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In any asset-intensive industry, businesses are pressured to continually improve asset performance and reliability while minimizing costs and ensuring regulatory compliance for e.g. safety. In this environment, optimizing maintenance is critical.

Advance Your Maturity Level Using a Phased Approach

New technologies, such as the Cloud, big data management, complex systems modeling and advanced analytics and concepts, such as the Industrial Internet of Things (IIoT) and Industry 4.0, offer users the ability to strategically plan, forecast and optimize their maintenance. Leveraging these new technologies enables an evolution beyond traditional reactive maintenance and toward proactive maintenance. This is the future of maintenance, operations and asset management, namely Asset Performance Management (APM) 4.0.

The maintenance maturity pyramid helps to visually represent the journey toward more proactive and optimized maintenance execution

APM 4.0 and the Maintenance Maturity Pyramid

With APM 4.0, it’s important to consider the various levels of maintenance, the value of each approach and where those levels fit into a comprehensive maintenance strategy. The maintenance maturity pyramid helps to visually represent the journey toward more proactive and optimized maintenance execution, all of which should be embedded in a solid asset management system, such as the International Organization for Standardization’s ISO55000. Enterprise-wide data management, risk management and mitigation form the foundation for a comprehensive APM strategy.

Figure 1Figure 1: The maintenance maturity pyramid

At the bottom of the maintenance maturity pyramid is the most basic approach, reactive maintenance. Reactive maintenance involves letting an asset run until it fails. This is suitable for noncritical assets that have little to no immediate impact on safety or plant availability and have minimal repair or replacement costs.

The next level of maintenance maturity is preventive maintenance (PM), which is regularly scheduled maintenance implemented in hopes that an asset will not reach the point of failure. The PM strategy prescribes maintenance work to be conducted on a fixed time schedule or based on operational statistics and manufacturer/industry recommendations of good practice. PM can be managed in the enterprise asset management (EAM) program or computerized maintenance management system (CMMS).

Some failure patterns in equipment are not related to aging or usage, but appear to happen stochastically. Hence, condition-based maintenance (CBM) is sometimes recommended. CBM focuses on the physical condition of equipment and how it is operating. It is ideal when measurable parameters are good indicators of impending problems. The condition is typically defined using rule-based logic, where the rule does not change depending on loading, ambient, or operational conditions. If the condition is met, work orders can be automatically generated to help mitigate risk and proactively resolve potential problems.

For more complex and critical assets, a predictive strategy is appropriate. Using predictive maintenance (PdM), organizations are able to move from asking, “Why did that happen?” to “What will happen?” Predictive asset analytics solutions learn an asset’s unique operating profile during all loading, ambient and operational process conditions. Existing sensor data is compared to real-time operating data using advanced analytical modeling techniques to determine and alert upon subtle deviations from expected behavior. Once an issue is identified, root cause analysis and fault diagnostics help the user to determine the significance of the problem and the resulting course of action. These early warning notifications enable users to address issues before they become problems that significantly impact operations.

The implementation of risk-based maintenance involves a comprehensive maintenance strategy that leverages existing data, advanced analytics and simulations, and forecasts to understand the true issues driving asset performance and reliability. By implementing risk-based maintenance, organizations are able to move beyond preventing failure and toward optimizing future performance. In other words, moving from, “What will happen?” to “What should we do?” This moves the asset from being merely a cost center to a major driver of profitability for the business.

Risk-Based Maintenance Benefits

Risk-based maintenance holds numerous benefits for organizations. First, getting the most out of your existing production assets is a key success factor in achieving business objectives. Risk-based solutions allow companies to prioritize asset management by focusing on the assets that need attention. Advanced asset criticality analysis ensures the most important assets receive priority and more rigorous analysis for optimal maintenance. When asset failures occur, root cause analysis enables users to quickly diagnose the cause and take action to eliminate reoccurring incidents. Inventory management quantifies the effect of spare parts to optimize asset management levels.

The second key benefit of risk-based maintenance is strategic. By practicing a future-focused, risk-based asset management strategy, users can perform detailed analysis and simulations to visualize the effects of deploying different asset management strategies and, ultimately, achieve short-term efficiencies and long-term sustainability. In-depth risk analysis provides detailed insight into the real factors driving asset reliability and performance, thus facilitating long-term planning. Extensive simulation capabilities allow for augmented intelligence, enabling users to see the impact of differing asset management approaches and resulting in an aligned strategic approach to operations and asset management.

One particular question that can be considered one of the largest pain points of asset-intensive industries is: “How do we allocate resources efficiently and fairly between competing short- and long-term commercial, social and environmental interests?” Therefore, it is important to consider the role and impact of accurate financial forecasts, as unexpected shifts in capital expenditures (CAPEX) and operating expenses (OPEX) budgets can derail even the most best-laid asset management plans. Advanced risk-based maintenance tools allow users, including those from different silos, to design, simulate, measure and optimize CAPEX and OPEX assessment plans, ensuring asset management plans accurately reflect the likely financial future. Risk-based maintenance technologies can provide quick time to value; a solution with an extensive library of readily available reliability data can speed up deployment time by up to 90 percent.

Providing Closed Loop Optimization

A comprehensive enterprise APM solution enables an APM 4.0 approach by ensuring maintenance strategies are deployed in the most efficient and effective manner possible. Enterprise APM solutions manage the collection of data from any number of sources, incorporate advanced analytics technology that combines rules-based logic and machine learning, and can trigger actions in the work order system to manage asset lifecycle and maintenance processes. These solutions help maintenance teams, systems engineers, controllers and many others take advantage of the massive amounts of data available today and use it to answer questions and make real-time decisions to maximize asset reliability and performance.

Using enterprise APM, engineers can identify and predict asset failures early on so personnel can spend less time sifting through raw data and spend more time proactively improving plant performance. Integration with advanced workflows facilitates the continuous improvement process, constantly driving improved operational excellence. An open-ended and hardware agnostic solution enables easy integration with existing systems.

APM 4.0 in Action

Innovative companies are reaping the significant benefits of implementing proactive maintenance strategies today. When a major dairy company implemented risk-based maintenance, the results were a 30 percent spare parts cost reduction and a three percent increase in productivity in the first year. The investment paid for itself sevenfold on a yearly basis and the APM implementation also initiated a systemic cultural shift as the existence of extensive data libraries enabled a company-wide culture of risk awareness, asset responsibility and problem ownership.

In an increasingly competitive market, organizations across multiple industries need to be able to take the bold steps necessary to optimize their maintenance strategies and operations. A rigorous, risk-based maintenance solution that can evaluate how cost, risk and performance should be balanced over time to deliver sustainable outcomes isn’t a choice anymore, but a necessity. Implementing APM 4.0 enables the transition to full, risk-based maintenance for improved asset performance, increased asset reliability, reduced risk and, ultimately, maximum return on asset investments.

Alok Pathak

Alok Pathak is Director, Global Consulting Head of Asset Management, Mobility and Analytics for AVEVA. Alok is a consulting and business development executive with over 20 years’ management experience in asset management fields including, asset performance management, enterprise asset management, industrial mobility and predictive.

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