Abstract
Queueing is a common phenomenon in various stages of manufacturing systems and some other organisations. Queueing usually reduces the time required by managers and manufacturers to complete a desired task. The queueing mathematical theory is a viable tool for analysing a waiting line model. This research presents the implementation of robots at the packaging stage of a virtual manufacturing scenario in which mathematical models were used to describe each stage of the manufacturing process. Some suitable parameters and operating conditions were assumed, and the Newton-Raphson iteration formula was implemented for numerical analysis of the models. Simulation was carried out to achieve optimal values that could yield efficient productivity. The optimisation process gave an outcome that adequately showed how queueing can be managed in the packaging stage in an advanced manufacturing environment.
Highlights
Performance optimisation during a manufacturing process is an essential tool that supports manufacturers in achieving a cost-effective manufacturing system
The models best describe the behaviour of the products during the arriving stage and the packaging stage of the virtual manufacturing scenario
Queueing is a complicated phenomenon that has a great impact on the throughput rate in an advanced manufacturing environment
Summary
Performance optimisation during a manufacturing process is an essential tool that supports manufacturers in achieving a cost-effective manufacturing system This process involves proper monitoring and modification of some operating conditions that can help to enhance productivity. Adequate control of the waiting time has become a major concern among manufacturers: waiting time results in queueing during manufacturing, as a process or product spends more than the required time waiting for an activity or process to be completed. It is important, to understand how to deal effectively with problems associated with queues resulting from products awaiting server operation. The outcome from the study presents a suitable model and mathematical expression that can be useful to manufacturers making decisions in the early stage of manufacturing
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