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
Ashley is a Senior Engineer with ENMAX Energy Corporation and has over 18 years of Reliability Engineering experience in Petro‐chemical, Fertilizer and Power Generation. He is currently responsible for leading reliability engineering programs and initiatives for the generating assets, establishing "road maps" for various reliability initiatives and implementing reliability procedures at the plants. His current initiatives include developing and creating an internal Health Index for critical assets, creating a road map for the implementation of AWARE program for stationary mechanical equipment and leading an Availability study for the District Energy plant. Prior to joining ENMAX, he has worked in various reliability engineering roles with Nova Chemicals, Agrium and TransAlta. He has led engineers and technicians to meet plant reliability objectives and promote reliability culture within plants to improve overall effectiveness. Ashley is a Mechanical Engineer from National Institute of Technology, Calicut, India and is a registered Professional Engineer with APEGA. He also holds a CMRP designation. He spends his spare time with family, travelling and playing soccer.
