20 research outputs found

    Taguchi Loss Function for Varus/Valgus Alignment in Total Knee Arthroplasty

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    Methods of designing equipment to improve quality have been developed by Taguchi. A key feature of these methods is the development of loss function, which quantifies the financial cost (loss) resulting from deviations from target dimensions. Total knee arthroplasties can fail due to prosthetic component malalignment. A Taguchi loss function for varus/valgus alignment of the prosthesis and revision rates was developed. Six studies were identified from a comprehensive literature search. Varus and extreme valgus alignments correlated with an increased percentage of prosthetic failure. A loss function of L( y) = 326.80y2,whereywasdeviationfromidealvarus/valgusangle,wasdetermined.TheexpectedlossfunctionwasEL=326.80y2 , where y was deviation from ideal varus/valgus angle, was determined. The expected loss function was EL=326.80yÂŻ2+s2 , where yÂŻ was the mean deviance from the ideal varus/valgus angle and s2 was the variance in varus/valgus angle. This loss function was used to estimate the cost savings of using computer-assisted surgical navigation in total knee arthroplasty (TKA). The average savings of a navigated TKA versus a conventional TKA, based on the expected loss equation derived from the Taguchi loss function, was $2,304 per knee. The expected loss function derived here can serve as a tool for biomedical engineers seeking to use Taguchi quality engineering methods in designing orthopaedic devices

    Parametric design optimisation of proximal humerus plates based on finite element method

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    Optimal treatment of proximal humerus fractures remains controversial. Locking plates offer theoretical advantages but are associated with complications in the clinic. This study aimed to perform parametric design optimisation of proximal humerus plates to enhance their mechanical performance. A finite element (FE) model was developed that simulated a two-part proximal humerus fracture that had been treated with a Spatial Subchondral Support (S3) plate and subjected to varus bending. The FE model was validated against in vitro biomechanical test results. The predicted load required to apply 5 mm cantilever varus bending was only 0.728% lower. The FE model was then used to conduct a parametric optimisation study to determine the orientations of inferomedial plate screws that would yield minimum fracture gap change (i.e. optimal stability). The feasible design space was automatically identified by imposing clinically relevant constraints, and the creation process of each FE model for the design optimisation was automated. Consequently, 538 FE models were generated, from which the obtained optimal model had 4.686% lower fracture gap change (0.156 mm) than that of the manufacturer’s standard plate. Whereas its screws were oriented towards the inferomedial region and within the range of neck-shaft angle of a healthy subject. The methodology presented in this study promises future applications in patient-specific design optimisation of implants for other regions of the human body
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