PrOntoDecide - Product development ontology supporting the provision of decision-relevant knowledge for multicriteria evaluation of decision alternatives

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Due to the growing complexity of modern products, new challenges arise for product developers, whose central task is to fulfill the requirements demanded by the market. These requirements concern specific properties, which have to be fulfilled by the product and ensured through related product characteristics. Due to the increase of product complexity, various relations between the characteristics and properties occur, which makes their consideration more difficult. Changes in product characteristics lead to different properties of the whole system, which in the case of complex relation networks result in unmanageable and often undesirable property changes. The effects of this include cost-intensive iterations for the adaptation to the demanded properties or even the failure of products in the market. For this reason, these influences have to be identified already during development and then taken into account during multi-criteria evaluation of decision alternatives. For this purpose, consistent decision models are required that contain these relations. In interdisciplinary product development, these relations as well as the relevant information and data originate from domain-specific models and are available as heterogeneous databases. This results in challenges regarding the provision of decision-relevant knowledge for multi-criteria decision processes and models.Motivated by these challenges, the objective of the proposed research project is to develop fundamental findings about the formalization and provision of context-specific knowledge in the fields of requirements-based, multi-criteria decision making. Ontologies offer a suitable method for the formalization and provision of context-specific knowledge, therefore, the main objective of the project has to be achieved with a decision-supporting product development ontology (PEO). Within the ontology development the own preliminary work from the first phase of the project has be considered, which provides the necessary fundamentals regarding computer aided multi-criteria decision making based on all product requirements. The extension of the PEO through data and knowledge integration from heterogeneous sources enables product developers to provide relevant decision knowledge consistently and reduces the effort for manual provision. Verification of the developed PEO requires new approaches for defining suitable queries. In summary, the research project focuses on scientific findings regarding the applicability and usability of ontologies for an efficient support of multi-criteria decision making.