Online process monitoring for additive series manufacturing

Aug. 7, 2014
Munich/Stuttgart, Germany – With the Melt Pool Monitoring concept, additive manufacturing solutions provider EOS is developing a high-performance online monitoring solution in cooperation with plasma Industrietechnik GmbH, a supplier of automated quality assurance systems.

Munich/Stuttgart, Germany – With the Melt Pool Monitoring concept, additive manufacturing solutions provider EOS is developing a high-performance online monitoring solution in cooperation with plasma Industrietechnik GmbH, a supplier of automated quality assurance systems. This process monitoring represents decisive added value in terms of risk management and cost reduction for customers.

At the end of 2013, the two companies confirmed their collaboration in the form of a cooperation contract. The aim of this close cooperation is to advance development of the online process monitoring for direct metal laser sintering (DMLS).

Dr. Tobias Abeln, technical director (CTO) at EOS, emphasizes: "We have been working successfully with plasmo for some time now. With their know-how, they are accompanying us as an expert partner in the field of manufacturing and process monitoring on our road towards additive series manufacturing. The key to successful process monitoring is the intelligence of the system. Many are able to record data. Understanding the data correctly and evaluating it appropriately brings the decisive added value. Our goal is to set new benchmarks in this field and we are very pleased to have found the optimum partner for this in plasmo."

"We can look back on 14 years of experience in the field of quality control of laser machining processes in the automotive, aerospace, and metalworking industry," says Dr. Thomas Grünberger, technical director (CTO) at plasmo. "Process know-how from EOS coupled with our expertise in the field of optical quality control systems results in solutions that fulfil the requirements of additive manufacturing perfectly. Our monitoring system, fast process observer, used in connection with the underlying powerful algorithms, is eminently suited for the very high process dynamics of additive manufacturing."

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