Journal of Industrial Engineering and Management

Improved sustainability in cellular manufacturing systems: Sensitivity analysis of penalty function driven NSG-II

Melusi Mithi Sibanda, Jared Padayachee — Mon, 19 Jan 2026 15:08:32 +0000

Purpose: Research suggests that material handling costs account for 20-50% of production costs. Furthermore, these production cost could be reduced by 10-30% by dynamically changing the layout. We propose an integer programming model to sustainably solve plant layouts in a financially conservative, yet environmentally friendly way.

Design/methodology/approach: We propose a bi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) approach to optimizing Dynamic Cellular Manufacturing Systems (DCMS). The mathematical model’s first objective function minimizes economic cost, while the second objective function minimizes environmental emissions. The NSGA-II solver uses the penalty approach to handle constraints. The solver is customized beyond the traditional NSGA-II, such that constraint violating solutions are repaired, and unique solutions are prioritized to enhance population diversity and exploration.

Findings: Although a manufacturing plant layout may be optimal for a particular demand period, when the demand changes that system may not be optimal for the new demand period. Extensive simulation shows that our bi-objective model dominates the single objective model from literature. Adding an environmental second objective to DCMS reveals that the most economical solution is often the least environmentally friendly approach, and vice versa. A convex relationship is observed between the two objectives. A weighted compromise is required when setting up a sustainable production system.

Research limitations/implications: Only carbon emissions were simulated. Hazardous liquid waste, Energy consumption, and water consumption were not considered.

Practical implications: Manufactures and their contracted line builders will need to consider environmental implications when setting up a production line. Decision makers need to be aware that the most cost conservative approach may lead to significantly higher carbon emissions.

Social implications: The social pillar of sustainability was incorporated via a set of constraints in the mathematical model of this study. The solution space showed that the model was not restricted by this objective.

Originality/value: The value add of this work is presented in a case study comparison of our multi-objective model against a single objective model from literature. The multi-objective model dominates the literature model giving invaluable insights to possible improvements to previous research work.

Autonomous vehicles in warehouse inventory management: Insights from Malaysia's national telecommunication and digital infrastructure provider

Sairul Izwan Bin Safie — Thu, 05 Feb 2026 10:51:22 +0000

Purpose: This study examines the role of autonomous vehicles (AVs) in warehouse inventory management, with a specific focus on Malaysia’s national telecommunication and digital infrastructure provider. It identifies key challenges, operational efficiencies, and strategic implementation considerations to enhance supply chain resilience.

Design/methodology/approach: A mixed-method research approach was employed, integrating qualitative interviews with logistics experts and a quantitative survey of warehouse personnel. Thematic analysis was applied to qualitative data, while Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze quantitative findings.

Findings: The study highlights that workforce adaptation is the strongest predictor of successful AV adoption, with employee upskilling emerging as a critical factor. Despite AVs' potential to optimize inventory accuracy and streamline operations, challenges such as budget constraints, cybersecurity risks, and system integration complexities persist. Notably, the research reveals a paradoxical misalignment between management support and AV adoption success, underscoring the need for strategic leadership engagement.

Research limitations/implications: The study primarily focuses on a national telecommunication provider, limiting the broader applicability to diverse logistics sectors. Future research should explore AV integration across varied industries and regions to enhance generalizability.

Practical implications: The findings provide logistics managers with an empirically driven framework for AV integration, emphasizing the importance of phased implementation, workforce readiness programs, and system compatibility measures. Additionally, the study informs policymakers on the regulatory considerations necessary for AV adoption in Malaysia’s telecommunications sector.

Social implications: Automation in warehouse management raises workforce displacement concerns, necessitating proactive upskilling initiatives. The study also contributes to sustainable logistics practices by demonstrating AVs’ potential to reduce energy consumption and improve space utilization in warehouse environments.

Originality/value: This research fills a critical gap in AV adoption literature by offering an empirically validated framework specific to warehouse inventory management in the telecommunications sector. It extends the Technology Acceptance Model (TAM) and Resource-Based View (RBV) theories to assess AV adoption drivers and barriers.

