10.5 Asset Reliability Improvements

We’re currently rolling out an Asset Integrity Management System (AIMS) across our terminal network, which consists of nine terminals across Canada and the U.S. We’re publishing 27 new standards as part of this initiative that cover a variety of topics such as risk assessment, inspection planning, recordkeeping, data management, and relevant codes, standards, and regulations. This presentation will focus on the training and rollout of this program and will highlight some of the lessons learned. Some of the challenges include providing training to a group that spans a large geographical area, having a wide variety of stakeholders who require different levels of knowledge about the program (operations, project management, document control, contractors, management), and ensuring training is effective and leads to a smooth adoption of the changes that come with the new standards. Some of the topics we’ll cover include using the ADKAR model of change management to evaluate how effective your training will be; awareness of the need to change; desire to support and participate in the change; knowledge of how to change; ability to implement required skills and behaviours; reinforcement to sustain the change; tailoring presentations to specific groups; creating short and long versions of modules—building blocks for presentations; tailoring presentations to each group based on required knowledge; having a one-hour “crash course” presentation to give a quick overview to certain groups (upper management, those not directly impacted by standards); giving several opportunities for questions to ensure any potential issues are identified early (standard review, training, pre-publishing); and some tips on encouraging engagement: examples and exercises (real world), visual aids (flowcharts, photos, graphics over text), handouts (quick reference guide, poster, contact sheet, acronym list), and summaries (standard review sheets, single-page overviews).

New technologies regularly enter the world of asset management (AM), often leveraging new inventions, which, in turn, are driven or supported by other advances such as computing power and big data handling. Such is the case for Motion Amplification, a new technology impacting crucial aspects of vibration analysis, machinery and structural troubleshooting, root cause analysis, and communications. This presentation will outline which areas of AM are impacted so we can have a road map facilitating the integration of the new tool into a global strategy and get an overall picture of the impacts it will have. We’ll also provide a brief technical introduction and some practical illustrations.Originally presented at MainTrain 2020

With many people at home either due to the closure of their operations, self-isolation protocols, or as a proactive measure to reduce non-essential staff on site, some might question how these individuals can be productive, particularly when assets are not operating. However, if employees have access to their CMMS/EAM/ERP data systems from home, here are some value-added activities that employees and employers should consider undertaking given the time they now have. Note these are in no particular order as priorities would be context-specific, and specific procedures are omitted for this same reason. 

As 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! 

Even today, many organizations see maintenance as a necessary evil neglecting the importance it has toward attaining optimum business results. These organizations have maintenance managers, supervisors, and technicians who are responsible for the preservation of their physical assets. Upon talking to and sharing experience with many maintenance colleagues in various countries, I've learned that most maintenance supervisors and managers don't have a formal maintenance educational background, yet they must make important decisions regarding assets affecting their business's bottom line. We learn about maintenance the hard way, learning from equipment failures and guessing how to avoid them by applying what has resulted well in the past and what the equipment manufacturer tells us. When organizations realize they must do something about maintenance to improve their business bottom line, they're exposed to a lot of information about many tools boasting to offering what they need to do better. This presentation will showcase the results of various case studies performed by our consulting firm at crude oil pumping, pharmaceutical, and water treatment organizations located in North and South America. Several methodologies ranging from Uptime (Strategies for Excellence in Maintenance Management) to RCM-R, ACA, RCA, and even PdM were used to tackle situations at the strategic, tactic, and operational levels.

One major challenge at the operate and maintain phase of an asset is achieving and sustaining the forecasted availability and reliability as intended at the project delivery phase. Many problems arise—equipment failures, underperformance, high costs—that are caused by numerous issues. The resolution demands thorough understanding of the causes of the issues, which we usually attempt to achieve through RCA methodologies. I've experienced many repeated failures even when RCAs have been conducted, due, mainly, to most of the RCAs focusing attention on solutions to the problem outcomes with limited focus on the human and system causes that drive the outcomes. The Causal Learning Approach brings in the understanding of these other causes that ensure effective and sustainable solutions development. There are three levels of causes: the physical outcomes; the human causes; and the system causes. The Causal Learning Approach also focuses on causal reasoning instead of defensive and solution reasoning. This presentation will provide the understanding of these causes and the three key elements of this approach: discovery, learning, and solution generation.

The U.K. railway network dates back to 1825 and is the oldest railway in the world. Several electrical assets on the network such as track power cables, switchgears, overhead line isolators, circuit breakers, and insulators are beyond their design life and the business must decide whether to renew or replace them—even though they're still operating at the optimum performance level. These assets are still being maintained at the original regimes; the challenge to the business is to understand the degradation models and change them to achieve different maintenance regimes for the aging assets. The work we're currently undertaking is intended to influence and change our asset policies—in particular, the assignment of asset regimes for assets that remain in service at the end of their design life and beyond. The philosophy behind the maintenance regimes is that they're based on degradation models, which are algorithms that consider various factors such as the environment, the loading, the utilization, the reliability, and the cost for interventions. The approach we pursued was to review the parameters of the degradation models for their “fit,” based on the knowledge asset managers have gained on the ground and through large volumes of asset data. The asset data was analyzed with data visualization software to gain further insight to influence the review of the degradation models. The findings of the work are summarized here: asset population is aging and future renewals bow wave are predicted; asset policy pushes all assets to maximum asset technical life and fix-on or run-to failure; safety-related works prioritized over asset performance/resilience; there's a need to modify some factors associated with the degradation models to cater for extension of technical asset life and maintain a more realistic/sustainable asset renewal profile; composite asset condition scores are required to manage bow wave of asset renewals and implement sustainable obsolescence management techniques (this is predominantly driven by organizational investment decisions where enhancements are the main driver of asset acquisition, making future renewals difficult due to the requirement to renew similar age assets at the same time); and determination of useful asset life required for assets that are being left in service longer than their originally predicted life.

Metrics, best practices, more than 40 key elements to implement, challenges, and opportunities all combine to make a successful implementation difficult. Where do you start, and how do you know how to work on what matters? Once you understand how it’s all related, you can focus on the vital few to leverage the maximum ROI. This presentation will clarify the importance of culture and employee engagement, along with other key plant floor performance indicators that will be clarified with data. We'll look at the current state of R&M; what’s working and what's not; survival skills for the next decade; impacts of connected technologies (edge computing, big data, machine learning, AI, 3D printing, augmented reality); the importance of getting your data ready for what's coming next; and relationships between R&M and safety, people engagement, quality, throughput/uptime, and cost.

Quelle est l’opportunité pour les gens de maintenance dans l’Industrie 4.0 ?- Constat de la maturité de la maintenance au Québec- Rappel de vieux concepts d’ingénierie de maintenance- Survol des concepts de l’Internet des objets et de l’Industrie 4.0- Analyse de l’opportunité 4.0

Reliability 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.