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.
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