All stakeholders in Industry 4.0 are expecting great things of Predictive Maintenance. And this hope is not wholly unjustified – a study by the World Economic Forum and consultants Accenture shows that: 12 percent of planned repairs can be avoided by Predictive Maintenance, and almost 30% of maintenance costs. The study even predicts a saving of 70% of unplanned outages.
All this is made possible by sensor technology and intelligent data analysis. Plant and machine operators can use these to capture status data from machine components continuously, combine the status data with information from third-party systems such as ERP or CRM, and analyse the results so as to predict the optimal time for carrying out maintenance. Impending faults can be recognised before they occur, speeding up processes and avoiding production outages.
Machine 4.0: Looking for new added value
A machine that provides data-flows of its own status is already a reality, as are analysis tools that process this data into meaningful messages. A prototype has been in mass production since autumn 2015 at Schaeffler’s works in Höchstädt. It is the result of close co-operation between Schaeffler, a leading worldwide producer of automobiles and industrial machinery, and DMG MORI. The machine is equipped with sensors at dozens of points that can capture the measured values of pressure, vibrations or forces. Their data is recorded in a network within the machine, and is stored in the Cloud. Online calculations can be initiated via a web service or app, regarding such aspects as the remaining expected lifetime of bearings and the ideal time for carrying out routine maintenance.
Why is Schaeffler one of the first machine manufacturers to turn the vision of Industry 4.0 into practice? “It’s important that we learn, from a real production example, how Industry 4.0 functions in practice, what the real requirements are, and how added value can be generated”, says Joerg-Oliver Hestermann, Schaeffler’s head of Strategic Application Technology for production machines. And in the end, it is all about survival – for only those who can use the digital transformation to offer useful new services to their clients will be able to profit.
Digital business model for machine-building
What do digital business models look like for machine-builders, in terms of the Internet of Things? Dr. Hans-Willi Kessler, Schaeffler’s head of Development for Industrial Service Products, highlights the so-called Micro Services -- analytical tools with which machine status data can be processed in the Cloud.
It is the machine-builder, himself, who must undertake the development of this analysis software. “The Schaeffler group has 100 years of knowledge about roller bearings, which we must convert into software and make it run on appropriate software platforms – and it is important to protect this knowledge. It is our specialist knowledge, and we cannot relinquish it to anyone else”, declares Dr. Kessler.
These Micro Services will provide the decisive advantage to future machine users, for example in the form of Predictive Maintenance – and they can be built into a new business model: “The engineering services that we include today in the price for one of our bearings will in future be calculated via these Micro Services. Thus we can re-finance the costs of developing the necessary software and IT infrastructures for Predictive Maintenance”.
So, will machine-builders in Industry 4.0 have to develop into IT service providers? “No, we will not be IT service providers”, clarifies Dr. Kessler. “The machine-builder will still need to be a technician. But we will need to specialise much more in IT.”
Discover the latest technical developments in Predictive Maintenance at the special Predictive Maintenance 4.0 event at HANNOVER MESSE 2016.