Early-Stage Transition to Predictive Maintenance: Using CMMS, IR Scans, and Vibration Analysis to Improve Uptime and Lower Maintenance Costs
Jason Hamilton
Abstract
Open-access reader
Jason Hamilton
Abstract
Open-access reader
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%.
OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
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%.
Key concepts: Predictive maintenance, Preventive maintenance, Planned maintenance, Reliability engineering, Corrective maintenance, Predictive value, Proactive maintenance, Computer science