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Knowledge, Awareness, and Prediction of Man, Machine, Material and Method in Manufacturing



The 7th Framework Programme funded, integrated large project „Knowledge, Awareness, and Prediction of Man, Machine, Material and Method in Manufacturing“ (KAP, 2010-2013) is a multidisciplinary, industry supported research initiative that aims to develop the next generation technology framework and manufacturing standards that ensure the efficient usage of energy and resources through the effective coordination of man, machine, material, and method.


Manufacturing is the driving force behind Europe’s economy, providing over €6,553 billion of GDP. Against a background of climate change legislation, volatile energy prices, and increased environmental awareness, modern manufacturing must encompass a focus on sustainability and eco-efficiency. Measurements will be gathered through a factory-wide network of sensors. Complex Event Processing (CEP) and data stream analysis will compute on-the-fly production performance indicators (PPIs) for real-time monitoring. Data mining in combination with Online Analytical Processing (OLAP) will support problem diagnosis and resolution. Computational learning techniques will create a self-improving system for operational control. The inclusion of energy management makes the interpretation of system data an even greater challenge. Perceptually efficient visualisations will communicate PPI’s to decision makers in a format that will reduce cognitive workload and improve situation awareness. A well-balanced consortium of research centres, academic and industry partners provides an ideal opportunity to realise the innovations proposed by the project. In terms of impact, partners estimate reductions of over 5% p.a. in waste and energy and 10% in time to market.

The Department for Assembly Technology and Factory Management (MF, German: Montagetechnik und Fabrikbetrieb) coordinates activities in the fields of energy efficient manufacturing. The long experience of MF in the areas of sustainable manufacturing, modelling of production systems and software supported production planning are the basis for its research work on hierarchical energy and resource consumption models, online monitoring infrastructures, green production planning and maintenance approaches. In addition, MF offers its wide dissemination network of academic and industrial partners and experience in standardization processes.

Project consortium

  • SAP Research, Germany
  • European Microsoft Innovation Center, Germany
  • Intel, Ireland
  • Infineon Technologies, Germany/Austria
  • Volvo, Sweden
  • Nissan, Spain
  • Atos, Spain
  • Missler, France
  • Leia Research (Tecnalia), Spain
  • Technical University of Berlin, Germany
  • University Patras, Greece
  • University Trento, Italy
  • De Montfort University, UK


Emec, S.; Kuschke, M.; Chemnitz, M.; Strunz, K.:

Potential for Demand Side Management in Automotive Manufacturing; Proceedings of the 4th European Innovative Smart Grid Technologies (ISGT), 2013.

(http://ieeexplore.ieee.org/xpl/abstractAuthors.jsp?arnumber=6695303 )


Emec, S.; Kuschke, M.; Strunz, K.; Seliger, G.:

Stochastic optimization method to schedule production steps according to volatile energy price: Proceedings of the 12th Global Conference on Sustainable Manufacturing, Berlin, 2013.



Swat , M.; Stock, T.; Bähre, D.; Seliger, G.: 

Monitoring production systems for energy-aware planning and design of process chains; Proceedings of the 12th Global Conference on Sustainable Manufacturing, Berlin, 2013.

(http://www.gcsm.eu/Papers/142/19.4_53.pdf )






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