دانلود رایگان مقاله انگلیسی توانا سازی آگاهی از وضعیت با مدیریت رویداد زنجیره تامین - الزویر 2018

Abstract

Supply chain event management exploits synergies between IT and logistics and refers to the set of methods and technologies used to efficiently integrate events from all actors and processes of the supply chain. In the context of supply chain event management, we examine how events can be used to leverage situation awareness. In our approach, situation awareness is facilitated by providing the capability to detect situations, which are represented as correlations between simple events, complex events and supply chain objects (e.g., suppliers, 3PL companies, retailers and material resources). We introduce a two-phase event correlation method which first correlates simple events into complex events and then events with supply chain objects. We describe how the proposed model has been implemented in a software framework and we conduct evaluation tests to examine its situation detection capabilities.

Conclusion and Further Work

Data intensive supply chain processes generate a plethora of events that deliver useful information to supply chain participants. The management of such events, especially of exception events, and the reaction to them is the main objective of SCEM. In this paper, we designed and implemented an SCEM framework that is capable of detecting and processing events from different stages of the SC, correlating events within an extended time window and offering situation awareness capabilities that go beyond those of existing SCEM systems. To achieve this, we incorporated methods and technologies from CEP and graph databases under a SOA approach. With the proposed framework, situation awareness is facilitated with situation detection capabilities and achieved through the delivery of transparent information via correlations between events and between events and SC objects. Such information reveals the state of the SC in time and space and can be useful for supporting decision making and for coordinating actions by supply chain participants with the final aim to improve SC effectiveness and efficiency. We implemented and evaluated the framework using a number of SC scenarios. We concluded that the framework is capable of correlating events produced from different SC objects and detecting more than the 70% of situations in the SC, in a variety of time windows. We can therefore argue that the framework supports our research objectives and is in synergy with the core requirements and functionalities of an SCEM system. The key characteristics of our framework are adaptability to dynamic SC conditions, scalability with respect to number and variety of events, as well as easy technology integration using widely adopted standards such as BPEL and Web Services. The graph database utilised proved to be highly useful for event correlation and situation detection because of the way it stores events and its capability to execute complex, two or more leveldeep queries, as required for event correlation and ultimately situation detection.