3.06 Reliability Engineering

Through the introduction of online monitoring technologies in the field, including substation monitors capable of providing near-real-time data and readings on power transformers, switchgear and circuit breakers, along with line monitors for overhead conductor and monitors for underground cables, organizations now possess novel opportunities to integrate this data into their asset management frameworks such that decision-making can be enhanced. This presentation will examine recent efforts to develop Asset Performance Management (APM) frameworks, leveraging available near-real-time data that is being retrieved from online monitoring devices. This presentation will touch upon the emerging field of analytics that can be applied to this data, including machine learning techniques, in order to detect specific signatures within the data that can be correlated to specific failure modes. Robust APM frameworks are able to leverage this near-real-time data for the purposes of delivering dynamic health index results based upon the newest readings, as well as operational alerts that can detect possible failures that will occur in the next few weeks or months, providing organizations with enough time to take action. For complex substation assets, an APM solution can allow plant managers to manage and mitigate significant risks within their system. This presentation will also present the results from specific case studies, where near-real-time data from field sensors was successfully leveraged and integrated into an APM such that the organization was able to enhance their risk management and asset management decision-making approaches.

ESG targets and reporting are becoming increasingly important. Investors and governments around the world are pushing for transparency and ever more rigorous reporting on ESG indicators. It is likely that financial regulators in North America will make ESG reporting mandatory within the next 2 years.  Many components of ESG frameworks affect asset management, and conversely good asset management can help improve an organization’s ESG scores. Think of climate change, pollution, health & safety, risk management, water use and GHG emissions to name a few.  It is therefore crucial for asset managers to understand the current frenzy around ESG reporting. Yet the ESG ecosystem can be quite baffling: there is no single definition of what ESG stands for, or what is “in” or “out”, or what reporting standard to follow.This presentation will shed some light on who does what in the ESG ecosystem, what standards and reporting options are available, and how all this will increasingly affect the way organizations make strategic decisions. Asset management has a big role to play in this context. Many asset managers have been confronted with complex, multi-stakeholder decision-making frameworks for years and are quite adept at aligning various departments to a common set of objectives. The definition of “value” in asset management often already contains many metrics that are now part of ESG reporting. We will explore how robust value frameworks can help organizations reach better decisions and improve their ESG scores – with the guidance of their asset management team!

The cost of an error depends on where you catch it. In DfR programs, the design phase is a good place to start.          Interview with ; Marie Getsug, PMP, CAMA, CMRP, CRL, CPIP | Jacobs | Program Manager            This article was originally published on MachineDesign.com.

2020 was a very different and transformative year for all industries due to the pandemic and mining was not an exception; one of the important challenges for the Kinross’ corporate team was to provide support from the headquarters in Toronto without the capability of travelling to sites; among the different corporate functions, the Maintenance team is responsible for leading the identification; application and effective implementation of practices aiming to the continuous improvement and evolution of Maintenance in order to better position the function globally towards asset management optimization Kinross Gold is a senior gold mining company Headquartered in Toronto with a diverse portfolio of mines and projects in the United States, Brazil, Chile, Ghana, Mauritania, and Russia. The proposed paper and related presentation will explain how the Corporate Maintenance group had to adapt and evolve in order to provide meaningful support to sites in spite of the impossibility of traveling and work side by side with our site based counterparts; in particular the presentation will focus on describing: - Initial failures and struggles in the adaptation process - New streams of support that were developed to overcome the mobilization challenge - How the maintenance corporate changed for good due to the new way of working - The overall performance of the maintenance function globally - The challenges that remains and new barriers expected for the future The proposed paper is simply an effort to share our experiences with the hope that the Asset Management community globally considers these lessons and benefit from them on their own quest for excellence

ARMS Reliability was engaged by a client to vet its design for an extension of its oil facility with special focus on the diluent recovery unit performance. The facility had capacity to load and ship approximately 100,000 barrels of oil per day and were looking to increase the capacity to 120,000 bbls/d with the addition of a DRU. In order to meet capacity goals, ARMS Reliability assisted in building a Reliability Block Diagram (RBD) remotely using failure data from previous RBDs equipment types with similar operating contexts and assigning failure models using RBDs from other sites and the ARMS Component Strategy Library. Since design choices were not finalized at the time of build, multiple scenarios were simulated using existing VRU packages from other sites and data on reliability performance of previously modeled equipment at other terminals.This case-study presentation will discuss how a Reliability Block Diagram helped our clients:• understand expected performance of current and potential design choices• enable cost-benefit-analysis to determine what changes need to be incorporated for top contributors• target optimized strategies against top contributors to availability and capacity losses• quantify the best-case impact of process cleaning activities to inform their cleaning intervals and condition monitoring methods

