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Predictive Maintenance: A Strategy for Maximum Asset Utilization and Cost Reduction: By Dave Thomas, EMA

Things are changing. Business has entered the “next wave” of asset productivity improvement – one that places new and additional stresses upon operations and productivity management. Enhanced demands for operational effectiveness, improved revenue and customer satisfaction, integrally linked to a simultaneous reduction in capital, operating and support costs.[1] To achieve these objectives will demand a new strategy to reach unprecedented levels of equipment availability, reliability and maintainability.

These demands have raised the discussion of “maintenance strategy” to a new level of importance, particularly among superior production and manufacturing companies. Identified as an expense on the operating budget, and a frequent target of cost-reduction programs, most understand the value and role of maintenance in today’s plant floor environment.

Maintenance, however, has been interpreted and classified in a number of different ways. Within the United States the most popular maintenance strategy is “Preventive Maintenance.” The term refers to a maintenance strategy which is explicitly centered to prevent faults from occurring by any viable and promising tools and techniques.”[2] However, a new maintenance strategy is rapidly emerging as the dominant methodology – Predictive Maintenance.

Predictive maintenance seeks to employ a strategy of measurements and analysis to detect the early onset of equipment degradation, thereby eliminating causal stressors, compensatory damages, and allow for a coordinated program between operations and production to perform the required maintenance. Basically, predictive maintenance is classified as such because it aims to prevent the occurrence of failure by execution of in-time maintenance.[3]

The Big Question: Does Predictive Maintenance deliver on its promises? Is Predictive Maintenance Cost Effective?

S&C Electric Company, a manufacturer of power distribution equipment, located on the North Side of Chicago responds with a resounding Yes. “Repair work orders are down 90%; production machinery uptime has increased from 90% to 97%. These improvements are estimated to save at least $4 million annually.”[4]

ENEL, Italy’s largest power company, implemented a predictive maintenance strategy at their Brindisi power station. They have reported enhanced plant management, increased reliability, safety standards and the residual life of machine components, reduction in unnecessary repairs, and a major reduction in maintenance costs. “The end result is an economic optimization of resources and improved overall equipment effectiveness (OEE), a recognized measure of plant effectiveness.”[5]

Cabot Corporation in Midland, MI reduced plant downtime from 18% to 4% while production increased by 10%.[6]

Alabama Power experienced a 10% reduction in routine maintenance through faster troubleshooting and predictive maintenance.[7]

The Important Question: Is a Predictive Maintenance Strategy Right for Your Company?

Introducing a Predictive Maintenance strategy requires an implementation analysis and should not be viewed as an all or nothing approach. EMA has been actively involved in working with clients across a wide industry spectrum to determine how to implement a Predictive Maintenance strategy. If maximizing asset utilization while reducing costs is of interest to you, we invite you to contact EMA at 770-448-4644.You may also contact us by hitting the contact icon on the top right of this page, or by clicking the “live support” icon.

[1] Schuman and Brent, “Asset life cycle management: towards improving physical assets performance in the process industry”, International Journal of Operations & Production Management, Vol. 25 No. 6, 2005, p. 566.

[2] Khazraei and Deuse, “A strategic standpoint on maintenance taxonomy”, Journal of Facilities Management, Vol. 9 No. 2, 2011, p. 100.

[3] Khazraei and Deuse, “A strategic standpoint on maintenance taxonomy”, Journal of Facilities Management, Vol. 9 No. 2, 2011, p. 102.

[4] Nailen, “Asset Management”, Electrical Apparatus, July 2006; 59, 7; p. 17.

[5] Tiraboschi and De Francesco, “Improving plant efficiency using predictive maintenance”, Power Engineering International; Nov 2008; 16, 9, p. 78.

[6] Broussard, “Act, don’t react, for greater asset optimization”, Plant Engineering, August 2007.

[7] Broussard, “Act, don’t react, for greater asset optimization”, Plant Engineering, August 2007.