Decision-making in product quality based on failure knowledge

Decision-making in product quality is an indispensable stage in product development, in order to reduce product development risk. Based on the identification of the deficiencies of quality function deployment (QFD) and failure modes and effects analysis (FMEA), a novel decision-making method is presented that draws upon a knowledge network of failure scenarios. An ontological expression of failure scenarios is presented together with a framework of failure knowledge network (FKN). According to the roles of quality characteristics (QCs) in failure processing, QCs are set into three categories namely perceptible QCs, restrictive QCs, and controllable QCs, which present the monitor targets, control targets and improvement targets respectively for quality management. A mathematical model and algorithms based on the analytic network process (ANP) is introduced for calculating the priority of QCs with respect to different development scenarios. A case study is provided according to the proposed decision-making procedure based on FKN. This methodology is applied in the propeller design process to solve the problem of prioritising QCs. This paper provides a practical approach for decision-making in product quality. Copyright © 2011 Inderscience Enterprises Ltd.

Decision support based on genomics:integration of data-and knowledge-driven reasoning

The breadth and depth of available clinico-genomic information, present an enormous opportunity for improving our ability to study disease mechanisms and meet the individualised medicine needs. A difficulty occurs when the results are to be transferred 'from bench to bedside'. Diversity of methods is one of the causes, but the most critical one relates to our inability to share and jointly exploit data and tools. This paper presents a perspective on current state-of-the-art in the analysis of clinico-genomic data and its relevance to medical decision support. It is an attempt to investigate the issues related to data and knowledge integration. Copyright © 2010 Inderscience Enterprises Ltd.

Knowledge sources, innovative activity and the performance of UK new technology based firms

We present an innovation value chain analysis for a representative sample of new technology based firms (NTBFs) in the UK. This involves determining which factors lead to the usage of different knowledge sources and the relationships that exist between those sources of knowledge; the effect that each knowledge source has on innovative activity; and how innovation outputs affect the performance of NTBFs. We find that internal (i.e. R&D) and external knowledge sources are complementary for NTBFs, and that supply chain linkages have both a direct and indirect effect on innovation. NTBFs' skill resources matter throughout the innovation value chain, being positively associated with external knowledge linkages and innovation success, and also having a direct effect on growth independent of the effect on innovation. ©2010 IEEE.

Knowledge sources, innovative activity and the performance of UK new technology based firms

We present an innovation value chain analysis for a representative sample of new technology based firms (NTBFs) in the UK. This involves determining which factors lead to the usage of different knowledge sources and the relationships that exist between those sources of knowledge; the effect that each knowledge source has on innovative activity; and how innovation outputs affect the performance of NTBFs. We find that internal (i.e. R&D) and external knowledge sources are complementary for NTBFs, and that supply chain linkages have both a direct and indirect effect on innovation. NTBFs' skill resources matter throughout the innovation value chain, being positively associated with external knowledge linkages and innovation success, and also having a direct effect on growth independent of the effect on innovation. ©2010 IEEE.