Newsvendor's supply chain design considering non-survival risks

Ernest Benedito, Albert Corominas — Fri, 06 Feb 2026 17:12:24 +0000

Purpose: We consider the long-term survival of the newsvendor's supply chain (SC). In this regard, the main contribution of this paper is to identify and analyze two risks that threaten it, both derived from the random nature of the demand, which is inherent in the definition of the newsvendor problem (NVP). These are the risk of a decrease in demand due to unsatisfied demands because of the lack of stock and the risk of bankruptcy of the vendor due to insufficient monetary inflows.

Design/methodology/approach: We present a mathematical model of the newsvendor's supply chain with three components: the Producer (P), the Vendor (V) and the Consumers (C). The model takes into account the relation between the components of the SC, the income and operative costs of P and V and the initial funds of V. We solve the model considering several assumptions related with the cost, the initial funds and the demand of C.

Findings: We identify and analyze two risks that threat the continuity of the newsvendor’s supply chain in the long term. The first comes from the decreasing in the demand derived from the low level of service that can result from optimizing the joint income of P and V without considering a level of service constraint, which is an essential characteristic of any system of inventory management and has deserved little attention in the literature on the NVP. In fact, an unacceptable low level of service is hardly compatible with the assumption that the law of the demand does not change throughout the time. The second risk is that of V’s bankruptcy due to insufficient monetary inflows, what can happen even if the expected value of V's daily net income is positive. Indicators are proposed to measure these risks and procedures to calculate them.

Practical implications: First, in the design of the Supply Chain, under conditions similar to that of the NVP, the decision maker must compare the options of resort or not to V, considering the consequences on income and risk. Second, the objective of coordinating the SC, understood as the maximization of the joint income of P and V, has the limitation of not taking into account that the consumers, which are also part of the SC, can leave it when they deem that the service is unsatisfactory. Third, P must be aware, when setting the parameters of the SC, that its decisions determine those of V and their consequences; therefore, P must take into consideration the economic survival of V, in order to avoid disruptions in the SC and the negative consequences they imply for P itself.

Originality/value: Our approach is different from the most usual, which is focused on the criteria and the optimization procedures of the vendor. Instead, we consider the whole SC, including one essential component of it, namely, the consumers.

A batch scheduling model on unrelated parallel machines with resource constraints and sequence-dependent setup time to minimize total actual flow time

Thu, 12 Feb 2026 12:47:57 +0000

Findings: The proposed algorithm achieves an average efficiency of 99.32% compared to the enumeration algorithm, with minimal deviation (0.4%). The results validate the main proposition for efficient scheduling, including prioritizing jobs based on due dates, allocating job demands based on machine capacity, and sequencing batches based on size to minimize delays.

Research limitations/implications: The model assumes static machine conditions and predefined job parameters, limiting its applicability in dynamic environments. Future research can extend this approach to incorporate real-time job arrivals or machine breakdown scenarios.

Practical implications: This algorithm provides a practical tool for industries to optimize batch scheduling on unrelated parallel machines, improving production efficiency and reducing operational costs.

Social implications: By improving production scheduling, this model indirectly supports sustainable manufacturing practices through optimal resource utilization.

Originality/value: This study introduces a novel integration of backward scheduling with resource constraints and sequence-dependent setup times, addressing gaps in scheduling research for unrelated parallel machines.

Importance of continuous improvement and emerging technologies on service sector in firms in ab emerging economy

César A. Bernal-Torres, Luis Paipa, Yavar Jarrah-Nezhad, Fernando Crespo R. — Wed, 18 Feb 2026 10:46:13 +0000

Purpose: This study examines the impact of continuous improvement practices and emerging technologies on business performance in the service sector of an emerging economy. It seeks to identify whether these factors contribute positively to competitiveness and how their effects compare to findings from developed economies.

Design/methodology/approach: A survey was conducted among 85 senior executives from medium- and large-scale service companies. The data were analyzed using Principal Component Analysis (PCA), a multivariate statistical method widely used in social science research to identify key patterns and relationships.

