Asset Performance Management: Focus, Direction, and Optimization for Reliability and Maintenance
Proper plant asset management is an integral part of achieving organizational goals. In addition to improving productivity, asset management is also an important DX theme for Yokogawa customers worldwide. During the COVID-19, customers are looking for more data-driven asset management solutions. Yokogawa can help our customers improve asset utilization and optimize maintenance costs by providing solutions to integrate asset-related data, and by formulating and executing maintenance strategies based on risk assessment of plant assets.
All process plant equipment and components—such as pumps, vessels, motors, valves, instruments, and controllers—must work seamlessly together for a unit to produce product effectively and profitably. Managing the performance of each of these assets can be a very difficult task, but solutions are at hand.
Plant managers and reliability teams have benefitted from developments in asset performance management (APM), often as part of larger digital transformation (DX) efforts. These smart manufacturing platforms collect performance and condition data from smart devices and monitoring instruments using IIoT-based networks, following balanced concepts outlined in the ISO 55000 Asset Management standard.
This data supports evaluation and decision making on multiple levels:
Is the asset performing its functions consistent with general expectations (CAPEX)?
Are its ongoing lifecycle costs (OPEX) on budget?
Does its diagnostic information promise continued reliable operation, avoiding risk of production outages, or are problems developing?
For many facilities, the most visible use of APM is the last item, helping identify which plant assets are developing problems before escalating to an outright failure. This helps avoid unscheduled outages and optimizes equipment maintenance/care programs, while ensuring ongoing risk management.
Using APM and computerized maintenance management system (CMMS) tools, maintenance teams can prioritize activities, working on equipment that needs it most and carries the highest risk to the process, while deferring maintenance on items not requiring attention. This is much more efficient than the traditional approach of preventive maintenance based on calendar or operating hours, and is of course a major improvement compared to a run-to-failure approach with opportunity to cut maintenance costs by up to 40%. Limiting work to assets requiring attention also minimizes the likelihood of wasting scarce resources on efforts that yield only minor or no improvements.
Asset management strategy
ISO 55000 goes well beyond maintenance, as important as it is. APM is a coordinated process to maintain the delicate balance across risks, costs, and desired performance through an asset’s lifecycle. APM calls for constant evaluation of the three points mentioned earlier to ensure an operation is realizing the full value of its investment, the asset is fulfilling its intended purpose, and its costs and performance are meeting expectations.
APM helps prioritize investments (CAPEX) by verifying an asset investment strategy is aligned with organizational goals and plant KPIs. This extends to asset performance over time in terms of basic output in whatever form it’s measured, weighed against repair and replacement costs. Such strategies are operationalized in the CMMS, guiding all maintenance efforts.
Optimizing planning to control costs
The economic impacts of COVID-19 have been felt in all process industries, hampering personnel availability, while often cutting CAPEX and OPEX budgets. Whatever resources were available pre-pandemic, there are fewer now. Fortunately, asset management has evolved, and digitalized monitoring and maintenance planning now makes it possible to do more with less. Silos and divisions among areas can be broken down, increasing the versatility and range of skills of each individual.
In times past, most plants had at least a few experienced, skilled technicians who had been there long enough to have a sense of how things were running and what might need fixing. This old-school system worked much of the time, but it was not very efficient, and there were no provisions for knowledge transfer.
Today, performance and reliability monitoring can be linked with maintenance planning using APM. These are data-driven evaluation processes, performed in light of risk management.
For example, a centrifugal pump installation has power monitors to ensure it is performing efficiently. It also has vibration sensors to recognize when bearings are failing or the motor has drifted out of alignment. The risk to production of that pump failing is well understood, so maintenance can place it on the list of things to do in an appropriate position reflecting the needs of the process. All maintenance activity and resources can be regulated and optimized by the balance of condition data and risk.
Beyond real-time monitoring, machine learning (ML) and artificial intelligence (AI) capabilities provide a mechanism to look at unit history and recognize conditions tending to create or forecast problematic situations, even before instruments and detectors begin to see the effects. Peculiar vibrations created at specific operating rates, or the effects of process upsets, may take their toll on equipment at a rate not detectable by manual and other means. ML and AI can recognize associations and point to developing problems, long before symptoms appear.
Making the transition
Any facility still using the old-school approach is paying the price in poor maintenance efficiency, excess costs and at the same time experiencing less than ideal reliability. Now is the time to make the change to digitalized APM. While technology is part of the solution, it is not where the process begins.
With Yokogawa, the first step is determining where your company is, and then clarifying specific business needs and challenges, since every situation is different. We create a plan and program to achieve your desired asset performance and reliability levels, but with enough flexibility to adjust as the situation evolves going forward.
The transition takes incremental steps so it can be digested internally by the existing workforce. As each improvement brings visible and tangible value, it supports buy-in at all levels. Success builds over time to the point where the program covers all areas in a plantwide asset management (PAM) program using integrated condition-based monitoring, with dashboards for organizational goals and KPIs.
Implementation does not require much in the way of new server hardware and related computing infrastructure because the system can be hosted in the cloud, ensuring a high level of data availability, with proper cybersecurity safeguards in place.
When deployed properly, asset management solutions within larger DX and IIoT programs save money, reduce risk and improve plant performance. Routine maintenance and turnaround costs frequently drop by up to 25%. These programs deliver on these promises by supporting data-driven, risk-based decision making—building toward true autonomous operations using optimized asset strategies and the best mix of digital technologies.
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