Improvement of quality performance in SME's manufacturing industries using statistical process control (SPC)
This project presented information on Statistical Process Control (SPC) control chart on quality improvement tools in automotive industries.By the recent knowledge,control chart is using the statistical approach to detect the occurrence of assignable causes so that necessary corrective action can b...
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| Format: | Undergraduates Project Papers |
| Language: | English |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/3750/1/LAU_SIEW_TIEN.PDF |
| _version_ | 1796989735157104640 |
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| author | Siew Tien, Lau |
| author_facet | Siew Tien, Lau |
| author_sort | Siew Tien, Lau |
| collection | UMP |
| description | This project presented information on Statistical Process Control (SPC) control chart on quality improvement tools in automotive industries.By the recent knowledge,control
chart is using the statistical approach to detect the occurrence of assignable causes so that necessary corrective action can be taken before a large quality of the reject product is manufactured which will negatively impacts quality and customer perception.Improvement in Quality Performance in SMEs Manufacturing Industries using
Statistical Process Control(SPC),Burnmark Industries (M) SdnBhd(Burnmark) has been selected to be improved. The objective of this project is improving the quality
performance of product and process using the SPC control chart in the Burnmark.This project focuses on applying the graphical method to improve the quality performance in
this company.The project is started by selecting the product which is Bracket IP CTR Mounting from Quality Control department in Burnmark,continued by data collection
for data analysis and proceeds to applying Minitab 16 for analysis step. From the result,creating X chart and R charts can clearly monitoring and controlling all the process in producing Bracket IP CTR mounting by reduce the dimensional range from 1.0 to 0.6 and the causes of the problem can be easily identify by monitoring the pattern of control chart and it bring the tolerances of dimension for Bracket IP CTR more close to center limit. As the conclusion, by creating the X chart and R chart,the performance of the product can be clearly identified by taking control of upper control limit and lower control limit.Corrective action can be taken instantly if the data beyond the upper and lower control limit. |
| first_indexed | 2024-03-06T11:41:30Z |
| format | Undergraduates Project Papers |
| id | UMPir3750 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T11:41:30Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | UMPir37502021-07-08T04:24:46Z http://umpir.ump.edu.my/id/eprint/3750/ Improvement of quality performance in SME's manufacturing industries using statistical process control (SPC) Siew Tien, Lau TS Manufactures This project presented information on Statistical Process Control (SPC) control chart on quality improvement tools in automotive industries.By the recent knowledge,control chart is using the statistical approach to detect the occurrence of assignable causes so that necessary corrective action can be taken before a large quality of the reject product is manufactured which will negatively impacts quality and customer perception.Improvement in Quality Performance in SMEs Manufacturing Industries using Statistical Process Control(SPC),Burnmark Industries (M) SdnBhd(Burnmark) has been selected to be improved. The objective of this project is improving the quality performance of product and process using the SPC control chart in the Burnmark.This project focuses on applying the graphical method to improve the quality performance in this company.The project is started by selecting the product which is Bracket IP CTR Mounting from Quality Control department in Burnmark,continued by data collection for data analysis and proceeds to applying Minitab 16 for analysis step. From the result,creating X chart and R charts can clearly monitoring and controlling all the process in producing Bracket IP CTR mounting by reduce the dimensional range from 1.0 to 0.6 and the causes of the problem can be easily identify by monitoring the pattern of control chart and it bring the tolerances of dimension for Bracket IP CTR more close to center limit. As the conclusion, by creating the X chart and R chart,the performance of the product can be clearly identified by taking control of upper control limit and lower control limit.Corrective action can be taken instantly if the data beyond the upper and lower control limit. 2012-06 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/3750/1/LAU_SIEW_TIEN.PDF Siew Tien, Lau (2012) Improvement of quality performance in SME's manufacturing industries using statistical process control (SPC). Faculty of Manufacturing Engineering, Universiti Malaysia Pahang. |
| spellingShingle | TS Manufactures Siew Tien, Lau Improvement of quality performance in SME's manufacturing industries using statistical process control (SPC) |
| title | Improvement of quality performance in SME's manufacturing industries using statistical process control (SPC) |
| title_full | Improvement of quality performance in SME's manufacturing industries using statistical process control (SPC) |
| title_fullStr | Improvement of quality performance in SME's manufacturing industries using statistical process control (SPC) |
| title_full_unstemmed | Improvement of quality performance in SME's manufacturing industries using statistical process control (SPC) |
| title_short | Improvement of quality performance in SME's manufacturing industries using statistical process control (SPC) |
| title_sort | improvement of quality performance in sme s manufacturing industries using statistical process control spc |
| topic | TS Manufactures |
| url | http://umpir.ump.edu.my/id/eprint/3750/1/LAU_SIEW_TIEN.PDF |
| work_keys_str_mv | AT siewtienlau improvementofqualityperformanceinsmesmanufacturingindustriesusingstatisticalprocesscontrolspc |