, Germany, France, Great Britain, Italy) shows that nearly 70% of workers believe that robotics and automation offer the opportunity to qualify for higher-skilled work—a technological shift that would require targeted training and further education for employees.

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One such country that has placed an emphasis on this is Singapore, with its SkillsFuture initiative. Employers in Singapore are asked to spell out expected changes, industry by industry, that they expect to happen over the next three-to-five years, and to identify the skills that would be required. These answers are then used to create "industry transformation maps" designed to guide individuals on this path. Since January 2016, every Singaporean above the age of 25 has been given $345 credit that can be used to pay for any training courses provided by 500 approved providers, including universities and massive open online courses.

from vision-systems.com

Global Virtualization in Industrial Automation Market 2018-2022

2018-05-09T18:51:00.001-04:00

The "Global Virtualization in Industrial Automation Market 2018-2022" report has been added to ResearchAndMarkets.com's offering.

The analysts forecast the global virtualization in industrial automation market to grow at a CAGR of 7.32% during the period 2018-2022.

Virtualization is a technology that makes use of software to create multiple simulated environments from a single hardware system. Hypervisor is a software that disengages virtual machines (VMs) from host servers and assigns computer resources to the VMs.The analysts forecast the global virtualization in industrial automation market to grow at a CAGR of 7.32% during the period 2018-2022.

The report covers the present scenario and the growth prospects of the global virtualization in industrial automation market for 2018-2022. To calculate the market size, the report presents a detailed picture of the market by way of study, synthesis, and summation of data from multiple sources.

According to the report, one driver in the market is ability to run multiple operating systems on a single physical server. Operations in industrial plants require multiple servers to run different operating systems and applications. Industrial plants have different applications and operating systems that support automated devices such as SCADA, PLC, and HMI.

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The report states that one challenge in the market is physical server failure affects an entire system. The major challenge of deploying virtualization is unplanned downtime. Operators lose visibility of the failure in ICSs such as PLC, SACADA and HMI, after which they are required to revert to manual operations.

Companies Mentioned

Citrix Systems
IBM
Microsoft
Oracle
VMware

Key Topics Covered:

1: Executive Summary

2: Scope Of The Report

3: Research Methodology

4: Market Landscape

5: Market Sizing

6: Five Forces Analysis

7: Customer Landscape

8: Market Segmentation By End-User

9: Regional Landscape

10: Decision Framework

11: Drivers And Challenges

12: Market Trends

13: Vendor Landscape

14: Vendor Analysis

15: Appendix

For more information about this report visit https://www.researchandmarkets.com/research/8wfjm2/global?w=4

Making industrial automation a profit engine

2018-05-09T18:37:00.002-04:00

Technology advancements have transformed many aspects of the manufacturing industry, rendering old models of production counterproductive to gaining market share—or even staying afloat. The Industrial Internet of Things (IIoT) has changed operating strategies across the board. Businesses are working smarter and more efficiently on everything from implementing new process control and automation systems to managing their supply chains, all ostensibly to drive more profit. But are they?

Even with all of today’s technology advances at their disposal, manufacturers are still struggling to measure and control the business value their process automation and control systems deliver. For decades, these systems were really only focused on improving the efficiency of the process, not total business performance. One reason for this was the rigidity of the automation-system architectures, which reduced the ability for agile solutions because they did not match plant and enterprise topologies. Manufacturers used traditional automation systems to control the efficiency of manufacturing processes, but not the profitability produced by the industrial assets.

So, while distributed control systems have historically done an exceptional job of controlling process performance, they have had little to no impact on total business performance. In fact, not only have these systems been costly to configure, engineer, install, implement and operate, the financial impact they have on business performance (especially the profitability of the operation) has traditionally not been properly and accurately measured because of technological limitations. But with added functionality from new IIoT technology, the potential value a DCS can provide is skyrocketing.

IIoT to the rescue

Connectivity, networking, big data, predictive analytics, cloud computing, fog computing, wireless communication, cyber physical systems, edge computing—IIoT is gaining acceptance each and every day, and it offers unprecedented promise.

But while all the discussion swirls around emerging technology and its potential, thought leaders know IIoT can help industrial manufacturers extend real-time control across their value chain because it has the potential to finally dissolve the IT-OT barrier.

In fact, with the integration of industrial automation/communications/networking, those siloes are already starting to break down. These integrated technologies enable better operations and business control because the industrial workforce and its business leaders have more and better access to critical real-time operations and business data, complemented with the proper context and advanced tools that help them act on that data from anywhere in the world.

