First Advisor

William Eisenhauer

Date of Award

2015

Document Type

Thesis

Degree Name

Bachelor of Science (B.S.) in Mechanical Engineering and University Honors

Department

Mechanical Engineering

Subjects

Machinery -- Maintenance and repair, Plant maintenance -- Management

DOI

10.15760/honors.188

Abstract

Implementing a predictive maintenance model does not have to be a five year, million dollar project. There are relatively simple steps a maintenance team can take to see results within the first year. Because overall cost of predictive maintenance is up to four time less expensive than preventative maintenance, as many assets as possible should be covered by predictive maintenance. Facilitating the transition to predictive maintenance is made easier with a Computerized Maintenance Management System. A good CMMS is user-friendly, automatically produces preventative maintenance work orders, and tracks all work done on each piece of machinery. IR scans and vibration analysis are two predictive maintenance techniques that can increase uptime. IR scans are an effective way to find loose or dirty electrical connections before they cause machine down time. Vibration analyses show bearing faults before the bearing locks up and destroys the journal.

Fitesa Washougal is a single machine non-wovens facility in Washougal, Wa. In July 2014 the maintenance team at this facility implemented a new predictive maintenance model. A new CMMS was purchased to better manage assets and preventative maintenance activities. Vibration analysis was contracted to an outside company, and is now done monthly. IR scans are done in-house, with each cabinet in the program scanned quarterly. These actions have resulted in a 3.5% increase in uptime. Maintenance spending increased by 31%, but unplanned maintenance downtime decreased by 34%.

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Persistent Identifier

http://archives.pdx.edu/ds/psu/15437

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