Analysis of manufacturing system performance using performance characteristic curve
This project evaluates an underperforming manufacturing system and analyses its performance based on the characteristic curve (Work In Progress Vs. Throughput). It also covers an in-depth analysis, identify the limits and evaluates on the key performance indicators of the manufacturing system. Throu...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2018
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| Online Access: | http://hdl.handle.net/10356/74796 |
| _version_ | 1811686074303381504 |
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| author | Lee, Eric Sing Loong |
| author2 | Sivakumar A. I. |
| author_facet | Sivakumar A. I. Lee, Eric Sing Loong |
| author_sort | Lee, Eric Sing Loong |
| collection | NTU |
| description | This project evaluates an underperforming manufacturing system and analyses its performance based on the characteristic curve (Work In Progress Vs. Throughput). It also covers an in-depth analysis, identify the limits and evaluates on the key performance indicators of the manufacturing system. Through the evaluation, it is shown that the manufacturing system is slightly underperforming and requires further improvements to aid in ideal optimization. With a clear understanding of where the operating point of the manufacturing system lies on the characteristic curve, analysis can be done on several input variables to help improve the system through identification of how these variables affect the key performance indicators of the system and where its limits lie. After analysis and modelling, results showed improvement when lot size is reduced but brings about no actual contribution in terms of actual improvement for the manufacturing system. As an actual improvement for throughput is measured in terms of the number of wafers that are produced but instead result in a beneficial reduction in cycle time; an increment in bottleneck workstations results in an upward shift in the characteristic curve along with the operating point causing the manufacturing system to be in an endless chase toward the good region of the characteristic curve. But the problem is solved when both methods are combined, even though the operating point does not shift into the good region, but it does show significant improvement to the system. |
| first_indexed | 2024-10-01T04:54:38Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/74796 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:54:38Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | ntu-10356/747962023-03-04T18:21:56Z Analysis of manufacturing system performance using performance characteristic curve Lee, Eric Sing Loong Sivakumar A. I. School of Mechanical and Aerospace Engineering DRNTU::Engineering This project evaluates an underperforming manufacturing system and analyses its performance based on the characteristic curve (Work In Progress Vs. Throughput). It also covers an in-depth analysis, identify the limits and evaluates on the key performance indicators of the manufacturing system. Through the evaluation, it is shown that the manufacturing system is slightly underperforming and requires further improvements to aid in ideal optimization. With a clear understanding of where the operating point of the manufacturing system lies on the characteristic curve, analysis can be done on several input variables to help improve the system through identification of how these variables affect the key performance indicators of the system and where its limits lie. After analysis and modelling, results showed improvement when lot size is reduced but brings about no actual contribution in terms of actual improvement for the manufacturing system. As an actual improvement for throughput is measured in terms of the number of wafers that are produced but instead result in a beneficial reduction in cycle time; an increment in bottleneck workstations results in an upward shift in the characteristic curve along with the operating point causing the manufacturing system to be in an endless chase toward the good region of the characteristic curve. But the problem is solved when both methods are combined, even though the operating point does not shift into the good region, but it does show significant improvement to the system. Bachelor of Engineering (Mechanical Engineering) 2018-05-24T02:54:20Z 2018-05-24T02:54:20Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/74796 en Nanyang Technological University 62 p. application/pdf |
| spellingShingle | DRNTU::Engineering Lee, Eric Sing Loong Analysis of manufacturing system performance using performance characteristic curve |
| title | Analysis of manufacturing system performance using performance characteristic curve |
| title_full | Analysis of manufacturing system performance using performance characteristic curve |
| title_fullStr | Analysis of manufacturing system performance using performance characteristic curve |
| title_full_unstemmed | Analysis of manufacturing system performance using performance characteristic curve |
| title_short | Analysis of manufacturing system performance using performance characteristic curve |
| title_sort | analysis of manufacturing system performance using performance characteristic curve |
| topic | DRNTU::Engineering |
| url | http://hdl.handle.net/10356/74796 |
| work_keys_str_mv | AT leeericsingloong analysisofmanufacturingsystemperformanceusingperformancecharacteristiccurve |