Knowledge Representation and Decision Support for Managing Product Obsolescence

Fast moving technologies have caused high-tech components to have shortened life cycles, rendering them obsolete quickly. Technology obsolescence creates significant problems for product sectors that use components that are only available for a short period of time for manufacture and maintenance of long field-life systems. Technology obsolescence can make design changes of systems prohibitively expensive, and results in high life cycle costs of systems. While the impact and pervasiveness of obsolescence problems are growing, existing tools and solutions are lacking the needed information and knowledge to do much more than focus on reactively managing obsolescence. Current methods and tools are limited by data conflicts and data inexplicitness, incompleteness, and inconsistency.

In response to the drawbacks of current tools, comprehensive knowledge representation that allows information sharing, reuse, and collaboration on obsolescence issues across different organizations is required. Further, decision making tools that can support proactive and strategic obsolescence management are needed. The purpose of this research is to establish an ontology-based knowledge representation scheme for information sharing, reuse, and collaboration on obsolescence issues, and develop decision making models to support proactive and strategic management for overall cost savings in managing obsolescence.

Three primary aspects of this research are investigated. First, ontologies for obsolescence knowledge representation are developed in a systematic way with the use of UML diagrams. The generality of the developed ontology is demonstrated with distinct examples. Diminishing Manufacturing Sources and Material Shortages (DMSMS) obsolescence provides the basis for this study. Second, an ontology-based hybrid approach for integrating heterogeneous data resources in existing obsolescence management tools is proposed. Third, decision support models are developed and formalized, and include the obsolescence forecasting method for proactively managing obsolescence, and the mathematical models to determine the optimal design refresh plan to minimize the product life cycle cost for strategic obsolescence management. Finally, the design of the obsolescence management information system is provided along with a system evaluation methodology.

Ultimately, the research contributes to the field of knowledge representation as well as design for managing product obsolescence.