Florian M. Dambietz
Performance simulation of modular product architectures by model-based configuration
Performance simulation of modular product architectures by model-based configuration
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- More about Performance simulation of modular product architectures by model-based configuration
Modular product architectures can improve manufacturing efficiency. This thesis develops a model-based simulation to assess these architectures using MBSE. It generates individual performance criteria by recursively configuring customer requests with alternative modular kits, validating with customer-specific laser welding systems.
Format: Paperback / softback
Length: 179 pages
Publication date: 02 October 2022
Publisher: Springer Fachmedien Wiesbaden
The utilization of modular product architectures holds immense potential for enhancing the efficiency within manufacturing companies. A wide array of modularization techniques is employed in the creation of these architectures, yielding diverse architecture alternatives. This thesis endeavors to present the development of a model-based simulation for comprehensive evaluation of these alternatives, along with their corresponding modular kits. At the core of this simulation lies a model-based configuration system, adept at identifying individually valid product variants through the principles and tools of Model-based-systems-engineering (MBSE). Employing the advanced Hyperspace algorithm, a geometric-mathematical solution approach is employed to assess these variants based on multiple criteria. Through the iterative reconfiguration of multiple customer requests utilizing alternative modular kits, an individual performance criterion is derived, encompassing customer, market, and company-specific parameters. This thesis elucidates the methodology behind the performance simulation, supported by a simplified explanation example. Furthermore, a validation of the simulation's effectiveness is demonstrated through its application to customer-specific laser welding systems.
Weight: 341g
Dimension: 240 x 168 (mm)
ISBN-13: 9783662642351
Edition number: 1st ed. 2022
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