LEADER 04935cam 2200493Ia 4500001 ocn773723379 003 OCoLC 005 20151103143340.0 006 m d 007 cr bn||||||||| 008 120124s2011 ncua ob 000 0 eng d 035 (Sirsi) o773723379 035 (OCoLC)773723379 040 ERE |cERE |dERE |dUtOrBLW 049 EREE 090 TS156.8 100 1 Zadeh Mohammadi, Mehdi. |?UNAUTHORIZED 245 10 Implementation of a system for monitoring overall equipment effectiveness (OEE) and exploring correlation between OEE and process capability / |cby Mehdi Zadeh Mohammadi. 260 [Greenville, N.C.] : |bEast Carolina University, |c2011. 300 122 pages : |billustrations (some color), digital, PDF file 336 text |2rdacontent 337 computer |2rdamedia 338 online resource |2rdacarrier 538 System requirements: Adobe Reader. 538 Mode of access: World Wide Web. 502 |bM.S. |cEast Carolina University |d2011. 500 Presented to the faculty of the Department of Technology Systems. 500 Title from PDF t.p. (viewed Mar. 9, 2012). 500 Advisor: Merwan Mehta. 520 3 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. 504 Includes bibliographical references. 650 0 Process control. |=^A47729 650 0 Total productive maintenance. |=^A697841 650 0 Machinery |xMonitoring. |=^A859998 653 Industrial engineering 700 1 Mehta, Merwan, |d1959- |=^A1269666 710 2 East Carolina University. |bDepartment of Technology Systems. |?UNAUTHORIZED 856 40 |zAccess via ScholarShip |uhttp://hdl.handle.net/10342/3764 949 |ojgml 994 C0 |bERE 596 1 4 998 2677554