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.

Failure mechanism of the all-polyethylene glenoid implant

Fixation failure of glenoid components is the main cause of unsuccessful total shoulder arthroplasties. The characteristics of these failures are still not well understood, hence, attempts at improving the implant fixation are somewhat blind and the failure rate remains high. This lack of understanding is largely due to the fundamental problem that direct observations of failure are impossible as the fixation is inherently embedded within the bone. Twenty custom made implants, reflecting various common fixation designs, and a specimen set-up was prepared to enable direct observation of failure when the specimens were exposed to cyclic superior loads during laboratory experiments. Finite element analyses of the laboratory tests were also carried out to explain the observed failure scenarios. All implants, irrespective of the particular fixation design, failed at the implant-cement interface and failure initiated at the inferior part of the component fixation. Finite element analyses indicated that this failure scenario was caused by a weak and brittle implant-cement interface and tensile stresses in the inferior region possibly worsened by a stress raiser effect at the inferior rim. The results of this study indicate that glenoid failure can be delayed or prevented by improving the implant/cement interface strength. Also any design features that reduce the geometrical stress raiser and the inferior tensile stresses in general should delay implant loosening.