Reliability Engineering uses a modelling approach specifically known as Reliability Block Diagrams (RBD) to asses all the characteristics of an asset during its life. The output of this exercise is a dynamic model illustrating different decision-making elements of the asset being studied. This includes economical aspects such as operating costs, spare part management, expected failures and other maintenance outcomes over time. This information allows and operator to correctly budget costs, logistics or labour requirements over the life of the asset. The model also allows the designer to estimate the production output of the asset over time and have a more realistic view of the design output. When it comes to preventive maintenance or redundancy (i.e. adding extra equipment), the model can be altered to visualize the expected output and incremental economical benefits or lack of there off, leading to better decision in terms of capital spending. The author will illustrate the study of a centrifugal pump and help the audience visualize all the above-mentioned aspects.Originally presented at MainTrain 2021 

Picture yourself driving to work on a cold, dark, winter morning. It’s Monday. You pull into the parking lot and note with surprise that the plant is much quieter than it should be on a Monday morning. As you walk inside to your office, your growing apprehension turns into the sudden realization that something serious must have happened over the weekend…Whether you work in a manufacturing facility, a continuous production facility, a hospital or building infrastructure, the need to prevent failures from reoccurring is familiar. So how is this accomplished? By applying root cause analysis methodology. Root Cause Analysis Made Simple covers the four fundamental steps to RCA. Quantify the magnitude of the problem – Why? When? Perform the analysis using the appropriate technique – Who? How? Develop a list of options for solving the problem Document the results and implement recommended actions This book provides an overview of RCA. It is intended to support you in understanding the business impact of preventing reoccurring failures and provide some tried-and-true practical approaches to conducting a root cause analysis.

Reliability Centered Maintenance – Reengineered: Practical Optimization of the RCM Process with RCM-R® 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® 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.Includes extensive review of the well proven RCM method and what is needed to make it successful in the industrial environmentLinks important elements of the RCM method with relevant International Standards for risk management and failure managementEnhances RCM with increased emphasis on statistical analysis, bringing it squarely into the realm of Evidence Based Asset ManagementIncludes extensive, experience based advice on implementing and sustaining RCM based failure management programs 

Let us look at an ordinary omnipresent part of Asset Management: bolting and fastening the machinery or structure. This single vital activity turns out to be remarkably neglected with undesirable consequences for reliability. Motion Amplification®, a new technology has the capacity to show machinery and structural movements, and so naturally brings out looseness or unnatural behaviors. Fastening errors seem to be one of the most prevalent occurrences and it is therefore important to look at what we can learn and how the technology can drive improvements and uses of best practices. A variety of problems are shown, such as forgotten difficult to access bolts, rusted/corroded fasteners, improper tension, improper washers, bolt grade or size and custom modifications such as a bunch of small shims. Some of the issues can be attributed to design errors, some to lack of asset information provided, some to installation errors, lack of training and proper tools or a culture of installation and maintenance excellence. Sometimes and improvement push comes with the integration of more advanced tools, for example tools exist where the torque can be properly managed. This requires that many other items come into place, such as the missing information, correct parts, training and cultural to get the job done properly.

Not knowing what you do not know can be very dangerous for an organization. With unfortunate events that led to injuries at competitor’s facilities, Skeena Bioenergy activated a safety review of all equipment using bowtie analysis and a risk matrix. Bowtie analysis identifies causes and preventative action to stop a defined event from occurring. Then, looks at loss prevention actions to prevent disastrous consequences that stem for the described event. The risk matrix is a chart that has frequency of occurrence on the vertical plain and the consequence of severity on the horizontal plane. When combined, gives a risk level number, colour coded, that identifies levels of acceptable and unacceptable risk. This application was successful in identifying that the design of the Cooler, one part of the process, does prevent fires and explosions. Further fire control measures identified will be added; 1. to improve containment of a fire so it remains in the Cooler and 2. to prevent a fire event from cascading into an explosion. These continuous improvements in the Cooler reduce the risk level to 3, Skeena Bioenergy’s acceptable level of risk. This abstract demonstrates the application and findings of applying bowtie analysis and a risk matrix to a piece of equipment, the basis of good risk management.