3.2 Performance Measurement & Optimization

Most organisations have implemented processes and tools to collect data to facilitate informed decision-making. Often, they will seek out best practices and measures to assist in decisionmaking or rely on technology to guide the basis of decisions. However, in many cases these same organisations approach a gap in tactical deployment and the ability to draw a connection to the follow-up or pre-emptive actions required to derive value from assets. This presentation will review the processes for establishing a framework for alignment and priority setting, while looking at the techniques employed for resiliency and risk management using a technology agnostic approach. We will review potential data sources which can be leveraged for decision-making and which reflect the needs and current state of the business environment. Further, we will discuss the relationship and application to the decision-making process. An overview of the fundamental outcome of key performance indicators and visualized metrics will be demonstrated. Finally, we will investigate the influence on decision making and the level of data confidence.

With all the talk about big data and the IIoT, many are asking how can we use this in maintenance? The IIoT enables us to put sensors in any location where we might want to collect and analyze equipment condition and performance data. There are companies that offer predictive maintenance services, and some companies do this for themselves, in-house. Typically, it’s the larger companies that can afford this, but democratization has meant this has become available to a much broader market. But there are hurdles to taking advantage of this sort of continuous monitoring program, even for your most critical equipment. One, it’s expensive, whether you do it in-house or outsource. And two, there are data bottlenecks. Condition monitoring data comes is huge volumes and it’s all time-sensitive. Even if you can afford it, you need a data handling network with a lot of capacity. In this workshop, we’ll present a viable technical solution to the data bottleneck problem — based on a solution already proven in financial securities markets — that opens up these possibilities in the realm of plant continuous condition monitoring.

Asset condition management (ACM) teaches on-condition monitoring for any business with high-capital assets looking to harness machine learning to avoid unexpected failures and control rising equipment maintenance costs. Many businesses are already using continuous condition monitoring technologies like IoT-connected devices. However, beyond simple threshold alerts from condition sensors, extracting real value from the data generated by these sensors for true predictive monitoring requires expert analysis and interpretation. To generate actionable results from condition sensor data, these experts also apply knowledge about the asset’s operation. This limits the value that IoT-enabled ACM can provide to the business. By taking the next step and using advanced algorithms and machine learning to automatically extract real-time insights that drive action, we can now achieve the full potential of ACM. Modern, cognitive online ACM takes data from multiple and varied sources, combines it, and uses AI and machine learning techniques to anticipate equipment failure before it happens. Many reliability professionals recognize the potential of IoT, machine learning, and AI, and are trying to learn these technologies. However, the available training is complex and assumes learners have a background in data science and computer programming. This workshop will provide a beginners’ level understanding of terminology, basic concepts, and techniques to determine how and where you can apply AI in your facilities for meaningful ACM.

Many organizations have embarked on asset management programs and struggle to implement best in class practices, find it difficult to sustain the new ways of working and find it difficult to demonstrate the return on the investment in AM.  Success in Asset Management (AM)  Development and Sustenance of the AM Program depends of effective Change Leadership throughout the program. It requires a focus on the following areas:1. Program and Steering Team Charters2. Comprehensive Business Case3. Comprehensive Project Management  Plan4. An AM Framework and Policy that provides a clear vision for AM5. A Leading Change Plan (and an effective issue management process)6. Communications Plan7. Tracking and Reporting of BenefitsThis presentation will provide practical guidance to people who are embarking on an AM Program, in the throes of implementing one or trying to sustain the new way of working. Participants will hear abut real case studies where challenges in the areas listed above were successfully managed.

Maintenance activities have a direct effect on the environment that surround the facility where they are executed. There are three aspects in which maintenance strategies contribute to a facility foot print in the environment: 1) Resources needed 2) Efficiency of the equipment 3) Waste introduced into the ambient as part of maintenance activities. In order to be a sustainable maintenance department, the first and third aspects must be reduced or closely controlled and aspect two should be maximized.There are a number of techniques and actions ready to help us achieve asset efficiency and reliability but the real question is, if we are willing to commit to be environmentally responsible in our maintenance activities; do we understand the environmental impact of keeping our assets reliable?Join this session for a lively conversation about how making cultural changes, all the way to adapting new technologies, organizations can start making changes that will endure economical trending, while positively impacting all our surroundings.

Reliability Block Diagrams (RBD) help organizations achieve new project goals which makes them an especially important tool under the restriction of budget and production cuts that are currently typical due to economic constraints such as low oil prices. At design stages and under new budget cuts, management should consider a few things besides meeting the projects budget like: New plant capacity expected; Plant overall reliability and availability; Operating risks; and Projected maintenance costs. Participants will see that by building an RBD the project team will have a document that will help in the decision making while supporting both in production and economic terms a decision. 

Asset Management is on the minds of many decisions makers as they struggle to maximize the investment of their assets. This session will provide some key insights along the AM journey and provide attendees with ideas about on how they can develop their own AM Roadmap to get to their destination of maximizing their asset investment. As well, learn about the new AM rules that should be applied in the face of new and emerging business drivers such as AM policy, vision, strategy and framework, as well as business process and maintenance effectiveness, and risk management.

In his keynote presentation, Alex will explore the various stages of asset life and the decisions which must be made in each, as well as discuss the meaning of whole life asset management. You will also be introduced to modern methods of cost/risk evaluation and optimization; and see some practical approaches to whole life cycle asset management and how this impacts maintenance and reliability. Alex will explore maintenance and reliability in the context of your organization and challenge maintenance and reliability professionals to consider alternative approaches.