High-value, high-risk aerospace and defense contracts have long been awarded on the basis of servitization, with equipment suppliers committing to keep critical assets working as promised throughout their useful lives.
The appeal for end users is pretty clear, because servitization passes at least some of the risk of breakdowns back up the supply chain to equipment providers. Today there is enormous potential to roll out similar servitization agreements across other industries and a growing number of companies are wising up to the possible benefits.
End users are looking to increase the reliability of their assets and manage costs more predictably. Meanwhile suppliers are looking to build better relationships with customers and reap the considerable revenues available from aftersales support.
Until recently, cost and scalability have been the two big obstacles preventing servitization from rolling out across many otherwise promising sectors. But there’s a crucial difference today, thanks to the availability of smart new asset monitoring technologies that make the risk and costs for original equipment manufacturers (OEMs) of adopting such aftersales service commitments much more predictable and manageable than ever before.
For end users, servitization is typically part of a wider drive to increase operating efficiency and capitalize on opportunities in the market. Servitization helps by reducing the risk of investing in new equipment, as well as increasing efficiency and reducing downtime.
Automotive manufacturers, for example, might typically run a factory with 700 welding robots and 300 handling robots. Why not offload the hassle of maintaining all those assets if the robotics companies can step up and shoulder the responsibility of delivering the necessary number of welds per hour?
And as margins are squeezed on equipment sales, research shows that margins are generally higher on services. OEMs recognize that the right service contracts could provide a welcome boost to revenues.
Traditional reactive and preventative maintenance are still being offered, but Predictive Maintenance is increasingly seen as the way to go. Predictive Maintenance enables OEMs to offer a better service to customers, resulting in fewer unplanned breakdowns and reduced downtime and costs. For many OEMs, more predictable workloads, spares inventory and other cost savings associated with Predictive Maintenance make servitization a reliably profitable business model for the first time.
Predictive Maintenance relies on the ability of OEMs to monitor the condition of assets remotely in order to spot potential problems as they’re happening and fix them before they impact on the end user.
Condition monitoring systems use the latest advanced machine learning algorithms to take machine data and turn it into valuable information about the state of assets across the organization. In other words, automated systems can now deliver advanced condition monitoring without the need for human intervention. What’s more, the new generation of condition monitoring solutions are available via the cloud, making them scalable and easy to implement.
In other words, there has never been a better time for OEMs across all industrial sectors to consider whether servitization is right for them and their customers.
Senseye PdM’s unique algorithms automate the process of turning machine data into an accurate prediction of the Remaining Useful Life (RUL) – a technique known as prognostics. Senseye deployments are a great example of what effective Predictive Maintenance can offer. They typically reduce unplanned machine downtime by 50%, increase maintenance staff productivity by 55% and boost the accuracy of forecasting downtime by 85%.