Author_Institution :
Millar Western Pulp Ltd., Whitecourt, Alta., Canada
Abstract :
Mechanical and electrical maintenance of industrial plant machinery is often carried out on a ´need to know´ basis. Those who analyze the data and prepare work orders for maintenance and repair know why they have prepared the orders, but those involved in the actual maintenance of the machinery, often know little more than which component to replace. By implementing an easy-to-use, accurate system of both machinery condition data collection and analysis, and by involving all maintenance personnel in the process, plant operation can become efficient and cost-effective. Personnel are educated as to the cause and extent of the damage, and learn how essential it is to pinpoint potential problems before they occur. By taking this proactive approach, a company can save millions of dollars by avoiding costly damage, unscheduled shutdowns, lost man-hours and missed project deadlines. This paper describes how to practically implement a cost effective predictive maintenance program, discussing what to do, what not to do, case histories, and the benefits and results achieved.
Keywords :
electric machines; maintenance engineering; paper industry; cost effective predictive maintenance program; electrical maintenance; industrial plant machinery; machinery condition data analysis; machinery condition data collection; maintenance personnel; mechanical maintenance; predictive maintenance implementation; proactive approach; pulp mills; Accelerometers; Data analysis; Lakes; Machine learning; Machinery; Milling machines; Personnel; Petroleum; Predictive maintenance; Vibrations;