Hyper Space Exploration A Multicriterial Quantitative Trade-Off Analysis for System Design in Complex Environment

Successful engineering requires environmentally adapted procedural and architectural approaches. While dealing with complicated issues has become an engineering standard, mastering uncertainties in complex environment is still a major issue. Global trends, such as an increasing rate of disruptive (non-evolutionary) technology changes or merging of technology fields, however, enforce the importance of complex problems dominated by a lack of engineering knowledge.This paper presents a novel approach of system design methodology in a complex environment called Hyper Space Exploration (HSE). The HSE approach combines methods of virtual prototyping with those of design of virtual experiments based studies for statistical learning. Virtual prototyping allows an early feedback on system behavior with a proof-of-concept prior implementation. Statistical learning enables system architects to systematically build up the space of potential solution alternatives, model the effects of design and use case variables on target indicators in complex territory, quantity target indicator trade-offs, and finally identify Pareto-optimal system solutions.The first part of the paper characterizes engineering challenges in complex environment. Section two presents the HSE methodology with its two major constituents work flow (part A) and tool chain (part B). Section three outlines first successful HSE applications that have already proved HSE capabilities and its universality. Final section four gives an outlook to further HSE applications as well as methodological future HSE extensions.