Skip to main navigation Skip to search Skip to main content

Production risk management of prawn crackers using fuzzy FMEA and fuzzy AHP methods

Research output: Contribution to journalArticlepeer-review

Abstract

Prawn crackers hold a significant position within Indonesia's agro-industrial product landscape. The industrial process involved in their production is fraught with potential risks that could result in substantial losses for companies. PT. XYZ, a prominent prawn cracker producer in Indonesia, grapples with various risks, including non-compliant raw material supplies, machinery and equipment breakdowns, product defects, and process failures. Hence, there is an imperative need for comprehensive risk management involving further analysis, identification of potential failure modes, and formulation of mitigation strategies to curb losses. This research aims to ascertain the priority of potential failure modes and their corresponding mitigation strategies in the prawn cracker production process at PT. XYZ. The study employs risk analysis through the Fuzzy Failure Mode and Effect Analysis (Fuzzy-FMEA) method and determines mitigation strategies using the Fuzzy Analytical Hierarchy Process (Fuzzy-AHP) method. The findings reveal 11 identified failure modes in PT. XYZ's prawn cracker production process, with machinery and equipment damage emerging as the top-priority failure mode, giving a Fuzzy Risk Priority Number (FRPN) value of 7.620. The recommended mitigation strategy involves intensifying inspections of production machinery and equipment, both before and after use by workers, with a weight of 0.368.

Original languageEnglish
Pages (from-to)150-157
Number of pages8
JournalAdvances in Food Science, Sustainable Agriculture, and Agroindustrial Engineering
Volume7
Issue number2
DOIs
Publication statusPublished - 2024

Keywords

  • Analytical Hierarchy Process
  • Crackers
  • Failure Mode and Effect Analysis
  • Fuzzy Risk

Fingerprint

Dive into the research topics of 'Production risk management of prawn crackers using fuzzy FMEA and fuzzy AHP methods'. Together they form a unique fingerprint.

Cite this