Process repositories: Principles and experiences

Abstract

Creative, ill-structured processes such as requirements engineering, industrial research, or design of new products share a number of properties that make it difficult to support them by current workflow or repository technology. For these processes, methods are only partially known. There is a heavy need, but little support for effective information exchange and conflict handling in the often large and heterogeneous design teams. Due to this lack of understanding and cooperation support, there is a lot of trial, error, and backtracking, often without a significant learning curve, which makes these processes extremely unpredictable and expensive. The talk identifies three key players in such a setting: the actual (knowledge) workers, their managers or process planners, and the methodology researchers which insert generic advice into process definitions. Based on an analysis of their interaction patterns, we work out precisely where current technologies fail, and identify repository-centered strategies for improving the situation.

Process repositories are a means to coordinate the interaction of process definition, process planning, process generation and customization, process guidance, process tracing, and experience-based process improvement. The integration of all these tasks implies a specific architecture (components and communication patterns). It also requires rich but computer-supportable conceptual modeling formalisms.

Architecture, modeling languages, and tool integration strategies of several process repositories based on the conceptual modeling environment Concept-Base are presented for illustration. Experiences from application projects in industrial engineering, software requirements engineering, pharmaceutical research, and chemical engineering substantiate the concepts and point out directions for further research and development.

This work was supported in part by the Commission of the European Communities under ESPRIT Basic Research Project 6353 (NATURE) and by the German Federal Ministry of Research and Technology (BMFT) under project PFT-92017-02QF30041 (WibQuS).