Workplace assessment by fuzzy decision tree and TOPSIS methodologies to manage the occupational safety and health performance
Article type: Research Article
Authors: Taylan, Osmana; * | Zytoon, Mohamed A.a; b | Morfeq, Alic | Al-Hmouz, Ramic | Herrera-Viedma, Enriquec; d
Affiliations: [a] Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia | [b] Department of Occupational Health and Air Pollution, High Institute of Public Health, Alexandria University, Alexandria, Egypt | [c] Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia | [d] Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain
Correspondence: [*] Corresponding author. Osman Taylan, Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, P.O. Box 80204, Jeddah, Saudi Arabia. Tel.: +966500031056; Fax: +966126952486; E-mail: [email protected].
Abstract: Food manufacturing industries have poor occupational safety and health (OSH) performance in many countries. The situation in Saudi Arabia is unknown due to absence of previous studies on the OSH performance of food industry. The current revised Labor Law is expected to dramatically increase workplace inspections by governmental inspectors. Therefore, both the industry and the OSH inspection authority needs to develop an effective decision making approach for improving the performance of companies. The objective of this study is to use quantitative and qualitative data for the assessment of OSH performance and develop a more reliable assessment approach. For the evaluation of OSH performance of food companies, a set of main and sub-criteria were determined. The quantitative assessments were carried out in accordance with national compliance requirements using a 5-point Likert scale approach. For the qualitative assessment, fuzzy linguistic terms were employed to measure the degree of satisfaction of main and sub-criteria. Two methods; the fuzzy decision tree approach and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) were used for the evaluation and the competitiveness of companies. The fuzzy decision tree approach was used for criteria weight determination, however, the fuzzy TOPSIS approach revealed the best practices regarding OSH for benchmarking, and governmental authorities for managing the regulatory inspections conducted to follow up compliances. Hence, the presented approach was used to rank 21 food enterprises, and it was found that company (x7) is the best in all criteria. The key difference between this company and the other companies is that it showed consistent performance in all criteria, while in the others were found in performance fluctuations and deficiency in some sub-criteria. On the other hand, the quantitative assessment showed that most companies with good score are technically good which indicates that the technologies used are fairly up-to-date which generate less occupational hazards. This leads to the conclusion that the OSH problems in the Saudi food industries are mainly due to managerial deficiencies rather than being financial. The ranking can be used by the food industries for also benchmarking their performance within the context of the food industry sector. The overall aim is to identify the best industrial practices and identify the priorities to help the official bodies for a more effective inspection.
Keywords: Workplace OSH performance assessment, fuzzy decision tree, fuzzy TOPSIS, OSH inspection, food industries
DOI: 10.3233/JIFS-17043
Journal: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 2, pp. 1209-1224, 2017
