Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/8286
Title: Applying Analytic Hierarchy Process (AHP) to choose a human factors technique: Choosing the suitable Human Reliability Analysis technique for the automotive industry
Authors: Petruni A.
Giagloglou, Evanthia
Douglas E.
Geng J.
Leva, Maria Chiara
Demichela, Micaela
Issue Date: 2019
Abstract: © 2017 Elsevier Ltd The increasing level of automation and complexity in the automotive industry has led to the establishment of a work environment, where human machine interface and human reliability are becoming critical factors of performance especially for safety critical tasks. Many different methodologies for performing risk assessment considering human factors are already available in the literature, but they were often developed for domains other than the automotive industry (aviation, nuclear and process industry). Their purpose is to support the root cause evaluation and estimate the probability of faulty human actions. The present paper introduces a method to support the evaluation and the choice of a suitable Human Reliability Analysis (HRA) technique for the automotive sector considering the ones proposed from other industrial domains. The Analytic Hierarchy Process (AHP) provides a way of assisting safety managers and risk assessors in the HRA technique selection process. This allows the selected HRA techniques to be evaluated based on relevant criteria for an application in an automotive manufacturing environment. An example of selected HRA techniques in this paper will be demonstrated in a case study. The example can also suggest implications to improve existing industry guidelines, international standards and regulations, which are frequently calling for a wide range of ergonomic factors to be considered in the risk assessment process. Further the case study should show potential benefits to organizations coming from the selection and application of the right HRA technique.
URI: https://scidar.kg.ac.rs/handle/123456789/8286
Type: article
DOI: 10.1016/j.ssci.2017.05.007
ISSN: 0925-7535
SCOPUS: 2-s2.0-85019718070
Appears in Collections:Faculty of Engineering, Kragujevac

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