Markus Ganser, Manager Standardisierung, Konstruktion, Innovation, BMW Group
“As the leading expert in the application of evolutionary strategies and meta-models to hard industrial optimization problems, Prof. Bäck has always delivered highest quality results for BMW. We truly appreciate our collaboration and warmly recommend a collaboration with Prof. Bäck to any industrial partner who is in the need of solving tough optimization, modeling, and prediction problems.”
Prof. Dr. Bernhard Sendhoff, CEO, Honda Research Institute
“Besides researching and developing the most suitable individual software components, successful multi-disciplinary optimization in an industrial context requires a system level analysis of the problem including issues of workflow, interoperability and resource sharing. Professor Bäck is world-wide one of the leading researchers in computational intelligence and his contributions to the development of new algorithms and methods cannot be overestimated. However, from our perspective, it is his unique analytical ability to amalgamate systems engineering with computational intelligence which makes him such a valuable partner for our institute.“
Dr. Thomas Hochkirchen, Statistical Methods, Central Quality, Ford Werke GmbH, Köln, Germany
"Guaranteeing highest quality standards of Ford vehicles requires a continuous evaluation of quality data from a variety of data sources. With divis GmbH, we have access to a competent partner in the areas of data warehousing, data analysis, and data mining. We would like to express our gratitude to Prof. Baeck and his team."
Dr. Thomas Hillemann, Leiter der Studienkoordination, Beiersdorf AG, Hamburg, Germany
"Our past experience limited our trials to include only familiar ingredients, and the lengthy process of attempting each combination had led us to declare the desired product infeasible after three months of research. However, with ClearVu Analytics, we satisfied all the technical requirements faster than with traditional processes, and now have a new product we will bring to the market."
Dr. Andreas Treitl, Technical Director, Chemetall GmbH, Frankfurt, Germany
„Through the support by the divis experts, we were able to develop a model which allows us to optimize the parameter settings of the coating process. Normally, this requires a large number of costly and time consuming laboratory experiments. The competent support provided by divis made it possible to reduce this effort significantly and make the whole process more efficient. The mathematical models derived by divis facilitate a better understanding of the impact of changes in the process control parameters on the resulting process behavior. This insight contributes significantly to process understanding as well as process robustness and quality at the client site.“
Dr. Matthias Hauser, Associate Director Scientific Relations, Johnson & Johnson GmbH, Düsseldorf, Germany
„We are still implementing and evaluating our new model, but clearly we can now predict micro results for new formulations using known components at this time. We will continue to expand our use of the model, but critical to this process is internal data collection. But even this early in the project, we have a better picture of how our materials interact and the effects to the wipe. And we have a set of working rules for our formulators.“
Charles Harper, Production Control Manager, Air Liquide America, Houston, TX
“Finally, we are now in possession of the tools and information needed to give us optimal solutions – this is exactly the kind of breakthrough we have been looking for to significantly change our business processes.”
Dr. Helmut Gehrke, Head of Laboratory Department, R&D Division, ThyssenKrupp Industrial Solutions AG
“Former ThyssenKrupp Uhde GmbH in Dortmund, today called Business Unit Process Technologies, part of ThyssenKrupp Industrial Solutions AG (a world-wide operating engineering corporation for the planning and construction of chemical plants) is using divis’s data mining software by divis GmbH for data driven modeling tasks. The goal is for chemical processes to describe cause and effect patterns faster and better than before, and to evaluate the process parameter’s impact through sensitivity analysis. The results obtained so far clearly illustrate the capabilities of the special methods provided by divis, such that ThyssenKrupp Industrial Solutions is now considering additional projects.”