Shared Learning Library
Welcome to PEMAC's Shared Learning Library, a growing body of community created knowledge, built up and maintained by the PEMAC member community. Explore a range of articles, presentations and webcasts covering a wide range of maintenance, reliability and asset management subject areas. You can even find presentations from past MainTrain conferences and PEMAC Lunch & Learn webcasts.
To easily find what you are looking for the content of the Shared Learning Library can be filtered by both Maintenance Management and Asset Management subject areas using the options in the menu to the left of the screen.
Displaying 1 - 5 of 5
BoK Content Type:Presentation SlidesWebcastPresentation PaperBoK Content Source:MainTrain 2019Original date:Sunday, March 8, 2020As the influence of the asset management approach continues to expand within Nova Scotia Power, we need a structured approach to ensure we continue to seek opportunities to optimize maintenance strategies. In a new installation, techniques such as failure modes and effects analysis (FMEA) and reliability centred maintenance (RCM) can be used to develop an optimized maintenance strategy from the start, in a top-down approach. However, the vast majority of Nova Scotia Power’s equipment was in place long before the asset management office—and, therefore, the asset management approach—existed. The result of that is a collection of value-added, but developed after-the-fact maintenance strategies. Each maintenance strategy has components of operator surveillance (rounds), testing, predictive pattern recognition (also known as advanced pattern recognition, APR), predictive maintenance (condition-based monitoring and risk-based inspections), online monitoring, and preventative maintenance. While efforts had been made to “baseline” the equipment processes when maintenance strategies were developed (i.e., “clean out” existing activities), the organic growth of the approach and the distributed nature of assets and personnel have made this difficult to maintain. Therefore, we needed an approach to optimize existing maintenance strategies, without recreating them. Nova Scotia Power has therefore undertaken an effort known as maintenance strategy optimization, and has made this activity a core accountability for the asset management team, which recognizes the need to seek continuous improvement (vs. a one-time exercise). With a focus on digitization wherever appropriate, Nova Scotia Power has asked a number of questions to streamline, standardize, and optimize its maintenance strategies. Is there opportunity to reduce PM frequency? Is there opportunity to collect more information such that we can strengthen our APR models? Can our in-house standards be revalidated to sustainably reduce operating and maintenance costs? Nova Scotia Power is answering yes to these questions, and more, and pursuing opportunities to optimize its maintenance strategies—from the bottom up!
Root Cause Analysis: Driving Bottom Line Improvement by Preventing One Failure at a TimeBoK Content Type:Presentation SlidesWebcastBoK Content Source:Practitioner ProducedOriginal date:Thursday, February 28, 2019Many maintenance and reliability staff are so busy fixing problems that they never get the chance to prevent them. In a reactive work environment, there is simply no time to spare. Root cause analysis (RCA) gives us an easy-to-implement approach to preventing failures that integrate with our current troubleshooting efforts and drives bottom-line business improvement. We can make our workplaces safer by reducing the number of unexpected failures, which will then result in improving our business performance, increasing our facility’s throughput and reducing the money spent on repairs – straight to the bottom line.
Reliability Centered Maintenance Re-Engineered RCM-R(r) - An IntroductionBoK Content Type:Presentation SlidesWebcastPresentation PaperBoK Content Source:Practitioner ProducedOriginal date:Monday, June 11, 2018Reliability Centered Maintenance – Reengineered, provides an optimized approach to a well established and highly successful method used for determining failure management policies for physical assets. It makes the original method that was developed to enhance flight safety, far more useful in a broad range of industries where asset criticality ranges from high to low. RCM-R® is focused on the science of failures and what must be done to enable long term sustainably reliable operations. If used correctly, RCM-R® is the first step in delivering fewer breakdowns, more productive capacity, lower costs, safer operations and improved environmental performance. Maintenance has a huge impact on most businesses whether its presence is felt or not. RCM-R® ensures that the right work is done to guarantee there are as few nasty surprises as possible that can harm the business in any way. RCM-R® addresses the shortfalls of RCM that have inhibited its broad acceptance in industry. Little new work has been done in the field of RCM since the 1990’s, yet demand for such a method, better adapted to industrial applications is higher than ever and growing. Demographics and ever more complex systems are driving a need to be more efficient in our use of skilled maintenance resources while ensuring first time success – greater effectiveness is needed. RCM-R® was developed to leverage on RCM’s original success at delivering that effectiveness while addressing the concerns of the industrial market. RCM-R® addresses the RCM method and shortfalls in its application. It modifies the method to consider asset and even failure mode criticality so that rigor is applied only where it is truly needed. It removes (within reason) the sources of concern about RCM being overly rigorous and too labor intensive without compromising on its ability to deliver a tailored failure management program for physical assets sensitive to their operational context and application. RCM-R® also provides its practitioners with standard based guidance for determining meaningful failure modes and causes facilitating their analysis for optimum outcome. It places RCM into the Asset Management spectrum strengthening the original method by introducing International Standard based risk management methods for assessing failure risks formally. RCM-R® employs quantitative reliability methods tailoring evidence based decision making whenever historical failure data is available.
PM ou PdM - où est l'équilibre ? - 15 octobre 2016BoK Content Type:WebcastBoK Content Source:Practitioner ProducedOriginal date:Saturday, October 15, 2016PM ou PdM - où est l'équilibre ?- Défaillance dans le cycle de vie- Les différents patron de défaillances (RCM)- Criticité et contexte opérationnel- Les différentes tactiques possibles- Introduction à la courbe PF- Comment choisir la bonne tactique
Simplifying RCM to Achieve Value with a Risk-Based Asset Management MethodologyBoK Content Type:Presentation SlidesPresentation PaperBoK Content Source:MainTrain 2016Original date:Thursday, September 22, 2016Risk-Based Asset Management is a strategic management approach to physical assets that leverages an enabling technology such as SAP Plant Maintenance coupled with risk and failure based controls. This approach ensures optimum asset care to drive increased availability that creates value, resulting in higher profits. Today, increasing asset utilization and decreasing total cost of ownership are standard corporate objectives. Organizations must optimize asset performance to survive tough business conditions. The focus on continuous improvement and lean events to increase OEE, improve availability and reduce life cycle costs is now common place - but this approach doesn't go far enough. Faced with the lack of technically qualified people, an aging work force, and shrinking margins, organizations must consider risk when applying resources to asset management. This presentation will describe the process of cataloging physical assets by hierarchy, criticality and risk. Participants will receive an overview of risk and failure analysis and their linkage to controls, and discover how some common reliability analysis techniques can used to ensure continuous improvement.