Introduction

New Tools to Boost Automated Manufacturing

 

The European research project IMPROVE has developed innovative 4.0 solutions to equip the manufacturing industry for the future.

  • Client

    IMPROVE

  • Services

    To equip the manufacturing industry for the future.

  • Technologies

    Industrial Automation

  • Dates

    06/10/2018

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Description

Within the three year research project IMPROVE 13 leading players from academia, industry, and software development from all across Europe have joined forces to find innovative solutions for the manufacturing industry. Responding to the changing needs and challenges faced by manufacturers and production facilities in times of Industry 4.0, the project has developed novel tools in the field of simulation and optimisation, condition monitoring, alarm management, and quality prediction.

 

To succeed in the increased global competition, the manufacturing industry depends on high-level solutions to ensure excellent machine functionality. Enterprises have to invest in innovative technologies to improve their production, reduce waste and provide an intuitive human machine interface for operators in the factory. The question how companies will react to the challenges of Industry 4.0 might decide whether they can defend their position on the market in the future. The IMPROVE project now presents novel solutions for the next generation of enhanced manufacturing.

 

“The tools and applications developed by the IMPROVE team over the past three years will help foster productivity of automated manufacturing and facilitate machine operation for enterprises all over the world,” states IMPROVE coordinator Prof Dr Oliver Niggemann from the Ostwestfalen-Lippe University of Applied Sciences. “I am convinced that our solutions will pave the way for new standards in automated manufacturing. By applying our tools, producers, manufacturers, IT specialists, and engineers can not only boost productivity and strengthen competitiveness – but also guarantee the sustainability of the production.”

 

The solutions in the fields of simulation and optimisation, condition monitoring, alarm management, and quality prediction allow manufacturers and producers to improve their productivity and product quality, to increase cost-efficiency and industrial competitiveness as well as to reduce energy consumption and waste.

 

IMPROVE Solutions at a Glance

With the simulation-optimisation round-trip solution, IMPROVE provides an application to enhance the overall production design. The tool allows forecasting the production process and ensures an optimised machine setting. Furthermore, it provides quality forecast, roll change simulation, energy optimisation, and the training education of operators by augmented reality applications.

 

The self-learning condition monitoring solution allows forecasting maintenance needs based on a data-driven machine learning approach. Up to now, only experienced operators were able to perform condition monitoring efficiently. The new IMPROVE solution is hence revolutionary for a precise prediction. The tool protects producers from unexpected breakdowns or product degradation and can be translated into different software options.

 

The alarm management solution supports the machine operator in case of an alarm flood. The innovative algorithm is based on data-driven similarity learning as well as case-based-reasoning and integrates expert knowledge. It particularly assists the operator in finding the root cause for the alarm and taking the right action.

 

With the decision support app for quality monitoring, IMPROVE helps the machine operator to predict the quality of the production by using data-driven models based on machine parameters. As the new app enables an exact quality prediction, it ensures the best possible quality for the whole production process.

 

“Our IMPROVE tools are all supporting the operator to facilitate the handling of difficult situations in the manufacturing process,” explains Professor Niggemann. “These are for example alarm floods, unexpected breakdowns, quality measuring or detection of faults and anomalies – with our solutions we are providing an intuitive and best possible human machine interface to improve the overall production process and to support the operator in the best possible way.”

 

Using IMPROVE tools in the industry

The solutions that have been developed within IMPROVE have been tested and verified in different use cases in an industrial surrounding – for example in the facility of the IMPROVE partner OCME.

 

“One main benefit of IMPROVE is that we have directly tested our research in the field. In IMPROVE, we have industry partners from a lot of different industry sectors with very complex plants – so we were able to test and verify our algorithms directly in these facilities. This is a very valuable point in our research project,” states Alexander von Birgelen from Ostwestfalen-Lippe University of Applied Sciences, who developed the condition monitoring tool.

 

“During the project, we tested the IMPROVE tools using our machines and our lines,” explains Davide Buratti, Research and Development Manager at OCME. “The results have been very promising: using these techniques it was possible to reduce the time of the engineering phase and to apply an optimal configuration in order to reduce space in the plants as well as to save energy. Currently, we plan the use of these technologies in more machines that we produce for our customers in order to increase their lines efficiency.”

 

The European research project IMPROVE stands for “Innovative Modelling Approaches for Production Systems to Increase Validatable Efficiency”. Together, the 13 partners from six countries have been working on new solutions for automated manufacturing since 2015 to meet the challenges of the Industry 4.0. IMPROVE has received an EU funding of € 4.2 million within the Programme for Research and Innovation Horizon 2020.

 

Find out more about IMPROVE and major findings on http://improve-vfof.eu/findings/

 

Captions

Pix1 – IMPROVE Consortium. Photo credit: IMPROVE

Pix2 – IMPROVE Demonstrator. Photo credit: HS-OWL

Pix3 – The Reicofil line. Photo credit: Reifenhaeuser Reicofil

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