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Asset Performance Management (APM) is an approach to managing assets that prioritizes business objectives in addition to traditional asset reliability and availability goals. APM has become a primary enabler of digital transformation for asset management among industrial companies. Modern APM combines traditional asset management practices with new digital technologies for transformation advances in reliability, maintenance execution, and business performance.
Business goals: Through digital transformation in asset and risk management, and improvements in asset availability and uptime, users achieve higher revenue and profitability while improving customer satisfaction with on-time delivery and quality.- Asset ecosystem: The ecosystem for assets extends beyond the plant floor and facilities to include a wide range of applications across asset-intensive industries that leverage sophisticated OT, IT and engineering systems and related production, maintenance, and engineering personnel. It also encompasses third party partners and other providers of parts and services.
- Digital tools: Apply modern technologies across a range of tools like smart devices, augmented reality, and mobility to improve business processes and create new methods for asset management.
- Data & analysis: Enable greater depth of collaboration across the asset ecosystem by using digital twin, digital thread, and other modern information assimilation and management approaches.
- Practices and apps: Traditional practices and applications become more effective when enhanced with data, digital tools, and support for business goals.
Asset Performance Management (APM) Business Benefits
APM involves people, processes, and technologies to improve the uptime with higher revenue and longevity of physical assets to conserve cash while reducing operating costs and business risk. APM helps assure assets have the needed capability for optimal operating performance to meet today’s dynamic business and production goals with high customer satisfaction for on-time delivery and product quality. This APM approach becomes a means to systematically improve key metrics like uptime, mean time to repair (MTTR), asset longevity, on-time shipments, quality/yield, and safety. Success with these metrics leads to improvements in executive metrics like revenue, margin, customer satisfaction, work-in-process (WIP) inventory, and return on assets (ROA).
APM Drives Successful Asset Management
APM improves the reliability and availability of physical assets by synchronizing the asset lifecycle management functions including reliability, maintenance, inspections, and information management. APM acts to optimize the performance of physical assets in their operating ecosystem, typically employing a digital thread throughout the asset lifecycle, supporting digital twins for assets and asset groups, supporting connected workers, and the network of parts and service providers.
Proactive Asset Performance Management with IIoT and Analytics
The Industrial Internet of Things (IIoT) with advanced analytics, offers new opportunities to improve the reliability of industrial assets, enabling owner-operators to progress toward no unplanned downtime, which many consider to be the ultimate objective for maintenance and operations.
Preventive maintenance assumes a failure pattern that increases with age or use. Unfortunately, this applies to only 18 percent of assets. The other 82 percent of assets display a random failure pattern. In contrast, predictive maintenance (PdM) approaches employ near real-time equipment and process data to predict failure. PdM combines multiple data sources with analytics to predict failure with a higher degree of confidence and low false positives.
Typical benefits of proactive maintenance include improved uptime, asset longevity, maintenance cost control, and safety. Industrial organizations should review their asset management strategy and consider increased adoption of condition monitoring and predictive maintenance solutions. ARC Advisory Group recommends that users consider a pilot project for proactive maintenance with analytics – especially for complex assets or a common asset type.
Comparing Maintenance Strategies and Approaches
Combining IoT with analytics and automated business process enables new, higher levels of maintenance effectiveness and maturity. IoT allows organizations to reduce data quality issues associated with manual inspections and move to automated data collection. This vastly improves data quantity and integrity, enabling new maintenance strategies. ARC classifies maintenance maturity into five types or levels: reactive, preventive, condition-based, predictive, and prescriptive.
|
Strategy |
Description |
Asset Attributes |
Car Analogy |
|
Reactive |
Run to failure, and then repair |
Failure is unlikely, easily fixed/replaced, or non-critical |
Radio |
|
Preventive |
Service in a fixed time or cycle interval |
Probability of failure increases with asset use or time |
Replace engine oil every 5,000 miles |
|
Condition Monitoring |
Alerts for bad trends or other rules-based logic using a single data value |
Assets where a component failure cascades into big $ losses |
Oil pressure, coolant temperature indicators |
| Predictive (PdM) | Equipment specific algorithms or machine learning. Multivariable | Critical assets where unplanned downtime has business impact | Battery Management System in electric cars |
|
Prescriptive |
Model and knowledgebase identifies an issue and what to do for repair |
Complex assets requiring advanced skills |
Dealership-level diagnostic equipment |
ARC Coverage Areas
ARC Coverage Areas