Process improvement using six sigma methodology

• 第一著者: Chew, Li Ling
• フォーマット: 学位論文
• 言語: English
• 出版事項: 2009
• 主題: TJ Mechanical engineering and machinery
• オンライン･アクセス: http://eprints.utm.my/id/eprint/123/1/ChewLiLingMFKM2009.pdf; http://eprints.utm.my/id/eprint/123/

The purpose of this thesis is to solve the screw stuck issue of Sensor Module in Agilent Technologies, using Six Sigma methodology D-M-A-I-C. The current yield loss due to this defect had contributed to the increased production cost due to higher material scrap and rework time. Project objectives were set in Define phase to increase the yield of both functionality and reworkability of Sensor Module from current baseline yield to 99.4% (targeted four sigma). The baseline data was collected in the Measure phase and shows that baseline yield for functionality and reworkability was 74% and 62% respectively. Analyze phase results revealed the relationship of vital few causes to the screw stuck issue, which led to the defect s root cause as thread galling. Thread galling phenomena was associated with the fasteners material and torque speed (rpm), therefore the relationship between these factors and the functionality and reworkability yield was developed. In Improve phase, the solution was chosen to replace the fastener s material and reduce the torque speed considering factors such as effectiveness, cost and lead time. Optimization test or DOE was carried out to determine the best options on the fastener s material selection and the torque speed. Experiment reveals improved yield with SP series nut new type, wax coated stainless steel screw, and manual torque driver. Pilot run was conducted successfully with 100% yield on functionality. In final Control phase, all the changes and implementation were institutionalized with proper training, documentation, process monitoring, response plan and sustainability plan. The result from the project has provided an insight on actual successful deployment of Six Sigma methodology DMAIC with application of its various statistical tools and techniques, and as the systematic problem solving framework on solving actual industrial issues.