2.03 Lifecycle Value Realisation

Asset management (AM) is a far-ranging topic and can be very confusing or overwhelming to anyone who is now embarking on a program or trying to take their existing program up a notch. The biggest impact in AM is on the planning side of the AM Framework. Essentially, if you plan well, then you can execute the right activities (capital project, operations, and maintenance tasks) well. Conversely, which is the case with many organizations, there is poor planning but with efficient execution of the work and attendant sub-optimal performance. Excellence in AM requires effective planning in three areas: Growth and Rationalization, Renewal & Replacement, and Operations & Maintenance. This presentation will provide best-in-class concepts for developing these three areas and the return on investment in effective planning, and will be supported by real-life examples.   Originally presented at MainTrain 2020

Many organizations 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 decision-making or rely on technology to guide their basis. In many cases, however, these same organizations approach a gap in tactical deployment and in the ability to draw a connection to the follow-up or pre-emptive actions required to derive value from assets. We'll review the processes for establishing a framework for alignment and priority setting while looking at the techniques used for resiliency and risk management using a technology-agnostic approach. We'll review potential data sources that can be leveraged for decision-making and can reflect the needs and current state of the business environment. Additionally, we'll discuss the relationship and application to the decision-making process.  

Companies are continually faced with competing priorities and limited resources, and, as a result, it's critical to drive value from the business decisions they make. With more focus on asset management principles, these decisions must be justified through demonstrated and quantified value to the business. With complex systems of equipment, such as a pipeline, determining the value of a project or proposed improvement can often be difficult to estimate—especially when considering an asset's lifespan. In such cases, a more systematic, data-driven approach may be required to predict value. RAM models are one such tool that can be used to achieve this. In this case study, we'll look at how RAM models have been developed and used at Enbridge Pipelines to identify and quantify the risks to throughput volume. The models include key equipment and operational events, along with specific throughput impacts and simulated long-range demand forecasts in order to prioritize the risks and focus resources toward capturing the best opportunities. When specific improvement opportunities (e.g., additional equipment sparing) are identified, alternate cases of the model can be created and the results compared to the base case to support decisions and justify projects. We'll explore some of the challenges we encountered during development and highlight examples of how this tool is being used to quantify value, as well as the approach taken to disseminate the information within the organization.

Learn to build a business case for improvements in Maintenance at your operations. You know your maintenance performance can improve, you know the problems you are faced with, you know some of what to do to correct it, you know it will take effort and some investment, and you need to prove it is worth investing in to your senior management / executive branch. To make the case, you need to show what it can save or earn for your business - where you will see the payoff and you need to estimate the cost of the investment. This is a hand's on workshop. Bring your maintenance performance metrics and be ready to work. You will be shown useful benchmarks that can be used and how to use them. Using those and the metrics from your current state you will show the potential benefit of making changes. After working out the potential benefits we will discuss tips for getting support and making your case an easy sell.

-Introduction a la gestion d’actifs véhiculaires-Processus intégré de la gestion d’un parc d’actifs véhiculaires-L’analyse du cycle de vie financier-Performance de l’actif-Questions et conclusions 

The structural configuration of an organizational design is the way work is divided and how it achieves co-ordination among its various work activities around the assets’ lifecycles. An organizational design structure resolves two basic tasks to get work done: dividing up the work into logical units, which enables performance management, and ensuring the work gets done by providing the co-ordination and control of work. In this webcast we’ll look at four models and discuss their advantages and disadvantages and present suitable information on typical roles and responsibilities that will be reflective of the selected model. The goal of asset management (AM) is to ensure that an organization’s staff is always working on the right activities at the right time, for the right reason, and for right cost. The AM governance model is intended to ensure there is effective collaboration and co-ordination to make this happen around all business processes. With the right AM governance model, overall AM program development can be expedited and new ways of working can be quickly integrated into the organization’s AM culture. We’ll provide the actual results from a number of case studies to demonstrate the value of designing and implementing the most appropriate AM governance model for your organization.

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.

While a host of factors influence profitability, maximizing your plant’s production output potential is arguably one of the facility’s greatest opportunities. An Asset Management, Reliability and Maintenance Strategic Plan can guide continuous improvement that’s aligned with bottom-line performance expectations for managing assets and people. This presentation will provide a framework approach for establishing your strategic asset management & reliability plan and the associated business case. Delegates will gain a fundamental understanding of how to establish a baseline: "know where you are," define where you’re going, who needs to be involved, how to measure the program’s progress and results, and what elements are essential for success.

Application of Lean Six Sigma methodology in the optimization of maintenance execution by using data and facts.    As always, equipment maintainability plays an important role in uptime. Besides the reduction of failure rates, the quick recovery from those failures or the successful execution of scheduled activities makes a considerable difference in availability indicators. The application of Lean tools and Six Sigma analysis contributes to the improvement of maintenance execution by applying the 5 steps of Lean Six Sigma methodology (Define, Measure, Analyze, Implement and Control) and using the tools associated with them. This presentation will discuss Lean Six Sigma theory, basic principles of the methodology and case studies showing the use of tools. Case 1 will illustrate the application of Lean Six Sigma in scheduled preventive maintenance for slurry pumps operating in the oil sands industry. Case 2 will examine how the use of Six Sigma analysis reduced the corrosion rate of tubes in a bank of 12 heat exchangers shell and tube type, which heat diluted bitumen upstream of a distillation tower. Both cases emphasize the importance of using data and facts to make decisions, including front end personnel, and the sustainment of implemented solutions. Presented at MainTrain 2017 

This presentation covers the journey at ENMAX Generation of establishing foundations for Asset Management Plans and Lifecycle Asset Management Practices incorporating into the Capital Planning Portfolio Optimization and Budgeting Process. One of the challenges that we are facing today is in bridging the results from  many technology sources occurring at different time continuum into actionable information that can be consistently used across the fleet. This initiative is driving our engineers and consultants to devise a Health Index (HI) for critical assets that can be consistently used across the fleet for similar assets for the prioritization of capital projects.Annual spending on new projects, major maintenance, and sustaining capital require careful consideration, which has led to an increased scrutiny at ENMAX Generation. A data driven and financial model-based decision-making process for Capital Planning and Portfolio Optimization can be significantly improved using asset analytics to provide meaningful insights.The implementation of this involved review of existing business process including current and future state mapping, gap analyses, alignment with Project Management Office (PMO) Stage Gate Process and with Authorization for Expenditure (AFE). It also included a redesign of value measures and modeling to appropriately value projects/investment opportunities. We developed preliminary Health Index based on asset condition, operating age, probability of failure curves, replacement costs/parameters, and consequence of failure and risk levels. This journey has utilized practices by ISO 55000 for data-driven decision making and Value Measures and Value Frameworks in the Capital Planning and Budgeting Process. The results are probabilistic “optimal” replacement dates. We use Reliability Centered Maintenance methodology to manage our plant physical assets. One of the challenges faced today is in integrating technology sources, which is driving our engineers and consultants to devise a Health Index (HI) for critical assets, starting with the high-value assets.In conclusion, a key element of effective data and model-based decision making in Capital Investment and Management Planning relies heavily on predictive asset analytics. For asset analytics to effectively work, we require a lot of meaningful data to populate newly enhanced Capital Budgeting Software (C55). These are used today in C55 to compute the optimal replacement dates.Presented at MainTrain 2017