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Journal : IPTEK The Journal for Technology and Science

Integrated Risk Assessment on Argon Purification Unit Based on FMECA and Fuzzy-AHP Rengga Sanditya; Anda Iviana Juniani; Haidar Natsir Amrullah; Wiediartini Wiediartini
IPTEK The Journal for Technology and Science Vol 31, No 3 (2020)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v31i3.6345

Abstract

Argon Purification Unit is a processing unit to purify the crude argon using hydrogen gas through an automatic machinery process. Based on the hazardous material and its automatic machinery process, the argon purification unit needs to be assessed for risk control consideration and business performance. This research proposed risk assessment of argon purification unit based on the failure modes using Failure Modes, Effects and Criticality Analysis (FMECA) with Fuzzy Analytical Hierarchy Process (Fuzzy-AHP) approach to minimize the risks and losses. In this research, FMECA is used to identify the potential failure modes, failure mechanism (causes), potential failure effects for each unit component and evaluate the risk by determining risk priority number (RPN). The RPN is the product of severity, occurrence, and detection variables. Then, Fuzzy-AHP is used to determine the weight of each variable based on its hierarchy. The fuzzy-AHP approach aims to increase validity and decrease expert judgment subjectivity in the risk assessment process for each failure mode by considering variables’ weight. The result of RPN is gained by multiplying each failure mode’s variables by considering the importance of variables. This research results weight of severity is 0.43, which is the highest of all variables. The highest RPN is 8.76, shown by the leaked joint of the argon compressor. This research indicates that the application of the fuzzy-AHP approach in FMECA can identify and evaluate the potential risk of the Argon Purification Unit validly and objectively, which provides the different weight of RPN variables.