Design methods for quality generally help to improve quality over time, but do not consider change of system performance over time, resulting from degradation in components. As design methods for quality over time (performance reliability), which minimizes effects of unavoidable component degradations as well as component variations on system performance change, system model-based sampling methods using Monte-Carlo simulations have been used. But, there are main concerns related to computational efficiency and optimization in applying the sampling methods. To overcome the concerns, we propose a non-sample method for quality over time. Based on the proposed method, the process of allocating design parameters, which could minimize the noise effects with the consequence that both quality and performance reliability are optimized, is discussed. Reliability metrics such as mean time to failure and standard deviation of time to failure are optimized simultaneously for reliability improvement. Desirability functions for the metrics are introduced to perform the simultaneous optimization. The proposed method is applied to an electrical system design and compared to a sampling based design method.
This paper proposes a way to predict electrical lifetime of a relay using Accelerated Life Testings (ALTs). The relay of interest mounting on printed circuit boards is usually under an inrush current stress. The inrush current is generated and accelerated through controlling a lamp switching device in the ALT. We find that the dominant failure mechanism under high levels of inrush current would be contact welding in the contact surface of the relay and the contact welding process is accelerated according to increase in inrush current. The electrical lifetime model based on Inverse Power Law in term of inrush current is proposed, and parameters characterizing relay's lifetime distribution are statistically estimated using ALTA 6 PRO software.
Information processing has been thought of as a key to ubiquitous systems. Operating systems composing ubiquitous systems are also important since ubiquitous systems do not provide desired performance when the operating systems fail. Bluetooth module becomes a critical item for these operating systems. Thus, accurate reliability estimation of the module under various environmental conditions is required for profitable ubiquitous system development. This paper shows quantitative reliability evaluation results of a Bluetooth module through extending previous qualitative methods limited to structure reliability tests and solder joint reliability tests for Bluetooth modules. Accelerated Life Testing (ALT) of the modules using temperature difference in temperature cycling as an accelerated stress was conducted for quantitative reliability evaluation under field environment conditions. Lifetime distribution parameters were estimated using the failure times obtained through the ALT, and then Coffin-Manson model was implemented. Results of the ALT showed that the failure mode of the modules was open and the failure mechanisms are both crack and delamination. The ALT reproduced the failure mode and mechanisms of failed Bluetooth modules collected from the field. Further, a quantitative reliability evaluation method with respect to various temperature differences in temperature cycling was proposed in this paper. B10 lifetime of the module for the temperature difference 70oC using the proposed method would be estimated as about 4 years.
The configuration of a musculoskeletal (MS) system is closely related to the individual motions of the human body. Many researches have been focused on evaluating the associations between the MS configuration and the individual motion using patient-specific MS models, but it still remains a challenging issue to accurately predict the motion by differed configurations of the MS system. The main objective of this paper is to predict the changes of a patient-specific gait by altering the geometric parameters of the hip joint using function-based morphing method (FBM). FBM is suitable for motion analysis since this method provide a robust way to morph a MS model while preserving the biomechanical functions of the bones. Computed-muscle control technique is used to calculate the muscle excitations to reproduce the targeted motion within a digital MS model without the motion-captured data. We applied this approach to a patient who has an abnormal gait pattern. Results showed that the femoral neck length and the angle significantly affect to the motion especially for the hip abduction angle during gait, and that this approach is suitable for gait prediction.
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