What is asset reliability transformation?
Asset reliability transformation takes into consideration the acquisition, operation, maintenance, and complete useful life of every industrial asset. The entire transformation journey can be mapped in the following steps:
Acquisition:
At the very first stage of asset acquisition, it is critical to determine whether the asset is designed and built for reliable performance or not. Furthermore, once acquired, the asset should improve the net plant reliability, integrating with the existing infrastructure and asset ecosystem. These prerequisites can be featured in every project plan along with standard regulation and acceptance tests that are performed at the time of new asset acquisition.
Discipline:
Once an asset has been installed and started functioning, the operation teams start focusing on asset control. This includes defining the workflows, planning, and scheduling asset utilization, determination of precision work conditions, and adopting CMMS (Computerized Maintenance Management Systems). Factoring in the standard wear of components, spare management must also be an important driver to ensure continued asset reliability.
Care:
Meticulous asset care directly contributes towards improved asset reliability. From adoption of standard operating procedures to a strategic maintenance approach; asset care includes cleaning, lubrication management, equipment calibration, and maintenance management, spares inventory, and operator care. Moving away from reactive and preventive maintenance to adopt more advanced prescriptive and predictive maintenance models can lay a foundation for more available and reliable assets.
Analytics:
For effective analytics to happen and provide business intelligence, processes and tools need to be in place for capturing relevant information. Key metrics to monitor and measure performance needs to be identified and regularly tracked. With AI and IoT-enabled solutions, predictive analytics can be used to diagnose hidden failures, minimize the risk of asset breakdown, and drive reliability objectives.
Optimization:
Asset optimization requires constant monitoring of machine health while assessing risks, challenges, and opportunities for driving reliability objectives. OEE (Overall Equipment Effectiveness) forms the premise for ensuring asset reliability, which can strategically build toward total plant reliability.
End Of Life (EOL):
Ultimately, End of Life management for all plant assets is also essential for maintaining sustainable production practices and pursuing reliability in a responsible manner. Before spares are installed or assets are replaced completely, performing root cause analysis for failure and capturing breakdown circumstances is critical. Information captured at this stage should serve as insights for managing new assets. Disposal standards for assets must also conform to regulatory norms.
The maintenance perspective in asset reliability transformation
Among these six steps of the asset reliability transformation journey; the maintenance perspective is clearly captured in the ‘discipline’ and ‘care’ of assets. Assets that are cared for and maintained in optimal working conditions are less likely to fail or break down. At the same time, digitalized monitoring mechanisms allow for safer and more effective maintenance strategies.
Advanced predictive maintenance and digital reliability solutions can empower plant operation teams to build a connected enterprise that has a mine of asset intelligence. With the right information accessible and analyzed for generating meaningful insights, maintenance teams can lead the reliability transformation wave.
- Visibility of all assets can be optimized with cloud and IoT-enabled technologies, and can capture asset data 24×7
- Asset performance, condition, and need for intervention can be monitored in real-time with minimal human intervention
- Plant-wide data can be predictively analyzed to plan and schedule maintenance events
- Asset cleaning, lubrication, and maintenance can be strategically planned for minimal disruption in production schedules
- Spares management can be streamlined and optimized by realizing the complete remaining life of assets and avoiding preventive part replacements
- Key metrics such as MTTR (Mean Time To Repair), and Mean Time Between Failure (MTBF) can guide maintenance planning, making equipment more reliable and available
- Root cause failure analysis and predictive analytics can provide helpful insights to guide asset acquisition and management
In sum, while asset reliability is a larger goal driving manufacturing leaders to look beyond asset management, it is rooted in asset maintenance and optimization through smart technologies. Acquiring assets that are built for reliable performance, caring for them, and optimizing their performance with intelligent interventions can drive reliability transformation. And predictive maintenance remains at the heart of it all.
Infinite Uptime’s digital reliability solutions are tailored to assist plant reliability teams in undergoing an effective asset reliability transformation. IoT-enabled asset health monitoring and predictive analytics are shared with plant leaders in industries such as Cement, Steel, Mining, Automotive, Tyre, Chemicals, Paper, FMCG, Pharmaceuticals, Glass, Oil & Gas, etc. Our patented vibration analysis technology and syndicated reliability reports allow maintenance leaders to maximize their plant reliability and minimize production downtime.
To know more about maintenance Perspective:
https://www.infinite-uptime.com/asset-reliability-transformation-the-maintenance-perspective/
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