Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Issue title: Special Section: FLINS 2018
Guest editors: Cengiz Kahraman
Article type: Research Article
Authors: Uzun, Ibrahim Mert | Cebi, Selcuk; *
Affiliations: Department of Industrial Engineering, Yildiz Technical University, Turkey
Correspondence: [*] Corresponding author. Selcuk Cebi, Department of Industrial Engineering, Yildiz Technical University, Turkey. Tel.: +90 212 383 2746; E-mail: scebi@yildiz.ed.tr.
Abstract: Risk identification and risk assessment are the most important issues among the occupational health and safety practices. In the industry, the identification of hazards and the risk assessment are often carried out by using subjective risk assessment methods. These methods usually do not provide a perspective on the nature of the measures to be taken. In order to keep sector-specific risks under control, as important as the assessment of risks is to take effective measures against these risks and to continuously monitor the effectiveness of these measures. Therefore, the main objective of this paper is to classify protective and preventive occupational health and safety measures implemented in the construction sector based on their efficiency by using Fuzzy Kano Model Approach. For this purpose, it is the first time, the feature classes defined by the conventional Kano Model and the Kano Model questionnaire have been reinterpreted in terms of occupational health and safety. Then, the proposed approach has been applied to classify the safety measures utilized in occupational health and safety in terms of their efficiency by using fuzzy Kano Model. According to obtain results, approximately 10% of the control measures which are effectively used at construction site are in Trusting Measure Class. The main contribution of this paper is to provide a new method for analysis of effectiveness of the occupational health and safety measures.
Keywords: Safety measures, fuzzy kano model, accident prevention, construction accidents
DOI: 10.3233/JIFS-179432
Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 589-600, 2020
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl