Supply chain management
Ramin Pabarja; Gholamreza Jamali; Khodakaram Salimifard; Ahmad Ghorbanpur
Abstract
The Lean, Agile, Resilience, and Green (LARG) supply chains are more competitive than conventional ones. Evaluating its performance under current conditions and developing suitable strategies is crucial to enhance LARG. This study aims to create an assessment model for LARG in Iran's hospital medical ...
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The Lean, Agile, Resilience, and Green (LARG) supply chains are more competitive than conventional ones. Evaluating its performance under current conditions and developing suitable strategies is crucial to enhance LARG. This study aims to create an assessment model for LARG in Iran's hospital medical equipment supply chain, especially in Hamadan. The Fuzzy Inference System (FIS) evaluates LARG across four dimensions: lean, agile, resilient, and green. Key indicators obtained from a comprehensive review of the literature and other published reports in the field of LARG were also confirmed by a focused group of experts in the medical equipment supply chain field. The findings indicate that the value LARG of the medical equipment supply chain is 0.787. Key indicators for the evaluation of LARG in the hospital medical equipment supply chain include reducing overall supply chain costs, optimizing inventory management, shortening supply chain development cycle time, increasing the introduction of new products, promoting information sharing among supply chain members, establishing flexible supply bases and sourcing, reducing fossil fuel consumption, and implementing waste management practices such as reuse and recycling of recyclable materials. This research provides managers with valuable insights into the current state of LARG and serves as a reference for formulating LARG strategies and practices. The study's results enable supply chain actors, particularly in Iran's Hamadan Province, to comprehend the key indicators for improving LARG performance in the hospital medical equipment supply chain. The proposed model can be adapted to other industries and service sectors by adjusting the indicators and assessing data availability.
Total quality management and quality engineering
Md. Limonur Rahman Lingkon; Pronab Krishna Saha; Abdulla Al Manzid; Md. Nazmul Hasan; Showra Kishore Mahalanobish
Abstract
The purpose of this study is to determine how the Bangladeshi garment industry's sewing defect reduction and productivity enhancement are affected by the Plan, Do, Check, Act (PDCA) and 5S (Sort, Set in order, Shine, Standardize, Sustain) techniques. One of the main reasons for production delays and ...
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The purpose of this study is to determine how the Bangladeshi garment industry's sewing defect reduction and productivity enhancement are affected by the Plan, Do, Check, Act (PDCA) and 5S (Sort, Set in order, Shine, Standardize, Sustain) techniques. One of the main reasons for production delays and increased costs is sewing defects. By reducing defects, improving Overall Equipment Effectiveness (OEE), and methodically using integrated PDCA concepts, the study aims to streamline and expand the production flowline while increasing throughput. To continuously evaluate and improve the sewing process, the 5S method is also employed. Tools like cause-effect diagrams and Pareto charts were used to identify the defect correctly. The OEE was used to evaluate the actual efficiency. The integration of 5S and PDCA as a lean methodology was utilized to minimize the defect rate and maximize quality to improve efficiency. For this purpose, data was collected from some renowned factories in Bangladesh. This mixed-integrated methodology is used in the study to integrate quantitative defect analysis with worker satisfaction along with efficiency surveys. The findings should offer valuable insights to the RMG industry in Bangladesh, as producers seek sustainable methods to increase productivity and enhance product quality while mitigating the impact of sewing errors on their production procedures. OEE was increased by almost 3-4% through this research.
