10 Continuous Improvement

Artificial Intelligence (AI) technology is developing rapidly and is appearing more and more often in asset intensive organizations. It is both a Threat and Opportunity. To some it is a tool for making better or faster decisions; and on systems where the output is king that could be a driving factor. For others, it is another layer of fog hiding decision making processes. Evolution of this technology is moving much faster than regulation, and in an unregulated space within a capitalist economy, where AI can provide a commercial advantage it will be used and advanced. How is AI being used in asset intensive organizations today, what could tomorrow look like? What skills and knowledge should Asset Management Professionals be investing in to work in a world with fast evolving AI systems?

According to GFMAM Landscape, the performance of asset-intensive organizations is dependent on the quality and availability of asset data and information. So why does research indicate that 70% of plant operators report 33% to 50% of their asset and process safety information is either missing, incomplete, inconsistent, or outdated? Common complaints from maintenance planners, reliability engineers, facility engineering, process safety and compliance managers include the following: “We can’t find it,” “It’s not complete,” and “We don’t trust it.” As a result, personnel continually make safety, engineering, financial, capital, maintenance, and operational decisions without full access to complete, consistent, and up-to-date information. Such decisions are suboptimal and can cause significant loss. We call this value leakage. Have you ever wondered how much value leakage is costing your organization? Why do the underlying causes of value leakage persist, and what can you do about it? In this presentation, we examine the root causes of value leakage—from incomplete project information handover, to a lack of standards and processes. We then explore a successful framework to improve AIM, including building the business case and return on investment (ROI). Attendees of this presentation will learn how to identify value leakage and the underlying causes; how to calculate the ROI (qualitative and quantitative) of improving asset information management to reduce value leakage; and quick wins and long-term strategies for improving asset information management.

In this session, we will look at the professional development pathways available from institutions and educational bodies from around the world. Special guest Dave Daines will look in detail at the professional development pathways the WPiAM can offer individuals and organizations, both now and in the future, through the GCS. Susan Lubell will discuss PEMAC’s approach to certifications, how they align to the GCS, and the many benefits to our PEMAC members as individuals and the organizations that employ them of hiring certified asset management, maintenance, and reliability professionals. Specific content will focus on MMP, CAMP, CSAM, CPAM, CTAM, and CAMA, as well as career development, transportability, transferability, and rigorous process for evaluation.

Cameco Corp. has recently deployed approximately 1,500 wireless asset condition monitoring sensors across four of its operations. This presentation will explore all aspects of this project, from initial identification of business pain, all the way through to deployment and management of the system. Condition-based monitoring of rotating assets typically involves a route that is executed at a fixed interval to collect asset condition data. This data can include vibration, temperature, acoustic emissions, and others. This data is then downloaded into software and analyzed for faults and trends. This method has many shortcomings that can be solved with remote sensing technology. This presentation will take you through Cameco’s journey of identifying the limitations of traditional data collection and why an alternative was investigated. Some of the key topics will include problems and inefficiencies with the current system, methodology used to determine which sensor company to partner with, potential cost savings and benefits, deployment strategy and execution, and some screen captures of actual asset detections. Finally, we will conclude with lessons learned and benefits realized from deploying a sensor solution.

An Intelligent machine can sense its environment, take a decision and apply an action or give a recommendation. How this can transform maintenance? With every Industrial Revolution, Maintenance tools and strategies grow to provide the needed service for this industrial era. Now what shall we do with the Augmented reality and other technologies that Industry 4.0 introduces in the production environment??! It is important to understand what AI -Artificial Intelligence in details is because it is currently part of our work and life even if we do not realize this. When we understand how AI works, we can use it as our ally. Otherwise, we shall resist its existence specially when it starts to give recommendations and report of what went good and what went bad. AI is a title frequently applied to the project of developing systems with the intellectual similar to those of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. The human maintenance team applies its intellectual process at every situation it encounters. This intellectual process includes the ability to reason, discover meaning, generalize, or learn from experience. How AI does this? It is all based on software and Algorithms. There are two (2) ways for the software to yield intelligent advices or actions. You either add to it all the possible solutions of a problem and the software searches through all possibilities to find a one matching to this situation, then returns the stored actions for this possibility. Alternatively, the other way is to let the algorithms of the intelligent software infer some reasoning based on the inputs then solve the problem. . Let us relate this to maintenance