This portends future process-automation systems architectures that will be incredibly agile, able to match the industrial-operational architecture that defines how a specific plant works (based on a hierarchy of assets, not processes). Soon, automation and control architectures will start controlling asset performance from the bottom up, beginning with the equipment assets of a plant—a pump, for example—and ending at the enterprise value chain. In short, the control systems of the future will be asset-centric, not process-centric.

That will unlock the true financial value of IIoT. But how can we make it happen?

Making industrial automation a profit engine

Technology advancements have transformed many aspects of the manufacturing industry, rendering old

Schneider Electric Process Automation's Peter Martin

models of production counterproductive to gaining market share—or even staying afloat. The Industrial Internet of Things (IIoT) has changed operating strategies across the board. Businesses are working smarter and more efficiently on everything from implementing new process control and automation systems to managing their supply chains, all ostensibly to drive more profit. But are they?

IIoT to the rescue

That will unlock the true financial value of IIoT. But how can we make it happen?

Turning your business into a profit engine

Implementing any new system is always accompanied by the probing inquiry: How will this contribute to growing the bottom line?

With IIoT, the answers are becoming clearer because (now more than ever) manufacturers have an opportunity to begin controlling all their business variables in real time. That is critically important when we consider how quickly business moves today. For example, a generation ago companies would buy their electricity at a set monthly or even quarterly price, but today’s energy prices change almost minute to minute.

That is the case with many other commodities and feedstock that impact the enterprise value chain. Therefore, managing the business month-to-month based on information accumulated and stored in an ERP system doesn’t make sense. To be successfully competitive, manufacturers have to look at how they can control all their business variables in real time, not just the efficiency of their process. Among those variables are the real-time safety, including environmental safety and cybersecurity, the real-time reliability and the real-time profitability of the operation.

All of the aforementioned business variables are changing quickly, yet reacting and planning for this change has not kept pace. Many business functions, such as scheduling and planning, have historically been managed on a weekly or even monthly basis; by the time companies receive updates from their resource planning systems, the information is no longer relevant to the business decisions they need to (or should have) made.

In the age of IIoT, business managers and plant personnel alike have never had greater opportunities to measure and improve the profitability of their operations in real time. Driving operational-profitability improvements starts with optimizing the performance of each industrial asset so that it performs in the safest, most reliable, efficient and profitable manner possible. With stronger computing power and advanced technology, it is possible to put real-time control, interoperability and communication everywhere, from the simplest plant asset all the way up to the supply chain. Manufacturers can incorporate big data and predictive analytics to measure how every asset is contributing to its operational profitability. Empowered with the ability to control every asset—even intangible assets like energy costs and raw material use—in real time, companies are now able to conduct business whenever it is most profitable for them.

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Operations and management can finally be in sync, with management understanding business constraints at every level of the operation and plant personnel understanding the impact their decisions have on profitability in real time.

Weaving profitability into digital transformation

Many industrial manufacturers have begun to preach digital transformation, but technology for technology’s sake does not truly transform business potential without a clear vision and the right technology implementation. IIoT offers unprecedented promise for finally realizing value through real, measurable improvements to all business variables, most notably profitability. And this is only made possible when manufacturers break down the barrier between IT and OT.

from smartindustry.com

Volvo’s Most Ubiquitous Contribution to the Auto Industry

2018-05-09T18:22:00.000-04:00

In 1959, Volvo engineer Nils Bohlin created the three-point seat belt which was launched in their Volvo Amazon and Volvo PV544 models.

Bohlin previously worked at Saab as an ejector seat designer for fighter planes before being hired by Volvo as the first chief safety engineer. Up until that point, two-point seatbelts were the only form of restraint used, and were known to cause severe internal injuries.

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While Volvo could have kept the design and profited from it, they opened up the patent to their competitors as they believed it was too important in their quest to prevent automobile fatalities. Since 1975, an estimated 255,000 lives have been saved by seat belts in the US alone.

from thomasnet.com

How 3D printing is revolutionizing the housing industry

2018-05-09T18:18:00.000-04:00

If you build it, they will come. And if you 3D-print it, they will come faster, cheaper and more sustainably.

We live in an era of overpopulation and mass housing shortages. Yet we also live in a time of phenomenal digital innovation. On the one hand we have major crises affecting the health, liberty and happiness of billions of people. But look at the other hand, where we have potential for life-changing technological breakthroughs at a rate never before seen on this planet.

Our challenges are vast, but our capabilities to produce solutions are even greater. In the future, we will remember this moment in time as a pivotal one. It is now — not tomorrow, and certainly not five years from now — when technology and innovation are disrupting multiple major industries, including those of housing and construction, at breathless and breakneck speed.

