Fuzzy Based Failure Mode and Effect Analysis Towards to Risks of Autonomous Maintenance Activities: As a TPM Implementation

Abstract

Manufacturing companies attach importance to Total Productive Maintenance (TPM) applications to extend equipment life and increase efficiency. The recommended applications with TPM are carried out under the pillar activities. Autonomous Maintenance (AM) pillar manage the assignments of the operators to undertake routine maintenance work on machine maintenance. Cleaning, lubrication and control activities are one of the steps of AM pillar and operators need to do them daily. However, there are a number of occupational health and safety risks that operators may face during these activities. Safety (S) pillar which serve as another TPM pillar, deal with occupational accidents and possible situations during TPM applications. AM and S pillars work together to assess the risks that may occur during AM applications. Failure Mode and Effect Analysis (FMEA) is also frequently utilized for risk assessment, but this is criticized in terms of the difficulty in reaching the common point of decision-makers’ risk assessment and equal weighting of risk factors. Therefore, it is appropriate to support with the fuzzy logic approach. In this study, the entropy-weighted fuzzy based FMEA method was utilized for identify and prioritize potential risks that may be encountered during the AM activities. Potential risks were revealed and evaluated with the FMEA team. Eleven potential risks were identified in the study. The risk factors of the assessment were weighted by the entropy method. The risk of hand injuring during cleaning the oil below material cutting saw has the highest risk priority.