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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳鴻基 博士(Houn-Gee Chen) | |
| dc.contributor.author | Tair Mukhanov | en |
| dc.contributor.author | 莫卡夫 | zh_TW |
| dc.date.accessioned | 2021-06-15T02:31:36Z | - |
| dc.date.available | 2009-08-20 | |
| dc.date.copyright | 2009-08-20 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-08-14 | |
| dc.identifier.citation | 1. Aberdeen Group. (2006). The Lean Benchmark Report – Closing the Reality
Gap. Boston, MA. 2. Ahmed, A. (2005). Best Manufacturing Scheduling Systems. TEC. 3. Andrey, S. (2006). SIMATIC IT – Tool for MES building. Information Technologies in Industry (Russia). 4. Balle, F. B. (2005). Lean or Sigma? Lean Enterprise Institute . 5. Basu, R. e. (1996). Measuring performance against world class standards. IIE Solutions.=orcross. 6. Bititci, U. S. (1997). Integrated performance measurement systems: an audit and development guide. The TQM Magazine. Bedford. 7. Bozdogan, K. (2004). A comparative review of lean thinking,six sigma and related enterprise change models. MIT,working paper. 8. Carreira, B. (2005). Lean manufacturing that works: powerful tools for dramatically reducing waste and maximizing profits. American Management Association. 9. Claus, A. (2006). Improving Manufacturing Business Operations with Wonderware Production & Performance Management Software Solutions. Free Press. 10. Cross, K. F. (1988). The SMART Way To Define And Sustain Success. =ational Productivity Review. =ew York. 11. Crowther, D. E. (1996). Corporate performance operates in three dimensions. Managerial Auditing Journal. Bradford. 54 12. Cua, K. O. (2001). Relationships between implementation of TQM, JIT,and TPM and manufacturing performance. Journal of Operations Management, 19, 675. 13. David, S. e. (1995). Effective process management through performance measurement Part II - benchmarking total quality-based performance measurement for best practice. Business Process Re-Engineering & Management Journal.1. 87. 14. David, S. e. (1995). Effective process management through performance measurement part I - applications of total quality-based performance measurement. Business Process Re-Engineering & Management Journal. 1. 77. 15. Dumond, E. J. (1994). Making best use of performance measures and information. International Journal of Operations & Production Management,14, 16. 16. Eccles, R. G. (1991). The Performance Measurement Manifesto. Harvard Business Review. 17. Folan, P. e. (2005). A review of performance measurement:Towards performance management. Computers in Industry. 56, 663. 18. Frolov, E. (2005). MES systems, top-down approach. ERP=EWS (Russia) . 19. Ganesh, W. (2008). Lean Manufacturing Strategic Guidebook. MESA International . 20. Georg, N. K. (2005). Kanban-controlled manufacturing systems. Springer. 21. Ghalayini, A. M. (1997). An integrated dynamic performance measurement system for improving manufacturing competitiveness. International Journal of Production Economics, 48, 207-225. 22. Gordienko, E. (2003). MES - Old dreams, new realities. CIO Journal,7. 55 23. Ha, S. (2007). Continuous Processes Can Be Lean. Manufacturing Engineering . 24. Hauser, J. e. (2002). Metrics: You Are What You Measure! Elsevier 16, 516. 25. Higgins, L. e. (2004). Measurement in the 21st Century. APQC. 26. HighJump Software. (2008). Four Vital Reasons Manufacturing Execution Systems are Essential to Lean Enterprise Initiatives. . Eden Prairie, MN. 27. Ittner, C. D. (2003). Coming up short on nonfinancial performance measurement. Harvard Business Review. 28. James E. deMin. (2007). The journey to lean. BT Global Services , 4-7. 29. Jeong, K.-Y. e. (2001). Operational efficiency and effectiveness measurement. 21, 1404. 30. Johnston, R. e. (2002). 'Good enough' performance measurement: A tradeoff between activity and action. The Journal of the Operational Research Society, 53, 256-262. 31. Julie, F. (2008). Improving Order Execution Performance: A Holistic View of Metrics Across Plant & Warehouse. MESA International , 6-15. 32. Julie, F. (1997). MES Explained: High Level Vision. MESA International . 33. Julie, F. (2004). MESA's Next Generation Collaborative MES Model. MESA International , 11-18. 34. Kaplan, R. S. (1992). The Balanced Scorecard - Measures That Drive Performance. Harvard Business Review. 35. Kennerley, M. e. (2003). Measuring performance in a changing business environment. International Journal of Operations & Production Management,23, 213-229. 36. Koufteros, X. A. (1998). Developing measures of time-based manufacturing. Journal of Operations Management, 16, 21. 56 37. Kutsevich N. (2003). The journey from SCADA-systems to SCADA-solutions and MES-components. Computer Automation Journal, 4. 38. Lockamy Iii, A. e. (1995). An empirical study of division and plant performance measurement systems in selected world class manufacturing firms: linkages for competitive advantage. International Journal of Production Research, 33, 221. 39. LogicaCMG. (2004). MES Selection: Best Practices. MESA International , 4-8. 40. Maskell, B. H. (2004). Practical lean accounting: a proven system for measuring and managing the lean enterprise. Productivity Press. 41. Mclachlin, R. (1997). Management initiatives and just-in-time manufacturing. Journal of Operations Management, 15, 271. 42. Melnyk, S. A. (2004). Metrics and performance measurement in operations management: dealing with the metrics maze. . Journal of Operations Management, 22, 209-217. 