Brazilian Journal of Operations & Production Management

A reactive hybrid product-driven system for rescheduling in a manufacturing planning

2025-04-21T13:41:53-03:00

Goal: This research aims to develop a novel scheduling model integrating the intelligent product paradigm of a product-driven system (PDS) with the shifting bottleneck heuristic (SBH) to enhance rescheduling efficiency and adaptability in dynamic job shop scheduling problems with disruptions (JSSP-D).

Design / Methodology / Approach: The model employs agent-based modeling, where products act as autonomous agents in rescheduling decisions. Simulations covered 151 scenarios across 14 benchmark instances of machine failures, with production time increases of 100%, 200%, and 300%. The model’s performance was evaluated on its ability to minimize makespan deterioration and maintain efficiency under different disturbance levels.

Results: The PDS-SBH model effectively reduced production efficiency gaps, achieving an average makespan reduction of 7.81%, with peaks of 36.06%. Higher disturbance levels allowed for better rescheduling outcomes, albeit with increased variability. The model’s adaptability provided solutions comparable or superior to stable scheduling benchmarks.

Limitations of the investigation: The study used 14 benchmark instances and focused solely on machine failures, limiting generalizability to other disruptions like resource shortages or order changes. Despite these constraints, the 151 scenarios and rigorous analysis strengthen result reliability.

Practical implications: The PDS-SBH model offers a robust approach for real-time schedule adjustments, maintaining operational continuity, and optimizing resource use. It provides practical insights for decision support systems and policy development in dynamic manufacturing.

Originality / Value: This study pioneers a hybrid approach combining intelligent product paradigms with SBH. It advances JSSP-D research by presenting a resilient, adaptive framework for dynamic scheduling, significantly contributing to manufacturing efficiency and robustness.

The role of digital supply chain practices in enhancing firm performance

2025-03-21T17:47:50-03:00

Purpose: This study examines the impact of digital supply chain practices (DSCP) on firm performance (FP) in the context of Bangladesh's manufacturing sector, with a focus on supply chain responsiveness (SCR) and customer development (CD) as mediating factors.

Design/methodology/approach: A quantitative research design was employed, utilizing partial least squares structural equation modeling (PLS-SEM) to analyze survey data collected from 438 participants representing manufacturing firms in Bangladesh. The model evaluates the direct effects of DSCP on FP, as well as the mediating roles of SCR and CD.

Findings: Results indicate that DSCP positively and significantly impacts FP, with SCR and CD serving as effective mediators in this relationship. The study demonstrates that digital integration in supply chains enhances responsiveness and customer engagement, ultimately leading to improved organizational performance.

Through increased operational efficiency, streamlined logistics, and improved decision-making, the results show that Digital Supply Chain Practices (DSCP) are essential for boosting company performance. By empowering businesses to quickly adjust to market needs, minimize interruptions, and maximize resource usage, DSCP improves supply chain responsiveness and, in the end, increases agility and competitive advantage. Additionally, by enhancing engagement, trust, and service quality, DSCP improves customer development, which supports long-term business success and sustainability in Bangladesh's manufacturing industry.

Research limitations/implications: The study is limited by its focus on the manufacturing sector in Bangladesh, which may affect the generalizability of findings to other industries or regions. Future studies should examine additional variables, such as organizational culture and market conditions, that may influence DSCP's effectiveness.

Practical implications: The findings provide actionable insights for managers seeking to enhance performance through digital supply chain integration. Investing in digital tools can improve responsiveness and customer satisfaction, driving organizational success in competitive markets.

Social implications: This study underscores the potential of digital transformation to improve supply chain efficiency, fostering economic growth and sustainability in emerging economies like Bangladesh.

Originality/value: This research contributes to the limited literature on digital supply chains in developing economies, offering empirical evidence of their role in improving firm performance.

A DEMATEL-based analysis of logistics determinants in online retail

2025-05-07T11:56:07-03:00

Goal: The objective of this study is to perform the analysis of the logistical determinants for the purchase of a product online through the DEMATEL methodology.
Design/methodology/approach: The factors that drive a customer to make a purchase online have become competitive and make it so that the customer can quickly compare online sales platforms and then select the one that is most attractive to them. This study sought through the DEMATEL methodology to identify with experts in the area, factors that lead a customer to make a purchase decision in an online retail in the logistics context.
Results: The results show that the experience that the retailer delivers to the customer in the delivery logistics process is totally directed with the purchase decision and that this is a focus factor of the specialists in the decision-making process.
Research limitations: Some data on logistics factors, customer preferences, or purchasing behavior may compromise the accuracy and reliability of the analysis results. Practical implications: Understanding the factors, businesses can optimize their supply chain processes to meet customer demands efficiently, reducing lead times, stockouts, and delivery delays. This may involve renegotiating contracts with shipping providers, investing in warehouse automation technology, or optimizing transportation routes to reduce costs and improve overall operational efficiency.
Originality/value: Few studies have applied DEMATEL to logistics issues, especially in the context of online retail. This article seeks to point out indicators for decision-making that are rarely studied in the literature and that serve as a new way of helping managers make decisions.

Enhancing inventory accuracy in dairy industries

2025-05-07T11:47:16-03:00

Goal: The goal is to analyze the application of Lean Six Sigma and DMAIC in the inventory management of a dairy industry, aiming to optimize inventory accuracy, reduce picking errors, and enhance OTIF performance, thereby improving overall operational efficiency.

Design / Methodology / Approach: This applied and descriptive research adopts an action research strategy, with researchers actively participating in the project's execution. Lean Six Sigma principles and the DMAIC framework were systematically applied to inventory, picking, and supply processes. Statistical validation was conducted using the Z-test for two proportions to confirm the effectiveness of the improvements implemented.

Limitations of the investigation: The study focuses on a case analysis in a dairy processing environment; however, the structured methodology adopted allows replication in industries characterized by operational complexity, perishability, or high inventory turnover.

Practical implications: The study offers valuable insights for logistics, procurement, and operations professionals. The implemented methodologies led to a 36.63% reduction in inventory discrepancies, resulting in cost savings of R$124,540.56. Additionally, significant improvements were achieved in controlling picking errors and enhancing OTIF performance, underscoring the critical role of structured continuous improvement methodologies in inventory management.

Originality / Value: This research addresses a gap in applied studies on inventory management in the dairy sector, demonstrating the successful application of Lean Six Sigma and DMAIC to achieve substantial operational improvements. The study presents a replicable model for other industries seeking to optimize inventory control, minimize operational errors, and elevate supply chain performance.