Local intelligence and networked planning to increase the efficiency of technical production machines in collaborative production networks of SMEs.

Industrial companies are confronted with the increasing individualization of production orders, technically more sophisticated products and increasing demands on cost-effectiveness and resource efficiency. Efficient production planning and control systems are necessary to efficiently manage this complexity and position themselves on the market with competitive prices, delivery times and customer-oriented flexibility.

A high degree of responsiveness requires real-time production and machine data to be taken into account, particularly in production control. This data, such as maintenance information, machine malfunctions or machine configurations, is often already locally available on the machines equipped with sensors, even in small and medium-sized companies. However, in IT systems that are fragmented across various planning and control levels, they are often not reproducible or not depictable in the required level of detail, cannot be integrated and thus cannot be used. This lack of integration of generally available real-time data into planning and control concepts has left considerable efficiency potential unused:

  • Early detection of missing parts and machine malfunctions in order to avoid costly post-production,
  • up to date information on maintenance and set-up intervals to avoid order postponements and to shorten production cycle times, as well as
  • knowledge of current machine configuration as a selection criterion for the best possible assignment of production orders to the machine park.

© Fraunhofer IML

The application partners in the inMachine project have recognized this optimization potential and have realized the vision of using cyber-physical systems to link the real and virtual world more closely and to develop new concepts and methods to make production planning and control sustainable in the future. Using the example of medium-sized manufacturing companies, inMachine will create a flexible, collaborative production system with staggered, optimized planning structures that will enable real-time production control, taking the various production and supply aspects such as energy requirements, material availability or delivery date commitments into account. The subobjectives of the proposal can be summarized as follows:

  • Redesign of planning structures
  • Development of modular planning services
  • Development of an architecture for sensor/actuator networks
  • Development of a concept for the interaction between man and machine


  • Smart Mechatronics
  • software4production
  • Fraunhofer IML
  • FH Dortmund
  • Großewinkelmann
  • Heermann

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