Proposal of analysis method of the worst accidents reasons (AMWAR) for product safety to clarify the worst accident scenarios when using consumer products

Hattan Altiyare, Akinori Komatsubara

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Accidents due to the misuse of consumer products are the main concern in this study. Currently, the traditional risk assessment processes such as the ISO/IEC 51 guide have been proposed for industrial machines. However, designers and safety managers for consumer products tend to relay on their experiences to conduct risk assessment. The reason is that the workload could be high because, with the traditional risk assessment processes, all risks including acceptable level of risk are evaluated for the targeted product. To solve this problem, we have developed the analysis method for worst accidents reasons (AMWAR), which is based on the concept of sabotage analysis focusing only on high-risk accidents. A case study was conducted using people with little experience in risk assessment to determine whether or not they could find out accident scenarios with AMWAR. A company survey was also conducted to evaluate AMWAR by people in charge of product safety. During the case study, the participants managed to forecast many accident scenarios. In the company survey, AMWAR was approved as a risk assessment method that could help reduce the workload. It was also suggested that AMWAR could be used as an educational tool for risk assessment and could be applied in all manufacturing stages of the product; especially those which newly developed without an accident history at the market.

Original languageEnglish
Pages (from-to)182-189
Number of pages8
JournalJournal of Japan Industrial Management Association
Volume66
Issue number2E
Publication statusPublished - 2015

Keywords

  • Product safety
  • Risk finding
  • Sabotage analysis

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Applied Mathematics

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