In a push for optimization of the maintenance processes of their assets, European manufacturers and transport operators are turning to digital technologies such as the Internet of Things or predictive analytics to enable the collection of vast amounts of operational data, which can be used to predict sudden failures of their machinery and vehicles. Thus, the concept of predictive maintenance, which has the potential to redefine maintenance and boost the efficiency of shop floor operations and fleets, is becoming a reality.
Market research and strategic consulting company PAC has conducted an in-depth study to find out how large and medium-sized European manufacturing and transport companies see and approach the opportunity of predictive maintenance from a strategic, implementation and operational perspective. The study titled “Digital Industrial Revolution with Predictive Maintenance” is based on a survey of more than 230 senior business and IT executives.
Predictive maintenance promises operational efficiency
According to the survey, 83% of companies are thus ready to raise their game when it comes to predictive maintenance – a clear sign that there is an appetite for solutions that can improve operational efficiency. This is not surprising, given that 96% of the companies regard their maintenance processes as not very efficient, making room for improvement and further cost-cutting in these asset-intensive industries.
The results of the study show that the companies in Europe are not too confident in terms of efficiency of the maintenance processes for their industrial machines or vehicles. Hence, they see an opportunity in cutting the unnecessary costs occurring due to unplanned and sudden failures of their assets by redefining their maintenance with predictive analytics insights. Furthermore, as analytics becomes a boardroom topic, PAC expects further investments to be channeled towards predictive maintenance.
55% of companies are already conducting some sort of predictive maintenance initiatives. Almost a quarter of the companies are already harvesting the fruits of such initiatives, while the rest are still testing the water. However, PAC expects companies’ interest and spending to further increase, as they will continue to feel the rising cost pressure and competitive headwinds.
Reducing repair time and unplanned downtime is considered one of the major goals of predictive maintenance projects by 91% of companies. Breathing new life into aging equipment is another major objective of predictive maintenance initiatives, as seen by 86% of companies. For 70% of companies, another important goal is improvement of customer satisfaction. This is especially important for product-oriented manufacturers, as for them predictive maintenance also means the ability to provide better servicing of these products to the customers.
The study will be available from PAC/CXP by the end of May 2018.