Risk Assessment Fuzzy-FMEA for the Prevention and Control of COVID-19 at Sarawak Longhouses

Authors

  • Mohd. Zulhilmi Firdaus Rosli Department of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan, Sarawak, Malaysia
  • Kasumawati Lias Department of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan, Sarawak, Malaysia
  • Aysha anak Samjun Department of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan, Sarawak, Malaysia
  • Helmy Hazmi Faculty of Medicine and Health Sciences, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan, Sarawak, Malaysia
  • Kuryati Kipli Department of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan, Sarawak, Malaysia
  • Hazrul Mohamed Basri Department of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan, Sarawak, Malaysia

Keywords:

COVID-19, FMEA, artificial intelligence, multi-criteria decision making, Mathematical programming, integrated approach

Abstract

The COVID-19 outbreak causes great concern due to the high rates of infection and the large number of deaths worldwide. This paper presents a risk assessment Fuzzy-FMEA for the prevention and control of COVID-19 at Sarawak longhouses. The paper also provides a comprehensive review study on the transmission potentials, effects, and causes of COVID-19, which emphasize Artificial Intelligence (AI), Multi-Criteria Decision Making (MCDM), integrated approaches, and mathematical programming with Failure Mode and Effect Analysis (FMEA). The spreading of COVID-19 can be controlled and prevented by implementing the FMEA method by considering each failure mode's severity, occurrence, and detection rating via the Risk Priority Number (RPN) value. However, FMEA alone cannot provide a precise risk evaluation as the generated RPN might be unreliable in real-life applications. Recent research shows that the limitation of conventional FMEA can be tackled by aggregating it with other approaches. In conclusion, FMEA with a combination of fuzzy methods is a great integration in order to conduct a risk assessment to prevent and control infectious diseases, which in this paper is focused on COVID-19 incidences.

Author Biographies

Mohd. Zulhilmi Firdaus Rosli, Department of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan, Sarawak, Malaysia

emifirdausi@gmail.com

Kasumawati Lias, Department of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan, Sarawak, Malaysia

lkasumawati@unimas.my

Helmy Hazmi, Faculty of Medicine and Health Sciences, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan, Sarawak, Malaysia

hhelmy@unimas.my

Kuryati Kipli, Department of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan, Sarawak, Malaysia

kkuryati@unimas.my

Hazrul Mohamed Basri, Department of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan, Sarawak, Malaysia

mbhazrul@unimas.my

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Published

2025-12-10

Issue

Vol. 40 No. 1: September (2025)

Section

Articles