No abstract

The number of samples available for testing of a newly developed item is quite small, and only limited reliability information is available in many real cases. Therefore, a multi-purpose test plan is essential for reliability estimation. To reflect real product development scenarios, this study presents a practical lifetime estimation strategy based on a partially step-stress-accelerated degradation test (PSSADT) with three stress levels. The PSSADT plan assumes that the degradation path follows a Wiener process and that the cumulative exposure model holds. The proposed test plan determines the stress level in the final loaded step that minimizes the asymptotic variance of the maximum likelihood estimator of the qth quantile of the lifetime distribution under the use condition. Finally, the test scenario, which includes the necessary validity check of the acceleration model, is illustrated with an example.

Abstract:Stepwise benchmark target selection in data envelopment analysis (DEA) is a realistic and effective method by which inefficient decision-making units (DMUs) can choose benchmarks in a stepwise manner. We propose, for the construction of a benchmarking network (i.e., a network structure consisting of an alternative sequence of benchmark targets), an approach that integrates the cross-efficiency DEA, K-means clustering and context-dependent DEA methods to minimize resource improvement pattern inconsistency in the selection of the intermediate benchmark targets (IBTs) of an inefficient DMU. The specific advantages and overall effectiveness of the proposed method were demonstrated by application to a case study of 34 actual container terminal ports and the successful determination of the stepwise benchmarking path of an inefficient DMU.

No abstract

Reverse logistics include all operations related to the reuse of products and materials. In this study, we focus on collection, which is the first operation of reverse logistics, and on the strength of using the sensor data and the concept of Industry 4.0. Previously, the collection activities of electronic wastes (e-wastes) was conducted by a fixed schedule without consideration of the fulfillment level of the collection boxes. However, due to the progress of IoT(internet of things) technology and sensor technology, it is possible to consider the fulfillment level of the collection boxes in order to make the collection schedule. To utilize the sensor data and IoT technology in reverse logistics, a collection signal algorithm is required to treat the rate of fulfilment of collection boxes. However, the collection signal algorithm for the disposal of small and medium (S&M)-sized e-wastes have not yet been developed in South Korea. This study uses a collection box to develop the collection algorithm based on an experimental design method with multiple sensors. The proposed algorithm can be utilized to solve the current collection problems and to save logistics costs. Furthermore, proper collection of e-wastes will lead to more recycling activities, which can further create and sustain a safer environment on Earth.