Mathematical Modelling and Simulation of Throughput in a Robotics Manufacturing System

Abstract

The paper presented the impact of robots in a pick and place task in an advanced manufacturing environment. The study seeks to address the problem faced by manufacturers trying to obtain optimal throughput when a robot is available to perform a difficult task. Classical models with assumed parameters were used to describe a scenario of a pick and place task in a virtual manufacturing environment. The models were studied and analyzed using Queuing theory and the renewal reward theorem. Various expressions were developed, and the engineering equation solver (EES) was used for the numerical computation. The numerical results were simulated using MATLAB to achieve the desired results and illustrated graphically. An equation that can be used to calculate optimal throughput was derived. The outcome of study suggested a model that can be effective when solution to optimal throughput is required during the pick and place task of a robotic line manufacturing system.

Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation

“…It is feasible to offer a simulation module that is based on throughput representations by removing the pre-defined assumption ( Salawu, Bright & Onunka, 2020 ). In this form of design, the entire robotic system’s behaviour is tested, and the entire manufacturing facility is modified.…”