| Summary |
An effective process equipment monitoring tool widely accepted in manufacturing units today is overall equipment effectiveness (OEE). OEE began its debut as a pillar of the total productive maintenance (TPM) system, where the goals are to increase the reliability and availability of equipment so that resource waste is reduced and product quality is enhanced. Interest by a manufacturing company in North Carolina in evaluating OEE in terms of appropriateness in its application, along with a desire to explore other quality performance metrics that can be easily tracked to predict OEE, was the motivation behind this study. The goals of this study were: 1) To recommend to the manufacturing company definite steps that they should undertake to implement a robust OEE based equipment performance evaluation system, 2) To demonstrate on a pilot basis how the implementation should be carried out, and 3) Study whether process capability which can be used as a leading quality indicator has any correlation to OEE which is a lagging indicator. A framework was established for the implementation of OEE in a pilot area of the manufacturing unit. A systematic plan was proposed and implemented which demonstrated that it is possible to reverse the effects of an ineffective OEE measurement process and create an effective system to pursue continuous improvement. Success in this endeavor can be attributed to pursuing training at various levels. Another key factor in establishing the system was using an appropriate calculation method for OEE compatible to the understanding power of the company's workforce. Providing clear definitions that were easy to understand and interpret for all terms involved in the OEE calculation also played a key role in the success of the implementation. Recommendations on how to go about changing the company's culture to embrace the concept of OEE were provided and pursued. Use of OEE values for conducting personnel annual evaluations was stopped. For exploring the correlation between process capability and OEE, the null hypothesis that there is no relation between process capability index and OEE, and between process capability index and each of OEE's three elements which are availability, performance and quality, was chosen. Calculating p-values for hypothesis testing, using non-linear regression analysis it was found that at a significance level of 0.05, the null hypothesis cannot be rejected for any of the four sub-hypothesis. Limitations to the study included a short time period for the study and a lack of good available data. Another limitation was the fact that the final decision whether a part is good or bad was made by attempting to assemble the part in the final assembly operation. Further future work to this study would be to explore correlation between process capability and OEE in a controlled lab environment with more machines and parts and definite part specification limits. |