Findings: The results contrast with studies in developed economies, where continuous improvement practices and technology adoption are strongly associated with enhanced business performance. In the context of this emerging economy, the findings suggest a more nuanced relationship, highlighting the need for further investigation into sector-specific and regional factors.

Research limitations/implications: The study is limited to a single emerging economy and focuses exclusively on the service sector. Future research could expand the sample size and explore additional industries to provide a more comprehensive understanding of these relationships.

Practical implications: The insights from this study can help business leaders refine their strategies for implementing continuous improvement and technological advancements, ensuring better alignment with the unique challenges of emerging markets.

Social implications: By improving business performance through strategic technological and process innovations, companies in emerging economies may enhance job stability, service quality, and overall economic development.

Originality/value: This study contributes to the ongoing discussion on business performance in emerging economies by providing empirical evidence from the service sector. It offers valuable insights for academics, entrepreneurs, and policymakers seeking to enhance competitiveness and adapt continuous improvement practices to dynamic economic conditions.

Clustering-based column generation and heuristic methods for the container loading problem with practical constraints: A case study

Sezgi Tekil-Ergün, Ferhan Çebi — Wed, 18 Feb 2026 10:46:36 +0000

Purpose: This study addresses a real-world container loading problem (CLP) encountered in a logistics company in Turkey, filling a gap in the literature by solving practical constraints using a state-of-the-art algorithm. The problem involves constraints such as rotations, stackability, loading priorities, and mixed loading constraints.

Design/methodology/approach: To overcome the computational challenges posed by large-scale instances, a novel three-step approach is proposed. First, the K-Means clustering algorithm is applied to group objects with similar dimensions. Then, each group is allocated to containers using a Column Generation (CG) method combined with a 3D-Best Fit Decreasing with Orientation (3D-BFDO) algorithm. Additionally, the CG process is enhanced by integrating a machine learning (ML) model to predict reduced-cost columns, improving computational efficiency and solution quality.

Findings: Extensive experiments demonstrate that the proposed approach significantly improves container space utilization while reducing operational costs. The results highlight the effectiveness of ML and K-Means in enhancing traditional optimization techniques.

Research limitations/implications: The study focuses on a specific set of practical constraints relevant to real-world logistics applications. Further research could explore additional constraints and scalability to different logistics environments.

Practical implications: The approach offers a practical solution for logistics companies dealing with a large-scale CLP by optimizing space utilization and reducing operational costs. The integration of ML into CG presents a viable method for improving decision-making in logistics.

Originality/value: The study bridges the gap between theoretical models and real-world logistics challenges by introducing a data-driven enhancement to traditional optimization techniques. The proposed integration of K-Means clustering and ML into CG represents an innovative contribution to container loading optimization.

Developing an integrated optimization inspection scheme with a flexible sampling mechanism for quality determination based on the process loss index

Armin Darmawan, Afirah Armayfa, Meti Sesa — Wed, 18 Feb 2026 10:46:57 +0000

Purpose: This study examines the quick switching sampling (QSS) system. This well-established sampling scheme incorporates two single sampling plans (SSPs) with adaptive transition rules between normal and tightened inspections. The QSS system dynamically adjusts inspection stringency in response to fluctuations in product quality, implementing normal inspection when quality meets satisfactory standards, and tightened inspection when quality deterioration is detected.

Design/methodology/approach: Traditional acceptance sampling plans often evaluate product quality based on process yield, which overlooks subtle variations within specification limits. To address this limitation, a novel performance metric, the process loss index L_e, was developed to quantify quality loss. This index is calculated as the ratio of expected quadratic loss to the square of half the specification width. Utilizing this index, two models of QSS sampling schemes were constructed by solving nonlinear optimization mathematical models and evaluated using general metrics. The efficacy and characteristics of these schemes were investigated, compared, and discussed.

Findings: The results highlight the potential of QSS systems to enhance the effectiveness of quality control while maintaining stringent quality standards. Besides, the proposed plan demonstrates superiority over the conventional plan in terms of adaptability, particularly with sample size adjustments, when switching to a stricter inspection plan in response to deteriorating lot quality and improved efficiency.

