Predictive equipment failure methodology with sustainable change

This dissertation examines an analytical methodology that considers predictive maintenance on industrial facilities equipment to exceed world class availability standards with greater understanding for organizational participation impacts. The research for this study was performed at one of the world's largest semiconductor facilities, with the intent of understanding one possible cause for a noticeable behavior in technical work routines. Semiconductor manufacturing disruption poses significant potential revenue loss on a scale easily quantified in millions of dollars per hour. These instances are commonly referred to as "Interruption to production" (ITP). ITP is a standardized metric used across Company ABC's worldwide factory network to track frequency of occurrence and duration of manufacturing downtime. ITP, the key quantifiable indicator in this dissertation, will be the primary analytical measurement to identify the effectiveness of maintenance personnel's work routines as they relate to unscheduled downtime with facilities systems. This dissertation examines the process used to obtain change in an industrial facilities organization and the associated reactions of individual organizational members. To give the reader background orientation on the methodology for testing, measuring and ultimately assessing the benefits and risks associated with integrating a predictive equipment failure methodology, this dissertation will examine analytical findings associated with the statement of purpose as it pertains to ITP reduction. However, the focus will be the exploration of behavioral findings within the organization and the development of an improved industry standard for predictive ITP reduction process implementation. Specifically, findings associated with organizational participation and learning development trends found within the work group.