Portal de Periódicos da CAPES

Stochastic modelling with applications

2020; Oxford University Press; Volume: 32; Issue: 1 Linguagem: Inglês

10.1093/imaman/dpaa018

1471-6798

Lirong Cui, Haitao Liao,

Statistical Distribution Estimation and Applications

This is the special issue for the Third International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operations Management held in Beijing, 28–31 May 2019. The symposium provides a forum for researchers and practitioners in their respective fields of expertise to exchange new ideas and share the latest results on stochastic modelling in reliability engineering, life science and operations management, which has been an important focus of the journal for a number of years (Mamon et al., 2020). The symposium was initiated by several Israeli professors in 2005. The topic of this special issue, including five research articles, is mathematical models for product reliability analysis, service logistics and sales. As design and technology advance at a fast pace, modern products are becoming more and more complex while pushing stakeholders to effectively evaluate product reliability, sales and service and develop warranty and maintenance plans. The five articles present a number of innovative stochastic process models, optimization models and solution methods to overcome the related challenges. Specifically, Dong and Cui studied a Wiener process model with piecewise linear drifts for a two-stage degradation process in a dynamic environment. The modelling method can be used for reliability evaluation, residual life prediction and maintenance optimization for a system experiencing two-stage degradation in a dynamic environment. Ruiz, Pohl and Liao investigated the use of Bayesian degradation modelling for spare parts inventory management and proposed a stochastic dynamic programming approach to minimize the expected spare parts inventory cost for a fixed planning horizon. The study provides a new approach based on Bayesian analysis to spare parts inventory management and shows useful managerial insights into the sensitivity of the optimal solution to the changes of prior assessments and cost structure. Wang, Zhu and Du developed a mathematical model to study the optimal preventive maintenance (PM) strategy under a two-dimensional stair-case warranty policy considering both age and usage of a product. Their study assists decision makers in determining the optimal PM strategy to minimize the cost of warranty and in shifting from a traditional warranty policy to the stair-case policy for cost reduction. Shen, Zhang, Ma and Lin developed a model to study the reliability of a system with a main component subject to random environmental shocks and under the protection of several auxiliary components. The proposed opportunistic maintenance strategy takes the failure of the main component as an opportunity to inspect and replace the auxiliary components, which overcomes challenges in estimating system reliability and optimizing maintenance plans due to the complexity of dependence between different types of components. Fu, Gu, Xie, Ye and Cao developed dynamic game models in four dual-channel e-retail structures to study pricing strategies and channel preference for manufacturers. Considering different combinations of open and self-support e-platform, this work provides interesting insights into third-party e-platforms and their impact on e-channels. Overall, the new mathematical developments and ideas addressed in these articles will open new directions for future research on stochastic processes, optimization and their applications in reliability modelling, warranty, service logistics and supply chain management, continuing the tradition of this journal for publishing developments in the mathematics of operational research (Fliege and Glazebrook, 2019). In particular, graduate students, researchers, practitioners and industrial stakeholders will benefit from these and further developments.