Research & Development

Research for innovation

The research credo of the center is to provide manufacturing companies with the competence to design and control their continuous, data-supported and agile value creation chains on location and network level. The aim is to achieve annual productivity increases by way of proactive responses to change.

This is achieved by merging various production apps in a global control center, which…

  • creates data-supported and realtime-capable transparency.
  • makes available alternative courses of action based on assessments.
  • helps to proactively identify necessary changes.
  • ensures best practice sharing within the network.
Based on multiple focus topics, the GPMC concentrates specifically on practical research approaches. Companies have the opportunity to participate in the topic areas in a variety of formats or to drive their own topics, for which the GPMC will offer support with its formidable background of research experience, embodied in its research assistants and experts, and the close proximity of the WZL at RWTH Aachen University.

Our current research topics are:

Process Mining

The ability to stay one step ahead of the competition hinges upon efficient business processes. The aim of the new data analytics technology ‘Process Mining’ is to identify, monitor and improve actual business processes based on real data and with as little costs as possible. The basis for Process Mining is therefore data that already exists in the information systems of a company. The use of this data permits the creation of an actual image of the business processes and allows dynamic process controlling by way of intuitive process descriptions and the analysis of key performance indicators (KPIs). The application of Process Mining has already proven cost-effective, as it has allowed companies to save millions.

Process-independent applications of Process Mining will significantly enhance the process efficiency increases achieved to date. The GPMC is therefore exploring the possibilities of an adaptation of Process Mining across the entire order handling process in collaboration with Prof. Dr. Van der Aalst – the founder of the Process Mining discipline. The objective is to compare the challenges of this innovative topic with the requirements of manufacturing companies and to transfer the findings back into research:

  • Which KPIs should be used for measuring order handling processes?
  • How can full transparency of the order handling process be simplified to the push of a button?
  • How can data-supported decision-making tools help optimize process performance?
The center furthermore offers methodological and expert support for company-specific Process Mining applications. Discussions and knowledge exchange between academia and industry will offer members an opportunity to increase their process efficiency by objectively identifying process deviations, weaknesses and bottlenecks based on actual, low-cost data.
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KI & Data Analytics

The big tech companies are leading the way: Apple’s voice-activated assistant “Siri” or Amazon’s purchasing aid “Frequently bought together”. Our society has gotten so used to dealing with Artificial Intelligence (AI) that we barely notice, how amazingly innovative it really is. In terms of production, the scenario is quite different: manual tweaking of production controls, low transparency at throughput times, and a whole host of repetitive work steps. Why hasn’t AI found its way into production?

There are many reasons for the low utilization of AI: complex processes, bad data quality and permanent cost pressures make AI products appear uncertain, which means they don’t get approved. Taking a closer look at these reasons, however, it soon becomes clear that AI is not the problem – it is the right answer. When AI is used properly, process complexities can be managed efficiently. AI can heal insufficient data quality with statistics and help decision-makers achieve significant cost savings. What is needed is a clear understanding of what AI can and can’t do, and a vision for actively involving employees in the data evaluation process to ensure that they can trust AI results and use them accordingly.

The offering of the GPMC for manufacturing companies is an application-oriented examination of the topic AI, an uncomplicated way to gain experience quickly and achieve good results. To that end, the GPMC examines success factors and best practice for dealing with AI and translates these into a structured and methodically secured procedure. Do you have the feeling that you keep having to start from scratch and still don’t get anywhere despite huge efforts? Contact us with regards to research and/or consulting projects, or seminars on the topic of AI.

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Contact

Dr.-Andreas-Guetzlaff Research & Development
Andreas Gützlaff, M.Sc. RWTH
Center Director
Telefon: +49 151 46761122
E-Mail: A.Guetzlaff@gpmc-aachen.de