Using evidential reasoning approach for prioritization of maintenance-related waste caused by human factors\u2014a case study

Abstract

The reduction and elimination of maintenance-related waste is receiving increasing attention because of the negative effect of such waste on production costs. The overall goal of this research is to identify and prioritize factors that can be considered maintenance-related waste within the automotive manufacturing industry. Five manufacturing companies participated in a workshop to identify root causes of maintenance-related waste; 16 categories were found. The identified factors were heavily reliant on human factors as a root or major contributory cause at different levels affecting performance and productivity. For prioritization, the evidential reasoning (ER) approach which is one of the latest developments in multi-criteria decision-making is applied. A basic tree structure necessary for ER assessment is developed based on the workshop results as well as literature on human factors. Then, a survey on basic attributes at the lowest level of this tree is designed and performed at one of the companies participating in the workshop. The application of ER shows that, on an overall level, “management condition” is in first order and “maintainer condition” and “working condition” are in second and third order respectively as the worst cases for creating maintenance-related waste. On the most delimited level “inadequate resources” and “weather/indoor climate” have the highest and lowest average scores respectively in ER ranking or prioritization. This methodology with its resulting ranking can be used as a tool to create awareness for managers seeking to reduce or eliminate maintenance-related waste.