Within the framework of the EU-funded research project "iMAIN", imc is participating in research on innovative concepts for condition monitoring and predictive maintenance.
Machinery, such as large hydraulic presses, are extremely expensive and can hold key strategic importance when it comes to production usage. If these types of machines fail due to a defect or overload, a company can incur enormous costs and can cripple entire production lines. Thus, this suggests that these machines should be continuously monitored to detect their condition, that is, their "state of health". This makes it possible to detect wear and impending failure before a breakdown. This is the basic idea behind "condition monitoring" - using modern measurement technology to greatly increase the potential gains in reliability and cost savings.
With intelligent analysis strategies, one isn't restricted to simply carrying out the maintenance after the machinery has already broken down ("reactive"), nor is one required to perform the maintenance unnecessarily early ("preventative"). Instead, it would be ideal to know the stress and load history, and be able to predict when a possible threat will arise. Naturally, this type of "predictive maintenance" strategy opens up possibilities to introduce a variety of innovative ideas.
The Research Project "iMAIN"
Funded by the EU Commission and in line with the "Seventh Framework Programme", the international research project "iMAIN" is pursuing exactly this challenge of predictive maintenance. Involved from the imc team, Director of Development Dr. Franz Hillenbrand and product marketing expert Martin Riedel worked together with a consortium of companies and institutes from Spain, Sweden, Slovenia and the Fraunhofer Institute in Chemnitz. Taking care of the test and measurement needs of the team, imc was responsible for providing an autonomous platform for data acquisition and analysis.
Concepts for Live Simulation
Very promising concepts for performing live-simulations using so-called "virtual sensors" should help to assist in the determination of load profiles on especially vulnerable components.
For example, by using only a few "actual" strain gauge sensors, the load profile of the massively loaded stand-structure of the press can be determined. The simulation method increases the breadth of coverage of the monitoring, minimizes sensor costs and also allows for the analysis of critical, even inaccessible, internal locations.
The eMaintenance Cloud
Other focal points of the project can be found in system networking over Internet platforms. An "eMaintenance cloud" allows, for example, not only flexible access and administration, but also brings together the user, service specialists, manufacturers and research experts. This is done through the exchange of data. Thus, all benefit from the continuously growing knowledge base.
In addition to the integration of multiple sensors and signal sources, as well as protocols and communication of machine control, wireless sensors are a particular important part of the concept. These are to be used for measurements at inaccessible and moving parts of the machine. They are developed by the Spanish project partner, ADVANTICSYS, and integrated in a homogeneous system structure.
Integrated Approaches Are Needed
Integrated real-time-capable signal analysis and simulation are approaches in physical test and measurement technology that imc has been practicing for quite some time. imc can not only use this expertise within the project, but at the same time, explore new aspects for further development.
The Pilot Plant
A first pilot plant is being installed at the Slovenian home appliance manufacturer, Gorenje. It monitors an 800-ton press that is being used by a project partner. Thus, this is not only a step on the way to the "Industry 4.0" - which fills this ever-present slogan with content and makes it tangible - but it is also a very concrete step to more productive and efficient solutions. Contributing to these are intelligent test and measurement solutions from imc.
Interested in learning more?
For additional information, visit the project website: www.imain-project.eu