Any new system, from a single piece of equipment to a complex production line, is only as good as the care and maintenance it receives. So with industry pivoting to a new, more advanced mode of operation, it makes sense that asset management would have to evolve in tandem.
That’s why Maintenance 4.0 has emerged as a framework for manufacturers. At a time when change is rapid, competition is fierce, and surrounding market conditions are iffy, the cost of unplanned outages or avoidable safety issues must be anticipated and mitigated.
Four stages of maintenance maturity
The eBook points to the road industry has travelled over the last 250 years, tracing four distinct stages of mechanisation and modernisation that end with today’s focus on Industry 4.0. That’s the term for an era defined by smart, autonomous systems fuelled by massive volumes of data and state-of-the-art machine learning tools.
It’s been a long time since anyone powered their business with steam and running water. You wouldn’t base mission-critical maintenance decisions on visual inspections, or on rudimentary instruments that have long since been replaced by more effective tools.
The maintenance maturity model parallels the evolution of industry itself with the development of more sophisticated, technology-enabled asset management strategies. Just as Industry 4.0 technology gives companies an avalanche of data to track, manage, and optimise every aspect of their business, Maintenance 4.0 harnesses that data to keep operations running smoothly.
Industry 4.0 and Maintenance Evolution
Industry 1.0—mechanism through steam and water
Maintenance 1.0—visual inspection
Industry 2.0—electricity drives mass production
Industry 3.0—computerised production processes
Maintenance 3.0—real-time monitoring
Industry 4.0—smart, autonomous systems
Maintenance 4.0—predictive & prescriptive maintenance
The dawn of asset performance management
Maintenance 4.0 enables an emerging approach to asset performance management (APM) that delivers superior operating performance when companies need it most, making it possible for asset managers to get more done with limited resources. An APM solution uses algorithms and machine learning models to predict when an asset is likely to fail, then prescriptively lays out the staff assignment, business processes, and tools that will solve the problem, efficiently and cost-effectively.
The first step is to bring onboard the sensors and other technologies that allow you to collect vast amounts of real-time data and process it with advanced analytics. With that essential business intelligence in hand, an APM solution helps you optimise labour and materials, increase safety, and improve the accuracy of capital budget forecasts.
But to make it happen—to get the full benefit of the shift to Maintenance 4.0—you have to be ready to let go of old techniques that were revolutionary in their time, but are no longer fit for purpose.
Many businesses have already made the shift from reactive processes that spring into action the moment a failure is detected, or preventive strategies that schedule maintenance according to a pre-determined schedule. Not so long ago, it was still sufficient to practice condition-based or even predictive maintenance, using Internet of Things (IoT) sensors to spot deficiencies or potential failures before they were visible to the naked eye.
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