43. Nave, D. (2002). How To Compare Six Sigma, Lean and the Theory of Constraints. American Society for Quality , 73-78. 44. Neely, A. e. (1997). Designing performance measures: a structured approach. 17, 1131. 45. Neely, A. e. (2001). The performance prism perspective. Cost Management. Boston. 46. Paul, M. (2008). Extending PLM to the Shop Floor. Free Press. 47. Pavnaskar, S. J. (2003). Classification scheme for lean manufacturing tools. International Journal of Production Research, 41, 3075. 48. Phillips, T. (2000). Lean manufacturing: building the lean machine. Free Press. 49. Porter, M. E. (1998). Competitive Advantage: Creating and Sustaining Superior Advantage. =ew York: The Free Press . 57 50. Ranjana, M. (2008). Planning and Implementation of a Manufacturing Execution System (MES) in a Steel Plant. MESA International . 51. Santos, S. P. (2002). Adding value to performance measurement by using system dynamics and multicriteria analysis. 22, 1246-1272. 52. SAP. (2005). Adaptive Manufacturing: Enabling the Lean Six Sigma Enterprise. The Free Press. 53. SAP. (2007). In Pursuit of The Perfect Plant. Free press. 54. Shah, R. e. (2003). Lean manufacturing: context, practice bundles, and performance. Journal of Operations Management, 21, 129. 55. SIEMENS. (2007). MES pocket guide. SIEME=S MES Solutions . 56. Sinclair, D. e. (2000). Performance measurement: a critical analysis of the literature with respect to total quality. International Journal of Management Reviews 2, 145. 57. Sink, D. S. (1989). Planning and measurement in your organization of the future. =orcross, Ga., Industrial Engineering and Management Press. 58. Toni, A. D. (1994). Lean organization, management by process and performance measurement. International Journal of Operations & Production Management , 221-236. 59. Womack, J. P. (1996). Lean thinking: banish waste and create wealth in your corporation. Simon & Schuster. 60. Yves, C. (2007). ISA-95-Based Operations and KPI Metrics Assessment and Analysis. MESA International . 61. Zagidullin, R. (2007). MES systems in Mechanical Engineering. STI=, 11 , 2-5. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/43884 | - |
| dc.description.abstract | As industrialized nations compete more often against the low manufacturing costs of developing countries, manufacturing businesses are implementing Manufacturing Execution Systems (MES) to increase productivity, improve quality and reduce downtime. MES solutions can greatly enhance the results obtained by today’s continuous improvement strategies like Six Sigma, Lean, and Total Quality Management. These improvement strategies all require the ability to gather timely and accurate measurements of a process in order to create improvement initiatives.
The research contained in this thesis explores the most effective practices for strategic improvement applied today in continuous-process manufacturing. The two most popular strategy initiatives today; Lean and Total Quality Management, originated from Toyota and Motorola, respectively. These companies are discrete-process manufacturers therefore, the evolution and development of the two methodologies has focused mostly on improvement in discrete-process manufacturing. Due to the fact that much less development work has been done concerning the implementation of Lean and Total Quality Management initiatives in continuous-process manufacturing, this thesis explores this area. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T02:31:36Z (GMT). No. of bitstreams: 1 ntu-98-R96749037-1.pdf: 2561193 bytes, checksum: 7acf4462ba9f575fbcf0251837dea140 (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | Abstract iii
Contents iv List of Figures and Tables vi CHAPTER ONE: INTRODUCTION 1 1. Introduction 1 CHAPTER TWO: LITERATURE REVIEW 3 2.1. Strategic initiatives 3 2.1.1. Lean Manufacturing 3 2.1.2. Quality and regulatory compliance 12 2.1.3. Real Time Enterprise 15 2.2. Manufacturing metrics 18 2.2.1 Objectives 18 2.2.2. Financial Metrics 19 2.2.3. Operational Metrics 20 2.2.4. Metrics Framework 21 2.3. MES functions 27 CHAPTER THREE: RESEARCH METHODS 29 1. Purpose of research 29 2. Research procedure 30 3. The Sampling 30 4. Questionnaire design 31 CHAPTER FOUR: RESEARCH RESULTS 33 1. Lean Manufacturing 34 2. Total Quality Management 38 3. Real-Time Enterprise 42 CHAPTER FIVE: CONCLUSION 48 1. Success factors 48 2. MES solutions today 49 3. Implementation 51 References 53 Appendix 1. 58 | |
| dc.language.iso | en | |
| dc.subject | MES 導入的成功因素(以貴金屬製造產業為例) | zh_TW |
| dc.subject | Continuous and Discrete process industry | en |
| dc.subject | Real-Time Enterprise | en |
| dc.subject | Lean Manufacturing | en |
| dc.subject | Manufacturing Execution Systems | en |
| dc.subject | Operational and Financial Metrics | en |
| dc.title | MES 導入的成功因素(以貴金屬製造產業為例) | zh_TW |
| dc.title | Success Factors for MES Implementation in the Rare Metals Production Industry | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 97-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 許瑋元(Carol Hsu),(Michael J. Shaw) | |
| dc.subject.keyword | MES 導入的成功因素(以貴金屬製造產業為例), | zh_TW |
| dc.subject.keyword | Manufacturing Execution Systems,Lean Manufacturing,Real-Time Enterprise,Operational and Financial Metrics,Continuous and Discrete process industry, | en |
| dc.relation.page | 65 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2009-08-17 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 企業管理碩士專班 | zh_TW |
| 顯示於系所單位： | 管理學院企業管理專班(Global MBA) | |
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