SIMULATION AND DATA MODELS FOR PRODUCTION

With the simulation-based analysis, planners and operators of production systems get a practical tool that enables them to predict the effects of planned measures or decisions as well as to estimate the key performance indicators that can be expected by these decisions.

The modelling process of simulation is a design lever to master the increasing complexity of production. Consistent and lifecycle spanning models are an important concept of the digital world. Consequently, they are of central importance in the context of industry 4.0.

Design models make the creative value of design, dimensioning and engineering transparent and thus create the basis for building complex systems at all. They represent the knowledge of the engineers and are thus the executable documentation of the problem-solving approach chosen.

Explanatory models, on the other hand, depict existing systems and are used to gain insights into the behaviour of complex processes and relations by performing experiments. Often, the understanding of a system gained by the explanatory models serves as the basis for the further creative process of designing and optimising.

The application areas for the simulation range from the technical and logistical processes of the shop floor to the associated business processes at the management level.

The analysis and simulation of a system allows the development and visualization of performance measurement systems. Using the right technologies supports the usage of big data in in-memory data bases. These support the analysis of different aspects in real time.

The discrete event simulation used as method models the dynamic processes of a production system, taking into account both the stochastic effects of real problems as well as all the interactions of the system components. In contrast to classical mean value and limit considerations, the simulation models consider and show temporal fluctuations, competing resources and shifting bottlenecks.

With the simulation results, different configurations and scenarios can be assessed technically as well as economically, systems can be optimally dimensioned as well as planning errors can be early detected and thus risks can be minimized. In addition, simulation models build the basis for new planning and optimisation tools used for plant operation.

For more than 20 years, PROFACTOR has developed discrete event models as well as simulation-based tools for various industries and applications. The focus is on the analysis, virtual validation and optimisation of technical production logistics as well as on the development of simulation-based solutions for production scheduling and control.

Vision is a consistent use of simulation models along the production life cycle in the sense of the Digital / Virtual Factory so that simulation models are available as decision support at any time and at any place in parallel to real production.