The Regional Municipality of Durham is a community that makes up the east end of the Greater Toronto Area (GTA), which comprises multiple cities and townships. The region provides a multitude of services to approximately 745,000 residents and maintains $17.85 billion in assets and infrastructure. The region was using several disconnected applications and business processes to manage these services, many of which had limited functionality, reporting, and analytics, as well as a lack of integrations to other systems. In an effort to standardize and streamline these services, the region amalgamated all of the tracking of regional assets, maintenance management, and business technology processes. The region began the process of requirements gathering in 2013; at this time, a steering committee was created to govern the project, and project leads and business subject matter experts were engaged to ensure the product selected met business requirements. In 2015, the region began the procurement process: request for proposal, evaluation, vendor presentation, and negotiations. Maximo was the selected enterprise maintenance management system. Durham used a multi-phased implementation plan—including Planning, Design, Execution, and Closing—which consisted of three go-live dates. This multi-phased approach would span over the course of three years. The initial phase of the project included detailed design, organizational impact analysis, future business process design, future role modifications and development, and multiple-tiered information sessions. The organization identified current operational gaps and business process changes were required. It followed Use Case business processes with some adaptation for operational responsiveness and consistency within the To-Be roles. The business was able to retain current operational practices as much as possible but built in a structured and disciplined approach to maintaining assets. This will influence and impact the quality of analytics and reporting. Through its approach, the region was able to implement a centralized maintenance management system across multiple divisions. This implementation impacted 800 end users across 13 divisions and multiple third-party system integrations. It also performed a readiness assessment of departments, divisions, and areas and organizational, process, and technology criteria. It created a go-live and system support strategy, and monitored system, sustainability, and performance throughout the implementation process.

As maintainers, we know there is a lot of value in what we do. Without our work, plant, and equipment will soon stop and our companies will then go out of business. What we do impacts safety, health, revenues, costs, and company reputation. A dirty little truth about maintenance is that it is only we who work in it, that really know the value of what we do – or do we? We do know our value in qualitative terms, but can we quantify it? Most maintenance can be improved and we know it. We can do things more efficiently, and we can keep things running more reliably. We often know how to do that, but when we want to make those improvements there is no money for them. Why? Most business people know very little about what we do and how it impacts their business. They see maintenance as a repair shop. We fix what breaks. And they know little, or nothing, more. They may know that maintenance represents a significant cost, and they may even know that they can’t get away with cutting it too much. But they do not know the full value of what maintenance can deliver, nor what it takes to deliver it. If you want to make improvements you need a decision-maker, someone with executive-level authority, to back you up. To get that, you will need to explain what value you can deliver, and in terms they can understand. You will need to show them the savings that are possible from doing things more efficiently, and the added revenues that can arise from investment in defining the right work. You will also need to show them how their support is needed to bring operators and the supply chain into the team with you to make those changes happen so that benefits are fully realized. Quantifying value and being simple in how you say it matters.

Presentation highlights the importance and interdependency of three pillars of success (people, processes, and technology) and Cameco’s asset management improvement efforts through each of these, including lessons learned. Audience will learn about the importance of organizational change management, business process management and agile methodologies, some of the technologies supporting asset maintenance and reliability, and its new Asset Management & Reliability Center of Excellence.

Are we converting our data to decisions? What is the state of digital adoption in asset management? What has changed since the onset of Covid? What has stayed the same? Using the DIKW Pyramid as our guide, combined with the experience and insights of our panelists; we will explore best practices in data-informed decision-making. Are we now in a much different place on our digital adoption journey?  

Imagine your production facility as a 1950s pickup truck. It’s functional, but a lack of available parts, new regulatory standards, and an absence of modern sensors and electronics make diagnosing problems and improving performance difficult. Commissioned in 1954, Sherritt International Corporation faces many challenges characteristic of a classic car—challenges that not only include equipment lifecycles, but also human resources, software, workflows, and asset obsolescence. This case study will review the training, business process transformation projects, organizational design changes, and continuous improvement initiatives that Sherritt is implementing to modernize their work management processes. See how optimization of these processes have helped address the challenges presented by an aging site, and learn how projects were prioritized, which initiatives helped build organizational capability and improve performance, and what wasn’t worth the effort.