Originality/value: This study presents a novel approach to quality control by integrating the process loss index into the QSS system, offering a fresh perspective on sampling methodologies. The integration of QSS with the process loss index L_e marks a significant contribution to the field of quality control, enabling more nuanced evaluations of product quality and providing a groundbreaking framework for optimizing quality control processes while minimizing sample sizes, thereby enhancing efficiency and effectiveness.

An optimized dependent sampling scheme for mixed quality criteria in feed manufacturing industry

Maria Anityasari, Rivaldo Indrawijaya, Nani Kurniati, Mokh. Suef — Fri, 20 Feb 2026 10:58:36 +0000

Purpose: This research proposed dependent sampling plan incorporating mixed acceptance criteria for entrance quality control of corn kernels, a primary material in the feed manufacturing industry. Mathematical models are involved to determine the alternative samplin plan based on allowable risk levels commonly applied in acceptance sampling practices.

Design/methodology/approach: This research develops alternative dependent mixed sampling plans by solving two non-linear equations simultaneously and satisfying the conditions of two points on the operating characteristic (OC) curve. Each sampling plan is then assessed not only for producer’s (?) and consumer’s (?) risks, but also for total inspection time and financial viability utilizing the benefit-cost ratio (BCR). A goal-programming technique finds the best course of action, providing the best balance between operational costs, inspection time efficiency, and the necessary quality level for the related industry.

Findings: By implementing the proposed framework from this research, entrance quality control at one of the feedmills owned by PT XYZ can be optimized by increasing time efficiency by 72.06%, supported by a promising benefit-cost ratio (BCR) of 9.59. Additionally, in this research can identified the potential to streamline the total number of quality criteria for corn kernels without compromising the ability to capture overall defect variance, using principal component analysis (PCA). With a producer's risk (?) of 2.00% and a consumer's risk (?) of 4.00%, the model P_DMSP(p; 3; 1.17; 2; 4; 2) allowed for the integration of these findings and resulted in a much improved inspection process while preserving acceptable risk levels.

Research limitations/implications: This research focuses solely on the the inspection of corn kernels in entrance quality control at PT XYZ. Future research could extend this approach to other types of raw materials used in the feed manufacturing industry

Originality/value: The majority of earlier research has only examined sampling strategies in terms of allowable risk. By including resource utilisation, this research aims to create a more thorough framework that will be more balanced and useful for implementation.

Impact of Lean tools and green practices on environmental performance in Spanish manufacturing companies

Sergio Palacios-Gazules, Gerusa Giménez, Rodolfo De Castro — Tue, 24 Feb 2026 15:57:03 +0000

Purpose: This study analyses the impact of lean tools on environmental performance and examines whether combining them with green practices can generate positive synergies.

Design/methodology/approach: Using data collected in the 2022 European Manufacturing Survey of Spanish manufacturing companies, a correlation analysis between lean tools and green practices was carried out on the 86 companies surveyed. Furthermore, a Stepwise multiple linear regression was performed between the aggregated Lean and Green independent variables and the dependent variable environmental performance.

Findings: Findings of our study show that green practices, unlike lean tools, are not yet sufficiently developed in manufacturing industries to be meaningful in terms of environmental performance. In the proposed regression model, the aggregate variable Lean was found to have a significant relationship with environmental performance. The Green variable, however, was excluded from the model as it was not significant.

Research limitations/implications: Spanish companies should continue to work on the adoption of green practices in order to benefit in the future from the synergies between these practices and lean tools, as the literature has shown. Findings will be useful for managers in the manufacturing firms to make best strategic decisions. The current study is limited by the relatively small sample size.

Originality/value: To the best of authors' knowledge, this is the first study to examine the impact of lean tools and green practices on environmental performance in Spanish industry.

Barriers to Industry 4.0 adoption in pharmaceutical manufacturing companies: A case study

Breno Strüssmann, Lars Hvam, Anders Haug — Tue, 24 Feb 2026 15:57:51 +0000

Purpose: This study explores the barriers to adopting Industry 4.0 technologies within the pharmaceutical manufacturing sector. Despite the potential for transformative benefits, the sector has been slow in embracing these technologies due to unique regulatory and operational challenges. This paper seeks to understand these challenges in greater depth by analyzing key obstacles that pharmaceutical companies face during their digital transformation efforts.

