Improving Productivity and Quality of a Machining Process by Using Lean Six Sigma Approach: A Case Study | ||
| Engineering Research Journal (Shoubra) | ||
| Volume 53, Issue 1, January 2024, Pages 1-16 PDF (1.68 M) | ||
| Document Type: Research articles | ||
| DOI: 10.21608/erjsh.2023.226742.1194 | ||
| Author | ||
| Attia H Gomaa* | ||
| Department of Mechanical Engineering, Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt. | ||
| Abstract | ||
| Lean six sigma (LSS) is a continuous process improvement approach that focuses on improving quality and eliminating waste, which in turn improves customer satisfaction and reduces operation costs. Some important LSS case studies, tools and techniques are discussed, which will be useful to LSS practitioners. In this context, this study focuses on the implementation of LSS in a spare parts company in Egypt. In this study, a generic LSS-DMAIC framework for implementing LSS in manufacturing is developed using various analysis and improvement tools such as brainstorming, process mapping, SIPOC, KPI analysis, OEE analysis, sigma level, seven QC tools, process time analysis, value stream mapping, waste analysis, DOE, Taguchi method, ANOVA, Takt time, standard time, 7S, standard work and cause–effect diagram. Based on the results of the study, suggestions were made to reduce defect rates, improve sigma level, reduce cycle time, increase value-added, reduce non-value-added time, increase labor productivity, and improve overall equipment effectiveness. For example, Total Effective Equipment Performance (TEEP) improved from 58.4% to 67.6%, Overall Equipment Effectiveness (OEE) improved from 64.5% to 75.7%, sigma level improved from 2.36 to 2.68, and process capability improved from 0.38 to 1.01. Finally, the proposed LSS framework can be used by production managers, leaders, and researchers in different production sectors before embarking on a continuous process improvement journey. | ||
| Keywords | ||
| LSS; KAIZEN; DMAIC; Continuous Improvement; Manufacturing | ||
|
Statistics Article View: 820 PDF Download: 1,054 |
||
