Issue |
E3S Web Conf.
Volume 484, 2024
The 4th Faculty of Industrial Technology International Congress: Development of Multidisciplinary Science and Engineering for Enhancing Innovation and Reputation (FoITIC 2023)
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Article Number | 01006 | |
Number of page(s) | 10 | |
Section | Manufacturing, Process, and Business Advancement | |
DOI | https://doi.org/10.1051/e3sconf/202448401006 | |
Published online | 07 February 2024 |
The Recommendations to Improve Quality of Kitchen Set Products Using New Failure Mode and Effect Analysis and Fault Tree Analysis Methods at a Furniture Company in Bandung
Industrial Engineering Department, Faculty of Industrial Technology, Institut Teknologi Nasional Bandung, PHH.Mustofa, No 23, Bandung, Indonesia
* Corresponding author: lauditta.irianti@itenas.ac.id
The company had a problem regarding product quality, especially on kitchen set products. Based on data for the last six months, reveals a consistent surpassing of acceptable limits for product defects every month. This causes negative consequences, encompassing both time and cost setbacks, along with a decline in consumer confidence in the company. Therefore, there was a compelling necessity to enhance the overall quality of the products. Two methodologies, New FMEA and FTA, were used to pursue the objective. A New FMEA was used to indicate which type of defect will be prioritized (using Action Priority (AP)) and a FTA was used to identify the root cause. The process of creating a kitchen set involved 11 steps, with defect occurrences noted in 8 of these steps. Based on AP high criteria, there were 6 failure modes (from 20) that will be singled out for root cause analysis through FTA. Based on the FTA, 14 root causes require attention. The proposed recommendations involved training, material inspection, material protection, periodic maintenance, operational procedures, replacement of measuring tools, and redesign of the workstation environment. Simulations were carried out to compare before and after (if the recommendations are applied) of AP by changing the occurrence and detection values. The simulation showed a decrease in the AP classification from high to moderate, suggesting a positive impact on product quality.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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