Design/methodology/approach: A mixed-methods approach was employed, combining maturity assessments with insights from in-depth interviews with key stakeholders in the pharmaceutical industry. The study identifies and categorizes the main barriers to Industry 4.0 adoption, providing a sector-specific analysis.

Findings: The primary barriers to Industry 4.0 adoption in pharmaceutical manufacturing were found to be "prioritization and strategic alignment," "technological challenges," and "financial constraints." Contrary to common assumptions in the literature, "regulatory and compliance challenges" were perceived as less impactful by stakeholders, as these are often ingrained in routine operations.

Research limitations/implications: The research focuses on a single pharmaceutical manufacturing company, which may limit generalizability. However, as the company operates within the broader pharmaceutical industry as a contract development and manufacturing organization (CDMO), the findings could reflect broader industry dynamics.

Practical implications: Pharmaceutical companies should prioritize overcoming strategic and technological barriers to facilitate Industry 4.0 adoption. Clear leadership direction, strategic alignment, and addressing interoperability challenges are critical for successful digital transformation in the sector.

Originality/value: This study provides a novel contribution by offering a detailed analysis of barriers to Industry 4.0 adoption specific to the pharmaceutical manufacturing sector. It challenges the traditional view of regulatory hurdles as the primary obstacle, emphasizing the increasing integration of regulatory management into daily operations and shifting the focus toward overcoming technological and strategic challenges.

Systematic literature mapping: Integrated system of logistic distribution for island

Eka Suswaini, Mochammad Agung Wibowo, Ferry Jie — Tue, 24 Feb 2026 15:58:23 +0000

Effective management of fuel logistic distribution is essential for ensuring timely supply chain operations and achieving product sustainability. This study employs systematic literature mapping (SLM) to identify gaps in research and potential advancements in Supply Chain Management (SCM) for fuel distribution. Using the Conceptual K-Chart, the study highlights unexplored areas and proposes an integrated information system methodology. It focuses on developing a logistic distribution framework for islands, leveraging memetic and genetic algorithms to address challenges like ship berthing delays caused by unpredictable weather. The proposed Integrated Information System of Fuel Logistic Distribution offers a novel solution to these issues, bridging research gaps and enhancing logistic efficiency. The outcomes of this research are unprecedented, filling the "empty box" in the result layer of the K-Chart, and establishing a groundbreaking approach distinct from prior studies in maritime logistics.

Sustainability initiatives in the Spanish road freight transport companies

Wed, 25 Mar 2026 12:54:54 +0000

Purpose: The objective of this study is to examine the status of implementation of 13 sustainability initiatives that impact road freight performance.

Design/methodology/approach: Through an empirical analysis with information collected from surveys carried out on 368 Spanish road transport companies, the researchers have identified the benchmark sustainability initiatives in Spain. On the one hand, those currently implemented are known, and on the other hand, those planned to be implemented in the future.

Findings: Our research reveals a clear disconnect between initiatives considered crucial in the academic literature, such as fleet modernization and decarbonization goals, and those that are prioritized in practice. This gap highlights the need to realign the approach to management with evidence-based priorities.

Research limitations/implications: Although this study provides valuable information, it is not without limitations, mainly due to its specific scope in Spain. The research opens the doors to potential future research, such as expanding the study sample with European companies. Moreover, in order to analyse the correlation between the implementation of initiatives and social, environmental and economic indicators, it is proposed to expand the study by asking the companies themselves about their use of these TBL indicators.

Practical implications: Supply chain management in road freight transport has acquired strategic importance within the Spanish economy, emerging as a critical factor driving its development. The results of the study suggest areas where specific interventions could bridge the gap between theory and practice. Professionals are encouraged to adopt high impact, widely implemented strategies to improve both environmental performance and operational efficiency.

Originality/value: Companies operating in the sector have prioritized the economic optimization of their operations. However, the growing importance of road transport goes beyond economic concerns, increasingly influencing environmental and social sustainability. This document underlines the critical role of implementing or planning initiatives to improve road freight performance.