Automation of input data to discrete event simulation for manufacturing: A review

Abstract

Discrete event simulation (DES) is a well-established decision support tool in modeling work flows in manufacturing industry. But, there are an amount of practical and financial obstacles that deter the employment of this technology in industry. One of the main weaknesses of operating DES is the costs spent on collecting and mapping input data from different enterprise data resources into a DES model. Another issue is the cost of integrating simulation applications with other manufacturing applications. These barriers hinder the automated input of data into DES models and as a result deter use of real-time DES in manufacturing. This review presents the existing research studies in the literature that address the above issues, demonstrating in parallel the already implemented concepts. The scope of this review is to provide an overview of the input data phase, focusing on its automation and motivating researchers to re-examine this phase by highlighting future research directions.