Abstract
In this paper, a combination of graph-based design and simulation-based engineering (SBE) into a new concept called Executable Integrative Product-Production Model (EIPPM) is elaborated. Today, the first collaborative process in engineering for all mechatronic disciplines is the virtual commissioning phase. The authors see a hitherto untapped potential for the earlier, integrated and iterative use of SBE for the development of production systems (PS). Seamless generation of and exchange between Model-, Software- and Hardware-in-the-Loop simulations is necessary. Feedback from simulation results will go into the design decisions after each iteration. The presented approach combines knowledge of the domain “PSs” together with the knowledge of the corresponding “product” using a so called Graph-based Design Language (GBDL). Its central data model, which represents the entire life cycle of product and PS, results of an automatic translation step in a compiler. Since the execution of the GBDL can be repeated as often as desired with modified boundary conditions (e.g., through feedback), a design of experiment is made possible, whereby unconventional solutions are also considered. The novel concept aims at the following advantages: Consistent linking of all mechatronic disciplines through a data model (graph) from the project start, automatic design cycles exploring multiple variants for optimized product-PS combinations, automatic generation of simulation models starting with the planning phase and feedback from simulation-based optimization back into the data model.
Highlights
Most contributions focus on a specific way to facilitate the creation and the usage of a data model for Model-Based Engineering (MBE)/Model-Based Systems Engineering (MBSE) purposes
The state of the art shows that the model-based description of either products or production systems (PS) has been researched widely
This paper focuses on capturing the knowledge of involved disciplines to be able to automate the creation of the central data model
Summary
When designing production systems (PS), flexibility with regard to the markets needs (e.g., product variants, production capacity) brings up the need for reconfigurable manufacturing systems [1]. Requirements from new product variants, which were not foreseen in the first years of operation, and changes in regulations increase the complexity and demand for higher flexibility in the current and future design processes. The prevailing design process for most PS manufacturers is still based on the sequential waterfall model, first defined by R OYCE et al [3]. This is in contrast to the idea of more parallelization using methods of the digital factory, cf [4]
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