Applying a Control Chart to the Learning Curve in TPM Adoption

Abstract

Total productive maintenance (TPM) has been recognized as a useful methodology for maximizing equipment effectiveness and overall equipment effectiveness (OEE). Considering the multiplicity of availability, performance, and quality factors, it is an important performance metric for evaluating the adoption of TPM. In this study, a time constant learning curve model is used to formulate a forecasting model of OEE. An OEE forecast can be considered as a process and, therefore, can be managed by statistical process control (SPC). A control chart, i.e. an EWMA (exponentially weighted moving average) in this study, is easily used to monitor the forecast errors. If the forecast errors go out of the control limits, then something has happened to the TPM adoption and that the implementers should be notified and actions should be taken to ensure the successful adoption of the TPM. OEE data collected from three factories in Taiwan and Japan are used for illustration.

Key Words:

• Control chart
• learning curve
• overall equipment effectiveness
• total productive maintenance

Additional information

Notes on contributors

Wang Fu-Kwun

Fu-Kwun Wang He is an associate professor in the Department of Industrial Management at National Taiwan University of Science & Technology, Taiwan. His primary research interests are in reliability, statistical quality control and supply chain management.