Predictive maintenance, which can detect maintenance issues in real-time, enables equipment and vehicle owners to execute cost-effective maintenance and predict it in advance, before the equipment malfunctions or is damaged. Predictive maintenance, when done effectively, may increase the lifespan of industrial assets while lowering costs and increasing availability.

With nearly 4,900 kilometers (3050 miles) of high-speed rail lines, Spain possesses the world’s second-largest high-speed rail network. Renfe, the rail operator, guarantees that all of its AVE (Alta Velocidad) trains will arrive on time across the country.

Renfe is now able to retain over 99 percent of its high-speed trains running at all times. Thanks to real-time monitoring, predictive maintenance, and on-demand component replacement.

Predictive Maintenance Assists Industries in Realizing Digitalization Benefits

Preventive maintenance entails conducting routine inspections and replacing certain parts at predetermined periods. While this has shown to be effective in various industries and has helped avoid more expensive repairs, it also generates a waste system. Many of the replaced parts are still in good enough condition to continue functioning properly.

Predictive maintenance, unlike preventative maintenance, replaces only the required part when it is needed. It not only detects machine conditions that may lead to failure, but it also estimates the time before that failure occurs, allowing for service planning.

The massive investment in legacy machinery is one of the most frequently highlighted hurdles to advance in Industry 4.0. Industrial assets are currently being used in this concept. Many heavy machinery manufacturers are now considering a “rent” model, in which the asset is leased to the operator, who pays for the machine’s actual use. The service includes maintenance and spare parts.

The manufacturer can use real-time monitoring and predictive maintenance to determine when a technician should be sent to perform maintenance work or notify the machine operator to replace a component that is about to fail. The asset’s downtime is minimized, and the machine’s best performance is ensured for many years.

Predictive Maintenance is coming to Consumer Products

Traditionally, preventive maintenance is performed on a vehicle when it reaches a given driving distance or a certain amount of time since its last checkup, whichever comes first. For decades, automobile manufacturers and dealers have relied on this method.

While there is a definite shift towards electrification, the majority of cars sold today still use internal combustion. Car manufacturers and dealers seek ways to improve maintenance by continuously monitoring all of the vehicle’s vital systems. Using connected sensors and onboard analytics, it is viable to predict when maintenance is essential.

Appliance manufacturers are considering the same concept. When the machine’s sensors identify that a vital component is about to fail, it will schedule a maintenance call, the necessary components, and a technician to replace it. The consumer no longer has to deal with a damaged appliance while waiting for a repairer to arrive, identify the problem, and return with replacement components later.

Wrapping Up

Predictive maintenance is already playing a significant role in Industry 4.0. It is also a critical component of engineering and manufacturing. From minimizing equipment downtime to creating substantial cost savings to increasing efficiency all through the production line, the advantages of investing in predictive maintenance are enormous.