| URN | etd-0113111-114516 | Statistics | This thesis had been viewed 1282 times. Download 0 times. |
| Author | PO-YU Chen | ||
| Author's Email Address | No Public. | ||
| Department | Institute of Industrial Management | ||
| Year | 2010 | Semester | 1 |
| Degree | Master | Type of Document | Master's Thesis |
| Language | zh-TW.Big5 Chinese | Page Count | 69 |
| Title | The Improvement of Defective Rate by Using Six Sigma Techniques - A Case Study for a Shock Absorber Manufacturing factory | ||
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| Abstract | ˇ@ˇ@Recently, due to financial tsunami and high oil price the people who want to buy new cars didnˇ¦t take action.ˇ@But these economic factors make the auto parts industry flourishing.ˇ@According to the latest statistical report issued by Taiwan auto trade union we know the value of Taiwan auto parts industry output is 216.2 billions in 2005 and the value of output has exceeded the whole automobilesˇ¦ since 2006.ˇ@Then it only accounts for 70% of the auto parts industry in 2009.ˇ@As the orders increase the auto parts industry starts to rise in the capacity.ˇ@Considering modern people pay attention to the security and efficiency of a car, the auto parts industry makes efforts in satisfying the customersˇ¦ needs by producing small amount of diverse products.ˇ@Todayˇ¦s competitive environment leaves no room for error.ˇ@Improving the manufacturing processes quality and cutting the cost have become the most important factors to survive.ˇ@The latest research report shows that there will be a great benefit by adopting the Six Sigma approach, so Six Sigma is used widely.ˇ@Six Sigma benefits are improving industrial competitiveness, increase the profit, manufacturing processes, expanding market share, satisfying customer requirements, and saving time and cost. ˇ@ˇ@The object of this study is a plant producing mounts.ˇ@We analyze the process of cementing pipe support by using the method of Six Sigma (DAMIC) and PFMEA.ˇ@It explains the reasons why the potential defects occur, the factors effecting the manufacturing processes, and finds out the best combination of process parameters to improve manufacturing processes by using fuzzy theory and Taguchi method.ˇ@Then we confirm the manufacturing processes to meet our goal and the effect of improvement better than the target we set. |
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| Files | indicate not accessible | ||
| Date of Defense | 2010-12-31 | Date of Submission | 2011-01-13 |