Queuing Network Modelling for improved Decision Support in Manufacturing Systems

In order to remain competitive in the digital transformed economic world, the perfect match of supply and demand through supply chain management and operations management is of essential importance. Productivity, quality, costs and customer satisfaction are of major interest for companies. Programs aimed at improving these factors are often launched under the label "Operational Excellence" (OPEX). Nowadays, companies use elements of different management systems and concepts simultaneously. These management systems provide fundamental insights for OPEX. The main challenge is to combine these systems for developing the ability to react efficiently to market volatility. This includes quick response times to emerging customer requirements and the adaption of new technologies. The aim of this work is to propose a decision support systems that can achieve operational excellence. For this purpose the application of rapid modeling (queuing networks modeling) is promising. The core components of the proposed OPEX system are based on a queuing networks modeling approach which can help to examine the behavior of the supply chain, enables a faster evaluation of different scenarios and offers the opportunity to reflect changes in the real world system close to real-time. The performance of a manufacturing system can be further improved by automated decisions that use innovative algorithms and intelligent software applications deriving from the knowledge in the field of production and operations management.