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Successful engineering requires environmentally adapted procedural andarchitectural approaches. While dealing with complicated issues has become anengineering standard mastering uncertainties in complex environment is still amajor issue. Global trends, such as an increasing rate of disruptive technologychanges or merging of technology fields, however, enforce the importance ofthis complex habitat. Missing experience in unknown technological territoryfaces engineers with two questions of paramount importance: 1) How can the bestarchitectural solution within the space of potential alternatives beidentified? 2) How can a proof-of-concept for considered solutions priorimplementation be provided? Mastering lack of knowledge related risks anduncertainties states one of the most prominent tasks in according projects. Thepaper presents a novel methodology of system design in complex environmentcalled Hyper Space Exploration (HSE). The HSE approach combines methods ofvirtual prototyping with those of design of virtual experiments based studiesfor statistical learning. Virtual prototyping allows an early feedback onsystem behavior with a proof-of-concept prior implementation. Statisticallearning enables system architects to systematically build up the space ofpotential solution alternatives, model the effects of design and use-casevariables on target indicators in complex territory, quantify target indicatortrade-offs and finally identify Pareto-optimal system solutions. The first partof the paper characterizes engineering challenges in complex environment.Section two presents the HSE methodology with its two major constituents workflow and tool chain. Section three outlines first successful HSE applicationsthat already proved its capabilities and universality. Final section four givesan outlook to further HSE applications as well as methodological future HSEextensions.

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