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MDA showcases digitalization with predictive maintenance applications Hannover Messe, the world’s leading trade fair for industrial technology will be staged from 24 th to 28 th April 2017 in Hannover, Germany. With its core focus on “Integrated Industry,” it is the world’s leading exhibition for the digitalization of production, maintenance and energy systems In the world of industries, predictive maintenance is currently a hot topic and will play a central role at the Motion Drive and Automation forum at Hannover Messe 2017. Operators of machinery and vehicles do not want to wait until a vital component fails, but they also do not want to replace it ahead of time. And now they no longer have to, because leading suppliers of power transmission and fluid technology have developed systems that permit continuous monitoring of key components such as roller bearings, electric motors, gears, hydraulic pumps, and compressed fluids. “Predictive Maintenance is an important part of networked production and Industrie 4.0. Intelligent components use integrated sensors to capture and evaluate data in real time. Predictive Maintenance is a terrific strategy to effectively harness the interaction between mechanical engineering and IT,” says Peter Synek, Deputy Managing Director, Fluid Power Division, German Mechanical Engineering Industry Association (VDMA). This is actually nothing new: “condition monitoring” was already a main topic at past MDA shows. What is new, however, is the information that can now be extracted from condition monitoring systems. With the aid of intelligent software, the data acquired in real time allows the operator to carry out servicing or replace worn components at precisely the right time – with no fixed service interval, and before the part in question fails. How Predictive Maintenance works in reality Roller bearings are a good example of this. The reference variables in this case are vibration, temperature and speed (revolutions per minute). These are continuously monitored and analyzed so that any irregularities can be detected and their effect on the life of the bearing calculated. At the same time, any bearing that is running hot can be identified by temperature monitoring. For example, Schaeffler offers such a service for roller bearings used in wind turbines and rail vehicles. Schaeffler’s dedicated cloud analyzes the collected data and generates the results in plain-text format. So the user or operator no longer needs to have any expertise in analyzing sensor data, as is the case with condition monitoring. Instead, the system itself performs the analysis and the condition of the bearing can be checked from anywhere in the world via the Internet; similarly, the remaining life of the bearing can be calculated on the basis of the actual load spectra. NEWS AND MARKETS WORLD OF INDUSTRIES – MOTION, DRIVE & AUTOMATION 1/2017

Demand for this kind of “micro-servicing” via data-based predictive maintenance is currently very high, and not only in electromechanical power transmission. Predictive maintenance systems for hydraulic drives, for instance, can incorporate particle counters. Parker will present such a system at MDA – not only at its own exhibit, but also in the VDMA Forum in Hall 19. Stefan Nilgen from Parker Hannifin tells us: “With our ‘Total System Health Management’, we can acquire data from every part of the system, including peripherals, then analyze it and use it to take the necessary measures. That way, we can keep an eye on the overall productivity as well as the total cost of ownership of complex systems such as hydraulic installations or fluid power transmissions, and can carry out whatever preventive maintenance might be needed. So ideally, any corrective measures will become unnecessary, or at least foreseeable, so that we can plan ahead and avoid the unexpected breakdowns of the past. For the user, that translates into cost savings, thanks to a longer service life and higher productivity.” The predictive maintenance tool developed by Bosch Rexroth is called OdiN, and it will also be on display at this year’s Hannover Messe. The acronym stands for “Online Diagnostic Network”, along with sensor technology and cloud-based applications it also employs the methodology of machine learning to perform preventive maintenance – with a high degree of precision. Tapio Torikka is the man responsible for developing the system: “A human expert monitoring the installation continuously by conventional means will detect a fault with 43 % probability. Our system has a fault detection rate of 99 %.” Gaining additional momentum Predictive maintenance has gained additional momentum as a result of Big Data and other themes associated with Industry 4.0. It is becoming progressively easier to collect and process relevant data for servicing and maintenance. This trend is driven in part by cross-sector collaboration, such as that between manufacturers of sensors and manufacturers of power transmission systems. Aventics and sensor specialist IFM are planning to work together in future to monitor and analyze operating data – e.g. for pneumatic cylinders – entirely online, and independently of machine control functions. This is a classic predictive maintenance scenario. Schaeffler and IBM have entered into a strategic partnership with the aim of continuously monitoring power transmission systems in critical applications such as wind turbines and railway trains using machine learning to optimize performance based on the data acquired. Systems of this kind are discussed under the collective heading of “predictive analytics”. Visitors to MDA forum with a special interest in this development would be well advised to take a close look at 7 other trade shows taking place in parallel, namely Industrial Automation, Digital Factory, Energy, ComVac, Industrial Supply and Research & Technology. Here, leading companies from all over the world will be presenting their ideas and visions for Industry 4.0 and the Industrial Internet of Things, including the whole area of preventive maintenance. Photographs: Deutsche Messe AG Peter Synek, Deputy Managing Director, Fluid Power Division, German Mechanical Engineering Industry Association (VDMA) WORLD OF INDUSTRIES – MOTION, DRIVE & AUTOMATION 1/2017