Advances in Industrial Engineering

Advances in Industrial Engineering

Prediction of Accident Occurrence Possibilityby Fuzzy Rule-Based and Multi-Variable Regression (Case Study: Lift Trucks)

Document Type : Research Paper

Authors
Rouzbeh Ghousi
AmirHossein Masoumi
Ahmad Makui
School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran.
10.22059/jieng.2021.328736.1797
Abstract
Uncertain and stochastic conditions of accidents could affect the risk and complexity of decisions for managers. Accident prediction methods could be helpful to confront these challenges. Fuzzy inference systems (FIS) have developed a new attitude in this field in recent years. As lift truck accidents are one of the main challenges that industries face worldwide, this paper focuses on predicting the possibility of these types of accidents. At first, the data collection is done by using interviews, questionnaires, and surveys. A FIS approach is proposed to predict the possibility of lift truck accidents in industrial plants. Furthermore, our approach is validated using data from many real cases. The results are approved by the multivariate logistic regression method. Finally, the output of the fuzzy and logit models is compared with each other. The re-validation of the fuzzy control model and high consistent of the output of these two models is presented.
Keywords
Accident Prediction
Fuzzy Inference System (FIS)
Multivariate Logistic Regression
Lift Truck Accident
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Advances in Industrial Engineering
Volume 55, Issue 2
Spring 2021
Pages 191-201