Assessing Cause of Defect Using Failure Mode and Effect Analysis
Keywords:
Defect, FMEA, Ishikawa Diagram, QualityAbstract
A company should implement good quality management to maintain consumer confidence in producing quality products. FMEA serves to identify product failures in a process and the causes of defects or losses that occur during the production process of a product, component, or system. The research aims to analyze quality control and identify production defects that cause a decrease in quality. The samples studied were rejected goods in production activities. Forty damaged parts were used as the samples in this study. This study used both qualitative and quantitative analysis. Quantitative analysis was conducted to determine the type of rejection and then to rank the risk, while qualitative analysis was performed with Ishikawa diagram to evaluate risk priorities. This research not only helps identify and assess the root cause of rejected goods but also affects the following year's planning by proposing measures to reduce risk. Check sheets and histograms are used to present further research. The analysis results show two classifications of defects in production: size error and painting error, with the most dominant defect, size error, and equal to 73.17%. Based on the analysis of the causes of defects, several factors were found that caused product defects; man, material, method, machine. The man factor has the highest value in contributing to defect, with an RPN score of 192.
References
Apriyan, J., Setiawan, A., H., S., & W.I., Ervianto. (2017). Analisis Risiko Kecelakaan Kerja Pada Proyek Bangunan Gedung Dengan Metode FMEA. Jurnal Muara Sains, Teknologi, Kedokteran Dan Ilmu Kesehatan, 1(1), 115–123.
Agrawal, M. (2021). Impact of Ishikawa on the analysis of data in mechanical industries. Materials Today: Proceedings, xxxx. https://doi.org/10.1016/j.matpr.2021.04.376.
Besterfield, D. H. (2009). Quality Control. 8th edition. New Jersey: Pearson Prentice Hall.
Carvalho, R., Lobo, M., Oliveira, M., Oliveira, A. R., Lopes, F., Souza, J., Ramalho, A., Viana, J., Alonso, V., Caballero, I., Santos, J. V., & Freitas, A. (2021). Analysis of root causes of problems affecting the quality of hospital administrative data: A systematic review and Ishikawa diagram. International Journal of Medical Informatics, 156(April). https://doi.org/10.1016/j.ijmedinf.2021.104584
Dai, W., Maropoulos, P. G., Cheung, W. M., & Tang, X. (2011). Decision-making in product quality based on failure knowledge. International Journal of Product Lifecycle Management, 5(2–4), 143–163. https://doi.org/10.1504/IJPLM.2011.043185
Grosfeld-Nir, A., Ronen, B., & Kozlovsky, N. (2007). The Pareto managerial principle: when does it apply?. International Journal of Production Research, 45(10), 2317-2325.
Judi, H.M., Jenal, R., Genasan, D. (Ed.) (2011). Quality Control Implementation in Manufacturing Companies: Motivating Factors and Challenges, Applications and Experiences of Quality Control. Edited Prof. Ognyan Ivanov (Ed.), ISBN: 978-953-307-236-4, InTech.
Kardos, P., Lahuta, P., & Hudakova, M. (2021). Risk Assessment Using the FMEA method in the Organization of Running Events. Transportation Research Procedia, 55, 1538–1546. https://doi.org/10.1016/j.trpro.2021.07.143
Khomah, I., & Siti Rahayu, E. (2015). Aplikasi Peta Kendali p sebagai Pengendalian Kualitas Karet di PTPN IX Batujamus/Kerjoarum. AGRARIS: Journal of Agribusiness and Rural Development Research, 1(1), 12–24. https://doi.org/10.18196/agr.113
Liu, H. C., Chen, X. Q., Duan, C. Y., & Wang, Y. M. (2019). Failure mode and effect analysis using multi-criteria decision making methods: A systematic literature review. Computers and Industrial Engineering, 135(April), 881–897. https://doi.org/10.1016/j.cie.2019.06.055
Liu, J., Wang, D., Lin, Q., & Deng, M. (2023). Risk assessment based on FMEA combining DEA and cloud model: A case application in robot-assisted rehabilitation. Expert Systems with Applications, 214(October 2022), 119119. https://doi.org/10.1016/j.eswa.2022.119119
McDermott, R. E., Mikulak, R. 1., & Beauregard, M. R. (2013). THE BASICS OF The Basics of FMEA.
Nguyen, Q. V., Miller, N., Arness, D., Huang, W., Huang, M. L., & Simoff, S. (2020). Evaluation on interactive visualization data with scatterplots. Visual Informatics, 4(4), 1–10. https://doi.org/10.1016/j.visinf.2020.09.004
Perera, H. E., & Navaratne, S. . (2016). Application of Pareto principle and Fishbone diagram for Waste Management in a Powder Filling Process. International Journal of Scientific & Engineering Research, 7(11), 181–184.
Ratnadi, R., & Suprianto, E. (2016). Pengendalian Kualitas Produksi Menggunakan Alat Bantu Statistik (Seven Tools) Dalam Upaya Menekan Tingkat Kerusakan Produk. Jurnal Indept, 6(2), 11.
Shebl, N. A., Franklin, B. D., & Barber, N. (2012). Failure mode and effects analysis outputs: Are they valid? BMC Health Services Research, 12(1). https://doi.org/10.1186/1472-6963-12-150
Wang, H. (2009). Comparison of p control charts for low defective rate. Computational Statistics and Data Analysis, 53(12), 4210–4220. https://doi.org/10.1016/j.csda.2009.05.024
Wang, L., Yan, F., Wang, F., & Li, Z. (2021). FMEA-CM based quantitative risk assessment for process industries—A case study of coal-to-methanol plant in China. Process Safety and Environmental Protection, 149, 299–311. https://doi.org/10.1016/j.psep.2020.10.052
Wawolumaja, Rudy. Rudianto Muis. 2013. Diktat Kuliah Pengendalian & Penjaminan Kualitas (Ie-501) Failure Mode & effect Analysis (FMEA). Universitas Kristen Maranatha. Bandung. Rudy. Wawolumaja. Maranatha.edu
Wong, K.C. (2011). Using an Ishikawa Diagram as A Tool to Assist Memory and Retrieval of Relevant Medical Cases from the Medical Literature. Journal of Medical Reports. 5(120).
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Berty Dwi Rahmawati, Nadia Nisya Budi Maharani
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
.png)
