Infoscience

Thesis

Knowledge-based decision support for improving the adaptive product development process

The product development process (PDP) is a complex process encompassing many very diverse activities, and involving a fairly big number of actors, spread across different professions, teams and companies. In today’s product development, more often than not these individual actors and groups of actors perform their duties almost isolated from the others, using their own methods and software tools to achieve their respective local goals within the overall development effort. Even though much of the same knowledge about the product is used in different phases and tasks of the PDP, in most cases it is not shared or structured in any formal manner, except locally in some cases. Instead, it is exchanged through meetings of the responsible people or other informal means. Current PDP support ICT solutions are focusing on specific parts of the process, but there is no integrated approach that includes product data and services required for the whole PDP, despite the knowledge commonalities shared by its parts and phases. Apart from that, information about the process itself (such as how the tasks are defined, planned and organized, which changes are made to a plan before and during the execution of the tasks, and based on which conditions are these decisions being made), is rarely kept or formally described, relying on the people and their memory. This lack of awareness about the process plans and execution among people responsible for different tasks within PDP leads to misunderstandings, collisions and delays arising much more often than necessary, and work being done in a suboptimal fashion. Having both the product and process knowledge captured, managed, shared and reused in a standardized manner would aid the process tremendously, by improving the collaboration between all the parties involved, making sure that the entire process and its individual tasks are executed at the right moment, with the correct resources, having minimal negative effect on the others, and with the best possible performance. This thesis presents an approach to reduce the impact of these issues, based on a PDP knowledge management and decision support software system. Ontologies, description logic and Semantic Web technologies are used to formalize the knowledge, enable reasoning and additional fact inferencing, as well as to make it easier to access by both machine and human actors in the PDP. As a first step, a general model of the PDP was created, based on detailed descriptions of product development processes in six companies from three different industry branches (aerospace, automotive and home appliances). In accordance with the model, a broad PDP ontology was designed and implemented, as part of a collaborative effort with other research institutes and companies. The ontology provides the formal structure for the knowledge encountered during the PDP by describing the relevant classes, properties and relations. In addition, the architecture of the ontology-centered knowledge base and the adjoining support software framework is described, showing relevant implementation details and features for supporting PDP planning and execution. They give insight into the benefits of applying the Semantic Web technologies in the product development domain, and how they provide the basis for improving the PDP. The benefits are reflected in shorter PDP project times and better results, which come from knowledge capture and reuse, improved collaboration, faster reaction and [...]

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