A hybrid risk assessment method for mining sector based on QFD, fuzzy inference system, and AHP

Cinar U., ÇEBİ S.

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, cilt.39, sa.5, ss.6047-6058, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 39 Sayı: 5
  • Basım Tarihi: 2020
  • Doi Numarası: 10.3233/jifs-189078
  • Dergi Adı: JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.6047-6058
  • Anahtar Kelimeler: Risk assessment, mining sector, QFD, fuzzy logic, AHP, SAFETY, SITES, LOGIC
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Conventional risk assessment methods are widely used for industrial safety applications. However, there are serious obstacles to their usage as; (i) all of the potential hazards are considered as an independent event, (ii) various risks are identified based on these hazards, (iii) risk magnitudes of these risks are obtained without considering interdependencies among the hazards, and then (iv) the protective measures against the defined risks are taken based on these risk magnitudes. Therefore, conventional methods do not provide any assessment for overall risks in the working environment. Furthermore, although an accident may cause different severity such as loss of working days, loss of limbs, occupational disease, and death, the conventional methods do not consider all potential consequences of any accident, simultaneously. The main objective of this paper is to propose an effective risk assessment approach by using the fuzzy set theory, Analytical Hierarchy Process (AHP), Fuzzy Inference System (FIS), and Quality Function Deployment (QFD) methods to quantify the risk of any hazard considering interdependencies among all potential hazards and consequences in working environment. Within the scope of this research, an application in the mining sector has been presented to illustrate the validation and the effectiveness of the proposed approach**.