Innovators around the world are hard at work to change the way we design, build and produce our homes, and all of this will result in massive change to the housing status quo. Harnessing the revolutionary power of 3D printing, companies from Russia to China, the U.S. and the Netherlands have already proven that not only can a home be 3D-printed, it can be done cheaply, efficiently and easily.

Here are just a few ways 3D printing is already transforming the way we live.

Speed

In March 2017, Apis Cor, 3D-printing specialists with offices in Russia and San Francisco, announced they had produced a 3D-printed home in just 24 hours. That means that from the time you drank your coffee yesterday to the time you sat down for cereal this morning, they produced the self-bearing walls, partitions and building envelopes of an entire home, installed it on site and added the roof and interior finishings. It happened in the dead of winter in a tiny Russian town named Stupino, and it was done using Apis Cor’s on-site printer, which means that the massive cost and logistical hurdle of transporting parts and building materials from factories to a home site was almost entirely eliminated.

Think about the possibilities: You select the site where you want to build your home, Apis Cor brings in their 4.5-meter-long printer, the raw materials are set up and within one single day, your home is printed and ready for you. Compare that to the traditional six- or seven-month construction time the industry is used to, and you’ll begin to understand the scope of potential disruption.

The speed of technological innovation here is also exponential and mind-blowing; just one year before Apis Cor’s breakthrough, we in the 3D-printing industry were marveling over Chinese construction company HuaShang Tengda, who set their own record by 3D-printing a two-story home in a month and a half. Consider that, for a moment: This industry is moving so quickly that construction time has been slashed from 45 days to 24 mere hours in the span of a single year.

Cost

Housing prices in America have skyrocketed over the past 50 years, with the average price for a home now surpassing $200,000. And remember, that’s just the average — if you live on the East or West Coast, chances are you’re going to be shelling out something closer to the half-million dollar mark (or more!).

According to a report from the McKinsey Global Institute, a full one-third of people who live in cities will find decent housing out of their reach due to cost by the year 2025. And construction costs are the primary barrier — the report also states that it will take between $9 trillion and $11 trillion just to build the necessary houses to flip that supply-demand ratio and make housing affordable in that time.

Of course, that’s taking only traditional methods of construction into account. But Apis Cor’s 24-hour home was made for around $10,000. HuaSheng Tenga’s homes were made with only 40 percent of the materials traditional construction usually requires, in 30 percent of the time. That represents massive savings in labor and material costs. And these companies aren’t alone — dozens of other firms are exploring cheaper and less complicated methods for building the roofs we all need over our heads, and slashing prices in the process.

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New Story, a Silicon Valley-based nonprofit that builds housing in the developing world, just unveiled a new 3D printer at SXSW that can print a house in less than a day for $4,000. DUS Architects — a Dutch architecture studio that has been 3D-printing houses since 2012 — has unveiled the KamerMaker, a huge 3D printer that can build using local recycled materials. This slashes transport, material and manufacturing costs, all driving down costs.

The bottom line

What’s so revolutionary about 3D printing is that its potential is limited only by our imaginations. If the past few years have taught us anything about this industry, it’s that barriers of size, scope and material do not apply to the potential that 3D printing brings to the manufacturing market. From cars to food, to the houses we live in, the industry isn’t just gearing up for a shakeup. It’s in the throes of it already, because change is happening now.

from techcrunch.com

Siemens to Roll Out New Simulation Platform for Self-Driving Vehicles

2018-03-28T17:39:00.000-04:00

Siemens today will introduce a computing and simulation platform aimed at speeding the validation and verification of autonomous cars.

The new platform, to be rolled out at a company event in Chicago, could enable automotive engineers to reduce the amount of physical testing that would otherwise need to take place on public highways and test tracks. Siemens engineers say that the platform would allow automakers to simulate billions of test miles and countless scenarios that could take place in real life. “We do believe that in the end, you can account for 99.99999% of everything that can happen on the roads,” Martijn Tideman, director of products for TASS International, a Siemens business, told Design News.

Siemens’ new model-based platform offers a solution to validation and verification of autonomous car. (Source: Siemens)

The new platform involves existing technologies from two relatively new Siemens acquisitions. Those include TASS International’s PreScan simulation environment and Mentor Graphics DRS360 data fusion platform. PreScan, which has existed for about a decade, is a physics-based simulation platform for developing and validating automated systems. DRS360, meanwhile, is a product that takes raw, unfiltered data from cameras, radar, and Lidar systems and fuses it for subsequent use by a central processor.

