Abstract
The objective of this research is to propose an extension of the Overall Equipment Effectiveness (OEE) by including information on OEE prediction through simulation modeling and experiments procedure (SMEP) in order to extent the benefit of OEE as key performance indicator (KPI). To succeed in total productive maintenance (TPM) implementation, a company needs to have the expertise in deciding which workstation or production lines needs priority improvements. This process simulation approach enables the decision-makers t0 forecast the output of manufacturing processes and the effectiveness of TPM, based on the input values. This study reveals the feasibility of the proposed decision support system. SMEP is able to address the complex interdependent input parameters in manufacturing line and provides the company with time to react to emerging problems evaluate potential solutions and decide on TPM implementation.
