A new framework for supporting and managing multi-disciplinary system-simulation in a PLM environment
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In order to keep products and systems attractive to consumers, developers have to do what they can to meet growing customers’ requirements. These requirements could be direct demands of customers but could also be the consequence of other influences such as globalization, customer fragmentation, product portfolio, regulations and so on. In the manufacturing industry, most companies are able to meet these growing requirements with mechatronic and interdisciplinary designed and developed products, which demand the collaboration between different disciplines. For example, the generation of a virtual prototype and its simulation tools of a mechatronic and multi-disciplinary product or system could require the cooperation of multiple departments within a company or between business partners. In a simulation, a virtual prototype is used for testing a product or a system. This virtual prototype and test approach could be used from the early stages of the development process to the end of the product or system lifecycle. Over years, different approaches/systems to generating virtual prototypes and testing have been designed and developed. But these systems have not been properly integrated, although some efforts have been made with limited success. Therefore, the requirement exists to propose and develop new technologies, methods and methodologies for achieving this integration.
In addition, the use of simulation tools requires special expertise for the generation of simulation models, plus the formats of product prototypes and simulation data are different for each system. This adds to the requirements of a guideline or framework for implementing the integration of a multi- and inter- disciplinary product design, simulation software and data management during the entire product lifecycle.
The main functionality and metadata structures of the new framework have been identified and optimised. The multi-disciplinary simulation data and their collection processes, the existing PLM (product lifecycle management) software and their applications have been analysed. In addition, the inter-disciplinary collaboration between a variety of simulation software has been analysed and evaluated. The new framework integrates the identified and optimised functionality and metadata structures to support and manage multi- and inter-disciplinary simulation in a PLM system environment.
It is believed that this project has made 6 contributions to new knowledge generation: (1) the New Conceptual Framework to Enhance the Support and Management of Multi-Disciplinary System-Simulation, (2) the New System-Simulation Oriented and Process Oriented Data Handling Approach, (3) the Enhanced Traceability of System-Simulation to Sources and Represented Products and Functions, (4) the New System-Simulation Derivation Approach, (5) the New Approach for the Synchronisation of System Describing Structures and (6) the Enhanced System-Simulation Result Data Handling Approach.
In addition, the new framework would bring significant benefits to each industry it is applied to. They are: (1) the more effective re-use of individual simulation models in system-simulation context, (2) the effective pre-defining and preparing of individual simulation models, (3) the easy and native reviewable system-simulation structures in relation to input-sources, such as products and / or functions, (4) the easy authoring-software independent update of system-simulation-structures, product-structures and function-structures, (5) the effective, distributed and cohesive post-process and interpretation of system-simulation-results, (6) the effective, easy and unique traceability of the data which means cost reductions in documentation and data security, and (7) the greater openness and flexibility in simulation software interactions with the data holding system.
Although the proposed and developed conceptual framework has not been implemented (that would require vast resources), it can be expected that the benefits in 7 above will lead to significant advances in the simulation of new product design and development over the whole lifecycle, offering enormous practical value to the manufacturing industry.
Due to time and resource constraints as well as the effort that would be involved in the implementation of the proposed new framework, it is clear there are some limitations to this PhD thesis. Five areas have been identified where further work is needed to improve the quality of this project: (1) an expanded industrial sector and product design and development processes, (2) parameter oriented system and production description in the new framework, (3) the improved user interface design of the new framework, (4) the automatic generation of simulation processes and (5) enhancement of the individual simulation models.