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 Bangladeshi garment industry’s sewing defect reduction and productivity enhancement are affected by the PDCA (Plan, Do, Check, Act) 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 Bangladeshi garment industry’s sewing defect reduction and productivity enhancement are affected by the PDCA (Plan, Do, Check, Act) and 5S (Sort, Set in order, Shine, Standardize, Sustain) techniques. One of the main reasons for production delays and increased costs are sewing defects. By reducing defects, improving Overall Equipment Efficiency (OEE) and methodically using integrated PDCA concepts, the study aims to streamline and expand the production flowline while also increasing throughput. To continuously evaluate and improve the sewing process, the 5S method is also employed. For the proper identification of the defect some tools like cause effect diagram, pareto chart was used. The OEE was used to evaluate the actual efficiency of it. Basically, the integration of 5S and PDCA as Lean Methodology was utilized to minimise the rate of defect and maximize the quality to improve the efficiency as well. For this purpose, data was collected from some renowned factory of Bangladesh. This mixed-integrated methodology is used in the study to integrate quantitative defect analysis with worker satisfaction along with efficiency surveys. The findings ought to 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 overall production procedures. OEE was increased by almost 3-4% through this research.
Scheduling
N. MD. Sarfaraj; Md. L. R. Lingkon; N. Zahan
Abstract
The continuous growth of the population causes an increased demand for our healthcare services. Insufficient hospitals face challenges to serve the patient within a preferable duration. Long lines in front of counters increase the processing time of a patient. From the entry to the completion, plenty ...
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The continuous growth of the population causes an increased demand for our healthcare services. Insufficient hospitals face challenges to serve the patient within a preferable duration. Long lines in front of counters increase the processing time of a patient. From the entry to the completion, plenty of time waste just for unscheduled hospital management system. Job shop scheduling is an optimization process in which jobs are assigned with maintain a particular sequence. In this paper, we proposed flexible job shop scheduling to solve this type of problem by considering patients as job and test counter as machine for the optimization of the processing time and increase the efficiency of a hospital or a clinic. Genetic Algorithm was used to analyze the processing time for multiple counter of a hospital for a stable and effective scheduling. The results showed that an optimized makespan was generated and patients could fulfill their needs much quickly after applying flexible job shop scheduling.
