A system study on the fabric manufacturing operations of Sun Fortune Inc.
A systems study was conducted on Sun Fortune Incorporated (SFI), a company that manufactures rolls of fabrics. The study focuses on the manufacturing area of the company particularly in the knitting are where yarns are turned into fabric rolls with a study period of January 2014 to December 2016. Wi...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
| Published: |
Animo Repository
2018
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/etd_bachelors/8260 |
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| Institution: | De La Salle University |
| Language: | English |
| Summary: | A systems study was conducted on Sun Fortune Incorporated (SFI), a company that manufactures rolls of fabrics. The study focuses on the manufacturing area of the company particularly in the knitting are where yarns are turned into fabric rolls with a study period of January 2014 to December 2016. With the objectives of the company, the company was evaluated through the application of a SWOT analysis. Furthermore, a EOTH-SURG analysis was performed which revealed the greatest problem of SFI which is the average deviation of 226 defected fabric rolls per month for the years 2014 to 2016 that are rejected in the knitting inspection incurring a discount cost of Php1,462,248 annually.
With the problem, a cause analysis approach was conducted as well as the necessary validations and solutions were proposed. The causes that contribute to the problem were either the high ratio of knitting machines to the operators or the ineffective method of capturing the particles in the air. The former had a setup of at most 10 machines to 1 worker while the latter was the amount of cotton fiber in the air, causing the break yarn and needle line defects at 32.3% and 27.42% respectively. The solutions were evaluated through the Kepner Tregoe decision analysis in order to determine the final solutions, which is to both install sensors on the machine and monitoring board, as well as to install fans on the machine. From this, the final solutions that tackle each cause were combined to further determine a decrease in the number of defects. The effectivity and improvement that the proposal could bring was supported using a simulation model from Monte Carlo. Results of the simulation show that with the proposed system, the solution showed a 57.56% decrease in the defective rolls of the company per month, showing the company will not exceed their tolerable amount of selected fabrics. Moreover, the expected net present value of the solution is estimated to be around Php882,829.13 with a payback period of 8 months. |
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