Collaborative design using solution spaces

Complex design tasks from many domains such as mechanical, electrical and civil engineering make the collaboration of many partners unavoidable for several reasons: knowledge from various experts is necessary, often more than one enterprises are involved and deadlines impose concurrent engineering. However, collaboration also leads to certain in-conveniences such as information loss and misunderstandings during communication and iterative negotiation when suggested partial solutions for sub-tasks conflict. Moreover, major problems are related to management of changes and ensuring design consistency. This thesis conjectures that many of these problems are caused by the use of single solutions during negotiation. Currently, project partners assign single values for sub-tasks and then proceed, often after tedious negotiations with other partners, to integrate these partial solutions into solutions for the whole project. While partners determine one single solution for a sub-task, much information about potential alternatives is lost and premature decisions are taken. The integration of partial solutions then often leads to artificial conflicts which are not due. to incompatible design goals but arise because information about possible compromises is no longer available. Consequently, many changes usually occur during negotiation about parameter values and much, effort must be invested in. order to keep the design consistent. Therefore, we investigate the use of solution spaces instead of single solutions. When solution. spaces are used during negotiation, more information about alternatives is avail-able, premature decisions are avoided and thus, no artificial conflicts arise. Moreover, since project partners provide formal information about project requirements, real conflicts between diverging project goals can be detected. However, the implementation of a collaboration system using solution spaces is far from trivial, since in general the computation of exact solution spaces is intractable. We employ constraint satisfaction techniques in order to calculate solution space approximations. Constraints arise naturally in many fields of engineering and are therefore suited to formally express project requirements. Using constraints on design parameters, project partners can describe large families of acceptable solutions. Moreover, descriptions using constraints can be easily adapted to changes in the project's context. When project descriptions in terms of constraints are available, constraint satisfaction techniques such as consistency can be employed to provide computational support during collaboration. Consistency algorithms use local inconsistencies to prune regions from the original search space where no solution can be expected and thus provide approximations of solution spaces. Algorithms which ensure low degrees of consistency provide a rough over-estimation of the solution space but have low complexity, while algorithms which enforce high d