QUALITY CONTROL PRODUCT WITH USING THE FAILURE MODE AND EFFECT ANALYSIS (FMEA) METHOD AND FAULT TREE ANALYSIS (FTA) AT PT. AGUNG STEEL MAKMUR SIDOARJO (Case Study: Handle Grandstone Iron)

Rony Prabowo, Mochamad Bagus Setiyawan, Rusman Rusman

Abstract


The era of the industrial revolution 4.0 now makes all business people want to be ahead of the competition by providing high-quality products. Control quality is crucial to do because it will positively impact the company both on production and income. Quality control is a combined activity between engineering and management to measure products with characteristics then compare and take corrective action if there is a difference between the product and the quality standard [1]. Quality control uses techniques and activities to achieve, maintain, and improve a product or service quality. In other words, quality control is an effort to maintain and improve the quality of the products produced to confirm product specifications that have been determined based on the company leadership policy [2].

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References


D. Pavletic, M. Sokovic, and G. Paliska. (2018). Practical Application of Quality Tools. International Journal Quality Research, vol. 2, no. 3, pp. 199–205.

K. Banker. (2014). Implementation of Statistical Quality Control (SQC) in Welded Stainless Steel Pipe Manufacturing Industry. International Journal Research Engineering of Technology, vol. 03, no. 09, pp. 270–273.

M. Sokovi?, J. Jovanovi?, Z. Krivokapi?, and A. Vujovi?. (2009). Basic quality tools in the continuous improvement process. Journal Mechanical Engineering, vol. 55, no. 5, pp. 1–9.

R. D. Banker, I. Khosla, and K. K. Sinha. (2008). Quality and competition. Management Science, vol. 44, no. 9, pp. 1179–1192.

Qiu, P. Introduction to statistical process control. 2013. Chapman and Hall. USA.

V. M. Magar and V. B. Shinde. Application of 7 quality control (7 QC) tools for continuous improvement of manufacturing processes. (2014). International Journal of Engineering Research Generation Science, vol. 2, no. 4, pp. 364–371.

G. Ilie and C. N. Ciocoiu. (2010). Application of fishbone diagram to determine the risk of an event with multiple causes. Management Research Practice, vol. 2, no. 1, pp. 1–20, 2010.

Kano, N., N. Seraku, F. Takahashi and S. Tsuji. (2004). Attractive Quality and Must-be Quality. The Journal of the Japanese Society for Quality Control, vol. 25, no. 14, pp. 39 -48.

Nelson, L. S. (2005). Interpreting Shewhart X Control Charts. Journal of Quality Technology, vol. 17, no. 12, pp. 114–116.

Quesenberry, C. P. (2013). The Effect of Sample Size on Estimated Effects. Journal of Quality Technology, vol. 25, no. 12, pp. 237–247.

Schilling, E. G. and Nelson, P. R. (2006). The Effect of Non-Normality on the Control Limits of X Charts. Journal of Quality Technology, vol. 8, no. 4, pp. 183– 187.

Wheeler, D. J. (2011). Shewhart’s Chart: Myths, Facts, and Competitors. 45th Annual Quality Congress Transactions. American Society for Quality Control. Pp. 533–538.


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