MATEC Web Conf.
Volume 204, 2018International Mechanical and Industrial Engineering Conference 2018 (IMIEC 2018)
|Number of page(s)||6|
|Published online||21 September 2018|
Human error probability analysis of overhead crane operation in steel fabrication company using SLIM-DEMATEL-ANP method
Student, Safety Engineering, Shipbuilding Institute of Polytechnic Surabaya, 60111 Surabaya, Indonesia
2 Safety Engineering, Shipbuilding Institute of Polytechnic Surabaya, 60111 Surabaya, Indonesia
3 Waste Treatment Engineering, Shipbuilding Institute of Polytechnic Surabaya, 60111 Surabaya, Indonesia
4 Marine Engineering, Shipbuilding Institute of Polytechnic Surabaya, 60111 Surabaya, Indonesia
5 Design and Manufacture Engineering, Shipbuilding Institute of Polytechnic Surabaya, 60111 Surabaya, Indonesia
Corresponding author : firstname.lastname@example.org
The accident record from a steel fabrication company in 2014-2017 shows that the most frequent accidents take place in overhead crane operation with a percentage of 42%. The overhead crane operation has the greatest potential of accidents with human error as the main cause. The purpose of this study is to determine what factors affect the occurrence of errors, to know how much HEPs, and to determine recommendations. The method used in this research is Success Likelihood Index Method (SLIM) with qualitative development using Decision Making Trial and Evaluation Laboratory (DEMATEL) which aims to establish the relationship among PSFs to be an easily comprehensible structured model by considering expert judgements and to solve dependency in a set of criteria. Analytic Network Process (ANP) is used to overcome the inconsistency of expert judgements and difficulty in selection and weighting. The calculation and analysis reveal that the highest Human Error Probability (HEP) value is shown by the task to handling or lifting with the value 0.000485. Impact assessment using the HEP value to determine probability and consequence is performed by expert judgements. Improvement recommendations are prioritized for high rating error tasks using Error Reduction Analysis.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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