Knowledge processing for concurrent engineering: An evolving challenge in CIM research

As technological tasks in CIM environments become more complicated, the level of intelligence required to automate and integrate these tasks also evolves with increasing complexity. This paper classifies CIM tasks and their required intelligence into facility, data and decision levels, and discusses the automation and integration of those knowledge-intensive CIM tasks at their decision level. Since decision-level tasks are often more abstract than those at the facility and data levels, a systematic approach is necessary to build research programs for the automation of these tasks. This paper will use the decision-level task of concurrent engineering as an example to explain the five-step approach that we have adapted to form our research programs in this evolving area of CIM research. These five steps are: (1) perform analysis of the task and its needed decision-level supports, (2) conceptualize these analysis results into a concise framework, (3) propose a software paradigm for the conceptual framework, (4) identify functional requirements from this paradigm to guide software implementations, and (5) correlate implementation results to identify a fundamental technology. More specifically, the analysis of concurrent engineering tasks in CIM can be found in Section 2. Section 3 explains the conceptualization process which views decision making activities as mappings and loops between a control and performance space. In Section 4, concurrent engineering is modeled as a team problem-solving process participated in by multiple cooperating knowledge sources (MCKS) with overlapping expertise to perform those loops. Several functional requirements are identified from this MCKS model of concurrent engineering and example research activities to address these challenges are described in Section 5. The correlations in Section 6 indicate that the knowledge processing technology, evolved from applied artificial intelligence research, is a fundamental technology for building intelligent systems to support various knowledge-intensive CIM tasks at their decision level.