Categories
Asset Reliability

Asset Reliability Transformation: The Maintenance Perspective

Asset Reliability Transformation:
The Maintenance Perspective

Asset_Reliability_Transformation_The_Maintenance_Perspective_Blog_IU
Persistent volatility in global trade and evolving geo-economic climate have propelled even the more conservative businesses towards digitalization and asset optimization. With better control of production costs and seamless visibility of the supply chain, even the harshest market conditions can be toughed out. As more and more manufacturing leaders come to realize this, asset reliability has taken center stage in Industry 4.0-related technologies and production best practices.

But what does asset reliability mean for operation and maintenance managers? How does the concept translate into viable strategies? In this article, we will discuss asset reliability transformation, how more reliable plants can be built and maintained, and what it would mean for the asset maintenance teams of tomorrow.

What is Asset Reliability?

Reliability as a term often revolves around adherence to defined standards, a set of expectations, and consistent performance. For most industrial assets, reliability means performing within pre-defined operating conditions and delivering expected results. In a production environment, therefore, an increasing focus is shifting toward asset reliability management. Reliable assets:

  • Experience lesser breakdown and component failures
  • Are available whenever they are required in the production process
  • Safer and more sustainable to operate
  • Adhere to regulatory and quality standards
  • Minimize net maintenance costs and effort

Although, throughout Industry 4.0, there has been a gradual buy-in from manufacturing leaders for prioritizing asset reliability, the ‘how’ part of it has been remiss. Operations and maintenance managers understand the need for reliable assets in their production plants, but how to make available assets more reliable is still not well understood.

With asset reliability transformation, the status quo is changing and manufacturing industries are beginning to develop scalable and sustainable strategies to improve asset reliability.

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:

A business consultant developing a plan that integrates maintenance perspectives for improved asset reliability transformation

1.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.

2.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, spares management must also be an important driver to ensure continued asset reliability.

3.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.

4.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.

5.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.

6.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.

Get in touch with our experts or book a demo now to understand how our solutions fit your plant.
FAQs
Asset reliability refers to the consistent performance of industrial assets within defined operational parameters, ensuring minimal breakdowns, optimal availability, and adherence to safety and quality standards. For maintenance managers, it entails implementing strategies to enhance asset lifespan and efficiency through proactive maintenance practices.
Asset reliability transformation involves adopting comprehensive strategies throughout an asset’s lifecycle—from acquisition to end-of-life management—to maximize reliability and minimize downtime. It is crucial for improving operational efficiency, reducing maintenance costs, and achieving sustainable production practices in industries undergoing digital transformation.
Predictive maintenance utilizes IoT and AI technologies to monitor asset conditions in real-time, predict potential failures, and schedule maintenance proactively. By moving from reactive or preventive maintenance to predictive models, maintenance teams can optimize asset performance, extend lifespan, and enhance overall reliability.
IoT enables continuous monitoring of asset health, while AI analyzes data to generate actionable insights for maintenance planning. These technologies streamline maintenance processes, improve decision-making accuracy, and minimize human intervention, thereby optimizing asset reliability across manufacturing operations.
Asset reliability transformation involves stages such as acquisition (selecting reliable assets), discipline (establishing operational workflows), care (implementing maintenance strategies), analytics (utilizing data for insights), optimization (monitoring and improving asset performance), and end-of-life management (ensuring responsible asset disposal). These steps collectively ensure sustained reliability and operational efficiency.
Advanced analytics enable maintenance teams to monitor key metrics like MTTR and MTBF, perform root cause analysis for failures, and optimize maintenance schedules based on predictive insights. By leveraging these analytics, teams can proactively manage asset health, minimize downtime, and drive continuous improvement in reliability.