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In this thesis, the failure mode and effects analysis (FMEA) method is used as a tool to reduce the error rate for any potential failures arising from the DIGIFAB process. DIGIFAB process focuses on fabric processing and making doll clothes. The amount of fabric scrap produced in 2019 was very high at around 30,320 Pcs and the company's losses reached $ 23,810,100. The purpose of this thesis is to assess whether the application of FMEA can significantly reduce the level of danger in each failure mode that occurs in the DIGIFAB process.
This research methodology begins by identifying the categories of failure modes, causes, and effects. A total of 12 failure modes were identified in 3 sub-processes in the DIGIFAB process. The 5 highest priorities are obtained after calculating the scale value of the Severity, Occurrence and Detection to get the RPN value. Corrective action was taken to reduce the RPN value, especially for high priority risks. After developing and implementing improvements, calculations were made for the new RPN value and the results were significantly reduced. The average monthly scrap loss decreased 59% from 1,110 pcs to 459 pcs in October 2020, and in November 2020 it also decreased by 89% from 1,689 pcs to 179 pcs compared to the same month in 2019. The decrease in average monthly scrap has a major impact on the company's cost-saving. The losses average monthly cost of the company decreased 78% from $ 1,149,272 to $ 255,533, so the company cost-saving around $ 893,739 in October 2020, and in November 2020 the losses average monthly cost of the company decrease 47% cost, from $ 853,810 to $ 451,412 so the company cost-saving around $ 402,398. FMEA method can effectively reduce the risk of potential failure modes occurring in the DIGIFAB process and can improve the quality of fabrics. |
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