Risk management in cyber-physical distribution center for e-commerce cross-border logistics

Abstract

Maintenance is the main part of product lifecycle management (PLM). Thus, the solution suitable for equipment maintenance can be easily extended to other industry equipment maintenance processes. While most of the current maintenance service management only rely on empirical experience, ignoring the dynamic information uncertainties and lacking flexible reactions hinder the effectiveness of the maintenance task assignment. Moreover, without a systematic and dynamic consideration of various related parameters, more limitations are exposed to current approaches. As such, it is of great importance to automate the maintenance process, consider all related parameters and cope with the dynamic uncertainties to endow equipment maintenance processes with smart and fast reaction capability, flexibility, and robustness. Among the first to address this problem, with the help of the Internet of Things (IoT) and cloud technologies, this thesis systematically proposes the real-time Cloud-enabled equipment maintenance service (CEMS). These new technologies can enable real-time equipment status data collection, advanced and proactive response maintenance as well as improved process visibility. By using the proposed CEMS, it results in a significant improvement in processing the equipment fault report, making a quick response, and dynamically assigning the maintenance tasks, enhancing the task management ability of the maintenance center. To achieve the overall aim of this research, three typical scenarios are examined as follows: Scenario Ⅰ: In this scenario, an overview of equipment maintenance service is studied and analyzed. Equipment maintenance service process is an important part of after-sales service, this study has taken a broad view at maintenance service and the corresponding research issues emerging in this field. ScenarioⅡ: In this scenario, a cloud-enabled platform for EMS assignment and control is developed, inspired by an industrial case of lift after-sales maintenance service. The presented cloud-based equipment maintenance service (CEMS) platform integrates various methods and techniques into a suite of applications for EMS assignment and control management, including intelligent inspection, equipment fault information processing, maintenance assignment and maintenance service execution control. Through the cloud computing and IoT technologies, a real-time maintenance service assignment and execution control platform is established. Heterogeneous physical equipment and manpower can be easily traced, tracked, and managed. Scenario Ⅲ: This scenario considers a maintenance service area where the maintenance service department operator needs to designate different kinds of maintenance task to corresponding maintenance service staff/agent. As the volume of maintenance demand increases quickly, the quality, efficiency, and robustness of such task assignment process require comprehensive study and analysis. Therefore, the major challenges of this work are how to the assign the maintenance task to the most suitable maintenance team. We propose an efficient assignment mechanism to minimize the total maintenance cost by dynamically assigning each task with most appropriate maintenance team. In this dissertation, the cloud enables and real-time advanced receiving, assignment and control problems in equipment maintenance are investigated and related maintenance assign task mechanisms and platform technologies are developed as well. This study of equipment maintenance service shall be of great value not only to researchers who desire to extend their research into this new area but also to practitioners who are interested in equipment fault prognosis by using the real-time equipment operation information.