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A Novel Approach to Generate Assembly Instructions Automatically from CAD Models

: Neb, Alexander; Scholz, Johannes


Weißgraeber, Philipp:
Advances in Automotive Production Technology - Theory and Application : Stuttgart Conference on Automotive Production (SCAP 2020), 9th and 10th of November 2020
Wiesbaden: Springer Vieweg, 2021 (ARENA2036)
ISBN: 978-3-662-62961-1 (Print)
ISBN: 978-3-662-62962-8 (Online)
Stuttgart Conference on the Automotive Production (SCAP) <1, 2020, Online>
Fraunhofer IPA ()
Automatisierung; CAD; CAD-Modell

For the distribution of consumer and industrial goods, every company is obliged to provide assembly instructions. For the consumer goods market, for example, the German Civil Code defines that defective assembly instructions must be declared as a material defect. However, the creation of comprehensible and defect-free assembly instructions is still a very time-consuming manual process, which must be determined in an extremely time-consuming procedure. Nonetheless, assembly instructions are more than just obligatory documents. They are also required in places where they are not prescribed. For example, assembly instructions are needed in production to pass on assembly knowledge to the assembly operators. Here, it often turns out that this knowledge is either not available or can only be used to a limited extent. The two key elements of an assembly instruction are the assembly sequence and the visual illustrations. Currently, the assembly sequence is determined manually by the designers based on their personal experience, whereas illustrations are generated with costly software tools which are not even able to check the feasibility of the planned instruction. This work presents a novel approach to generate assembly instructions directly and automatically from CAD models of the designers. For this purpose, the commercial CAD software SolidWorks was extended by a macro Tool. All necessary data to generate an assembly instruction are extracted from the CAD model. The extracted data are assembly features, stability and geometric restrictions, subassemblies and assembly directions. Based on these data, the assembly operations are evaluated with a fitness function which includes the attributes like tool changing costs or distances of assembly paths. The whole assembly sequence optimization process was modeled as a Travelling Salesman Problem. After the ideal assembly sequence was found by the macro Tool, this tool also generated matching visualizations of the assembly operations based on the CAD model. The approach was validated by three different models, an assembly benchmark, a single-cylinder engine and a gear box.