In autonomous car applications, PreScan would feed the simulated data to DRS360, essentially as if it were real-world information. “DRS360 doesn’t know if it’s real or virtual because our sensor data is so good,” Tideman said. “So it enables you to test massive numbers of scenarios as if they were real.”

The ability to do that is critical to the auto industry right now, because verification and validation of autonomous cars is such a monumental task. Many industry engineers believe the sensors, actuators, and software are already in place for the creation of a Level 5 car, but they still need to “teach” vehicles how to react to the billions of possible scenarios that could take place on real-world roads. To do so on public highways and test tracks would be impossible, they say.

“There are voices in the industry talking about the needs for billions of miles of testing before a full validation cycle is complete,” noted AminKashi, director of ADAS/AD driving for Mentor Graphics, a Siemens company.

Products such as PreScan could change that, however. PreScan would enable developers to change the simulated parameters from, say, urban to rural, dark to light, rainy to sunny, or sleet to snow. “PreScan is able, not only to create a scenario, but also to re-create it for the maximum number of different situations and environmental conditions,” Kashi said.

Siemens’ end-to-end solution, complete with the ability to feed simulated data to a fusion platform, is believed to be unique in the industry right now. “There are bits and pieces of this out there right now,” Phil Magney, founder and principal advisor for VSI Labs, told Design News. “But no one has tried to stitch together and end-to-end solution for automated vehicles.”

Waymo probably has an in-house solution right now but is not making it commercially available. Nvidia Corp. may also offer a similar solution very soon (possibly as early as this week) but has not released it yet.

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The development of such systems is being driven by a dire need for autonomous simulation solutions in the auto industry right now. Experts say that Level 5 autonomous cars may still be a decade or more away, largely because validation and verification of them is unlike anything in the 130-year history of the industry. The need to log billions of physical test miles would only add to the long wait, which is why simulation is so critical, they say.

“The autonomous car changes everything,” Magney said. “It heightens the role that simulation plays.”

from designnews.com

Siemens talks digitalization, edge computing at Siemens Factory Automation SCADA/IPC Days 2018

2018-03-07T13:49:00.000-05:00

From February 19-22, 2018, in San Antonio, Texas, approximately 130 people gathered for four days of product presentations, emerging technology discussions and a market trend outlook at the Siemens Factory Automation SCADA/IPC Days 2018. Members of the Siemens management, sales and support team joined their Solution Partners and a diverse assortment of end user companies from various market segments to review new product offerings in the IPC segment of the Siemens portfolio, plus a number of platforms in the SCADA segment. The event was hosted by the product marketing teams for Factory Automation, based in Norcross, Georgia.

Following a welcome session on the first evening, a series of presentations were made on day two to the entire group by Siemens management and technical thought leaders, covering the digital factory strategy and the company’s move to Digitalization, the current theme for the Siemens marketing message across its entire industrial platform. Key speakers were Kevin Lewis, Russell Barnes, Thorsten Julich, Bernd Raithel, Michael Steigberger, Bernd Staufer and Tom Elswick. The primary message takeaway for the group was that Digitalization will hallmark the factory of the future and SCADA will be the “digital doorway for data” in that rapid evolutionary process, as it impacts all industries, both discrete and process.

There were also presentations on cloud computing and edge computing, the constituent elements of the Digitalization trend, comprising both hardware and software elements. This discussion led directly into the program’s introduction of various new thin client IPC product offerings and the latest version of SIMATIC WinCC SCADA systems.

In addition to the technical presentations and market overviews, a very interesting end user application was detailed by end user Derek Thoma of Hop Valley Brewing, a Miller/Coors company. Thoma spoke on the marked improvements in production and product quality tracking made possible by the advanced IPC and HMI provided by Siemens, in addition to the SCADA software for process monitoring and management.

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Day three began with a review of new IPC products and emerging technologies on the horizon from Siemens, followed by more intense product and software breakout workshops, tagged the Wisdom Series by the event coordinators.

Finally, day four offered direct consultation from the Siemens product specialists gathered at the event, including the Solutions Partners, who represent the system integrator community at Siemens, as they bring the products, application engineering, installation and service, plus related data gathering and process control products to the process industries. In addition, those interested in becoming a WinCC Specialist were offered the opportunity to take their certification test during the event.

Guest instructors were present during the workshop sessions to discuss such topics as Automation for Networks, Using WinCC to Build a Toolbox, Batch Tracking Made Easier with WinCC Archives, Mindsphere and Cybersecurity, and the Industrial PC of tomorrow. Rapidly developing MindApps for performance optimization on all types of industrial manufacturing and process machines were also discussed in detail, as Siemens seeks to assist its customer base and machine builders alike to gather, process, analyze and apply relevant data.

from automation.com