Column Maintenance On The Floor Reliability

The Future of Maintenance

Klaus M. Blache | December 1, 2021

By Dr. Klaus M. Blache, Univ. of Tennessee Reliability and Maintainability Center (RMC)

Q:  What’s next for maintenance?

A: The global maintenance workforce has evolved through various stages since 1950. Here’s an updated version of my representation of the evolution of R&M tools and technologies. These changes are coming faster, enabling better decisions based on data, but at the cost of complexity and, for at least some time, greater difficulty in implementation. Changing mindsets from a reactive to a proactive maintenance strategy will continue to be a challenge. Human reliability and data integrity (enough to make the tough operational decisions) will still be a hurdle.

Note that in about 1950, 1980, 2010, and 2020 there were “zones of uncertainty.” I’ve witnessed three of them and the next one may come as soon as 2025. They are happening more frequently: 30, 30, 10, and probably 5 (TBD), years apart. I define a zone of uncertainty as still stuck in the prior paradigm of R&M either because you and/or your workforce don’t understand or don’t have the resources and knowledge to move forward.

Gartner Inc., Stamford, CT, (, published a report on maintenance becoming more collaborative, 6 Critical Changes That Affect the Future of Asset Maintenance. “Equipment characteristics and related process changes will transform business ecosystems from simple, own-maintain models to complex, collaborative ones. Asset-intensive industry CIOs must respond to changes in asset attributes, maintenance management, supply chains, and business value.” Examples include:

  • Change 1: New attributes (physical and digital) will define equipment.
    • OT and IOT platforms expand the data sources from equipment.
  • Change 2: Data and intelligence will be collected in new ways.
    • Who owns the data and who should have access?
  • Change 3: Maintenance will be managed through new tools.
    • New asset-management support tools are emerging.
  • Change 4: Parts will move differently in the supply chain.
    • On-site replenishment
    • 3D printing
  • Change 5: Companies will need to identify and participate in the right ecosystems to expand data reach.
    • Identifying the correct ecosystems
    • Participating in the right ecosystems
  • Change 6: How we value asset-centric businesses will change.
    • Digital twins enable new strategic business models.

Reliability and maintenance have come a long way from “fix it when broke” to today’s technologies. There will much greater interconnectivity in asset management, machine-to-machine communication, and sensors (more reliable and without batteries). Many more options for 3D printing will affect supply-chain needs (additive manufacturing on site) and, overall, new business models will be needed to make sense of it all to enable successful implementation. 

The best companies will have their purchasing departments responsible for “lifetime” costs of the assets to get designed-in maintainability concepts at purchase. More machine learning will help in condition-based maintenance (CBM), providing better/faster feedback on results. I say this because some of my analysis showed that CBM was not getting expected benefits in a group of facilities. So, it’s important to follow up to assess the CBM finds and benefits. A similar analysis on predictive technology routes (followed with fixes) resulted in less reactive maintenance. 

Also in development is 4D printing. Fundamentally it’s the same as 3D printing, except it includes shape morphing responding to an environmental stimulus such as temperature, light, voltage, humidity. There will be more real-time data for decision making and prescriptive maintenance (machine learning assigning only necessary work orders/maintenance)

 The amount of available data will cause its own challenges, primarily the cost of storage and security. There will be a greater need for improved human-machine interfaces (ergonomics) as more automation, connected devices, software controls, assists, edge computing, machine learning/AI decisions at systems thinking level are implemented. 

International Data Corp., Needham, MA, (, predicts that the collective sum of the world’s data will grow from 33 zettabytes in 2021 to 175 by 2025. One zettabyte equals 1,000,000,000,000,000,000,000 bytes. Almost 30% of the data generated will be consumed in real-time by 2025.

Companies are making better data-based decisions, but it’s still what I refer to as “data rich, information poor.” The practicable tools and processes have not been established to take advantage of the dormant knowledge that can be used to improve performance.

As companies work toward Industry 4.0 (often referred to as the fourth industrial revolution), things will change more quickly for all involved in reliability and maintenance. Many items will be beyond anything that we can conceptualize today. EP

Based in Knoxville, Dr. Klaus M. Blache is director of the Reliability & Maintainability Center at the Univ. of Tennessee, and a research professor in the College of Engineering. Contact him at



Klaus M. Blache

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