Elliot Robinson assesses the ways that asset performance management can transform businesses through its integration, availability, and safety.

With an estimated size of $14.4 billion, the global asset performance management (APM) market size is only expected to get bigger with a forecast compound annual growth rate of nine per cent, which is predicted to take its size to $37 billion by 2030. APM is an essential tool in monitoring, maintaining, and improving the reliability and availability of physical assets for optimised operational performance. The APM tools primarily focus on predictive maintenance, condition monitoring, reliability centred maintenance and asset integrity management through information sharing and applications integration between maintenance and operations.

With increasing investment in smart factory, industrial internet of things (IIoT) and Industry 4.0, the plant operators are focusing on adopting advanced analytics tools to predict and prevent failures to optimise production lead time and improve the safety of critical assets. These changes are anticipated to contribute toward the growth of the global asset performance management market in the coming years.

APM and field service management

International Data Corporation recently published a new MarketScape report to evaluate APM vendors in the worldwide manufacturing industry. The report found that manufacturing is still maturing as an APM market. Adoption in manufacturing today is highest, primarily, in process sectors such as chemicals, pulp and paper, food and beverage, consumer packaged goods, and metals. In general, with more critical assets in the operation, it is easier to justify the large upfront investment in APM and create a return on that investment.

The connection between APM and field service management will have long term importance. For many discrete manufacturers and original equipment manufacturers, servitisation is a critical component of the overall digital transformation. A provider’s alignment and capabilities to support leveraging APM for servicing products in the field is an important area to assess.

Despite this, integration remains a challenge. One of the biggest difficulties with APM implementation is the integration with adjacent systems that manage transactional data, interdependent workflows in service, maintenance, operations, and co-dependent occupational therapy systems.

Business transformation

Companies who sell and service mission critical equipment (or assets), such as industrial, medical and life science, and test and laboratory equipment, have a unique set of challenges related to ensuring asset uptime, performance, and customer satisfaction. “These types of assets typically have a long lifespan, and the equipment is sold and serviced along with warranties and service contracts,” Mohan Rajagopalan, VP of product marketing at ServiceMax, says. “Over time it becomes necessary to know where the equipment is installed, who serviced it last, the health of the asset, or whether a contract or warranty has expired or is up for renewal.  High performing companies can leverage equipment data to provide a differentiated service experience and revenue generating outcomes. In addition, they can bring data and actions together to ensure safety and compliance controls are met while avoiding unexpected downtime.”

The ability to test and deploy new business models is imperative to a strong business transformation. This all starts with having clarity of the customer level profitability. With service and equipment data, companies can build a single dashboard and business leaders can understand all of the revenue streams a customer provides. They can then work from that understanding to identify potential new revenue sources. The preliminary data can then be used to test new pricing strategies before the public launch. This helps enable the presentation of data driven return of investment, or business case, when it comes time to sell new products and services. This builds trust between the customer and the company and builds a foundation for improved customer satisfaction and higher customer lifetime value.

Innovation in asset management

Volatility in today’s markets is driving innovation across the APM space, demanding new levels of operational excellence and more dynamic approaches to achieve company goals. Energy transition, sustainability initiatives, shortages of skilled personnel, and increasingly complex digital transformation efforts require a deeper reliance on artificial intelligence (AI) and machine learning powered prescriptive maintenance applications to manage asset performance and downtime. This process, known as autonomous reliability, can completely transform preventative measures.

“Predictive alerts and AI powered prescriptive analytics enable early warnings of process and mechanical issues with sufficient lead time to make adjustments and avoid poor production yields and quality, or to evade process induced degradation of mechanical equipment,” Douglas Cooper, director of APM solution management at Aspen Technology, says. “In scenarios where maintenance service is inevitable, it can provide operators enough time to plan safe and environmentally conscious interventions to avoid sudden and sometimes catastrophic breakdowns. Where asset decisions must be made, it can provide analysis of cost and risk of mitigation options, not just on a single asset basis, but concerning any effects on other assets, the production performance costs (plant and enterprise wide), and interactions with logistical events, weather issues, or other factors.”

This approach can be viewed in three layers of defence, these are preventative maintenance, condition based maintenance, and operational mitigation. These layers of defence are built on a foundation of thousands of autonomous agents blanketing the plant and enterprise to continuously monitor, detect, and mitigate potential asset and process risks. This helps prevent unplanned downtime and process disruptions before they become failures.

Preventive maintenance includes regular service such as oil and filter changes, and routine manual inspections, while condition based activities leverage sensor data to identify initial asset performance degradation that if left unattended will lead to failure. Operational mitigation provides the earliest notice of potential issues to assure availability and full performance of all assets by providing total system based risk/cost analysis and protecting against losses in production, quality, yield, and waste. With today’s emphasis on energy transition and carbon emission reduction, it is paramount that enterprise deployments have a flexible solution that can adapt between predicting a compressor surge in a refinery or a potential gearbox failure in a windmill.

Boosting availability and safety

A better level of service can be delivered whilst also reducing operational costs by using IT systems which turn the emphasis away from reactive maintenance and instead shift toward planned maintenance.  Infinis are a renewable energy group, employing approximately 400 people, of whom around 190 are engineers. The business’s generators are fitted with a comprehensive range of sensors that monitor the condition of each component and can generate alarms when predefined thresholds, such as temperature or vibration levels, are reached.  These alarms are managed by supervisory control and data acquisition (SCADA) and building management systems (BMS) systems that relay data to the company’s logistics centre.

The infrastructure the company manages is complex and requires a high level of reactive maintenance. However, sending engineers out to sites at short notice is time consuming and expensive. This is because, until recently, the team at the logistics centre had to use four different systems to co-ordinate their response to an alarm. With up to 1,000 calls coming in from field engineers each day, and 2,000 work orders being generated per week, it became increasingly difficult to keep up with the workload. An exponential moving average integration specialist, Peacock Engineering, were brought in to work with the company to integrate a comprehensive incident management system (IMS).

Integrating alarm systems with asset management

This integrated approach has given a new insight into the root causes of breakdowns, enabling a more predictive approach to planned maintenance. It has also contributed to an improvement in the mean time between breakdowns and a reduction in mean time to repair. “By combining our in-house telemetry skills with Peacock Engineering’s expertise in IBM Maximo, we have been able to create a system that genuinely transforms the way we handle incidents at our sites.” Neil Douglas, head of IT at Infinis, says. Now, when alarms are triggered at one of the company sites, the SCADA and BMS systems send the relevant data to the IMS, which links each alarm to the appropriate asset. The system also now displays all the open work orders that may affect that asset, as well as confirming whether the generator is authorised for a remote restart, or whether it must be restarted manually. If necessary, it also creates a work order and allocates it to an engineer via the Maximo Integration Gateway. A solution that gives Maximo access to advanced job scheduling capabilities. “Our long term relationship with Infinis and intimate understanding of their needs helps us to deliver appropriate technology that does deliver tangible bottom line improvements.” Alan Cambridge, CFO at Peacock Engineering, adds.

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