03 Asset Strategy Management

The Global Forum on Maintenance & Asset Management and highlights of the second edition of it’s recently published Maintenance Framework, including the project to develop the document and differences from the first edition.

L'objectif de ce webinaire, sera un partage d'un récent mandat chez un client minier ou ils ont fait l'évaluation de la maturité de la gestion de maintenance. Le webinaire couvrira également les découvertes et nos actions pour l'améliorer.Agenda de la présentation:- Contexte opérationnel- Évaluation (analyse de données et temps d'outil)- Découvertes- Action en partenariat- Résultats préliminaires- Les actions prochaines pour fiabiliser les opérations

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.

When a defect occurs in a physical asset, it’s often not immediately detectable by operators. In fact, in some cases the defects are not visible to the naked eye. However, from the moment a defect occurs until it is found, there is a risk that the defect will grow in severity, and possibly transition into a failure, resulting in reduced or halted production. At a municipal transit company, the Nondestructive Testing (NDT) team uses specialized equipment to inspect the train tracks and identify the location and severity of any defects. Due to the limited hours during which the team can perform their work, the whole subway system can only be tested once per year. Using their data on train tracks and found defects, we investigate efficient ways to use the NDT team’s fixed resources in order to improve the reliability of the train track system.

The Northwest Territories has 33 geographically dispersed communities, many of which are not grid connected for community power supply. The majority are powered by small, local diesel plants with others supplied by three hydro systems which generate the majority of the total power produced annually by the Northwest Territories Power Corporation (NTPC). This paper will describe how the condition of these assets is assessed and monitored, the process used and how the results form part of the annual capital planning and implementation process. Asset management at NTPC is divided into Thermal, Hydro and Transmission and Distribution; the focus of this paper will be primarily on thermal and hydro asset health inspections. On an annual basis, one third of the assets are inspected in person by the relevant asset manager and a small team of subject matter experts. The process by which these inspections are conducted will be outlined, including what information is gathered, and what we look for when carrying out the inspections. The asset condition information for various component parts is entered into one spreadsheet for each asset. The paper will describe how an asset health index for that asset is assigned. The condition of the asset determines what further action or inspections are required and the criteria used will be discussed. The presentation will also outline how the results from the inspections are used as part of a project prioritization process for capital planning. Current reporting practices on individual asset health indices and for each power plant will be described. In discussing this topic, NTPC sees an opportunity to receive feedback from others and to promote discussion on best practice from other power utility companies.

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

2020 was a challenging year for everyone, but in our facility, we were able to sustain the site reliability through the successful implementation of Total Productive Maintenance. Total Productive Maintenance allowed us to minimize equipment downtime throughout the year through the combination of keeping equipment in its base condition and producing clear operational and maintenance triggers to catch problems before they become in-process failures. The talk will go through the initial implementation phase (pre-lockdown) and how we navigated through internal and external challenges in 2020 to sustain the TPM and Reliability activities.

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.

The Maintenance management Framework is intended to be used by members of the GFMAM, the Maintenance and Asset Management communities to:   Provide an overview of the discipline of maintenance management;   Provide a structure for the building of a body of knowledge for certification schemes and qualifications in maintenance management;   Provide a structure (and potentially the criteria) for assessing an organization’s maturity in maintenance management;   Provide information for maintenance management knowledge requirements for assessors and auditors;    Provide the capability to compare the products and services of the different GFMAM members related to maintenance management; andProvide a reference for future GFMAM projects.