The use of systems engineering principles for the integration of existing models and simulations
2017-09-29T08:10:07Z (GMT) by
With the rise in computational power, the prospect of simulating a complex engineering system with a high degree of accuracy and in a meaningful way is becoming a real possibility. Modelling and simulation have become ubiquitous throughout the engineering life cycle, as a consequence there are many thousands of existing models and simulations that are potential candidates for integration. This work is concerned with ascertaining if systems engineering principles are of use in the support of virtual testing, from desire to test, designing experiments, specifying simulations, selecting models and simulations, integrating component parts, verifying that the work is as specified, and validating that any outcomes are meaningful. A novel representation of systems engineering framework is proposed and forms the bases for the methods that were developed. It takes the core systems engineering principles and expresses them in a way that can be implemented in a variety of ways. An end to end process for virtual testing with the potential to use existing models and simulations is proposed, it provides structure and order to the testing task. A key part of the proposed process is the recognition that models and simulations requirements are different from those of the system being designed, and hence a modelling and simulation specific writing guide is produced. The automation of any engineering task has the potential to reduce the time to market of the final product, for this reason the potential of natural language processing technology to hasten the proposed processes was investigated. Two case studies were selected to test and demonstrate the potential of the novel approach, the first being an investigation into material selection for a squash ball, and the second being automotive in nature concerned with combining steering and braking systems. The processes and methods indicated their potential value, especially in the automotive case study where inconsistences were identified that could have otherwise affected the successful integration. This capability, combined with the verification stages, improves the confidence of any model and simulation integration. The NLP proof of concept software also demonstrated that such technology has value in the automation of integration. With further testing and development there is the possibility to create a software package to guide engineers through the difficult task of virtual testing. Such a tool would have the potential to drastically reduce the time to market of complex products.