Stochastic cycle time analysis in robotic cells

Abstract

The purpose of this study is to analyse the cycle time in a single part type robotic cell. The robotic cell is made up of several machines and a single gripper robot that loads, unloads the machines and moves the part between machines. The cell can be classified into flow- and open-shops based on the part sequence and robot move. When number of machine is increased, the cycle time analysis in a robotic cell can lead to an NP-complete problem, which remains a challenge in existing literature. In addition, the problem complication rise by having stochastic processing time in the cell. In this study, we have developed a formula for decrease (increase) structure that part processing sequence is based on decrease (increase) order of manufacturing process time. This leads to a virtual robotic cell, which its machines are virtually arranged in order of processing time regardless of their physical location. In addition, using flow-graph concept, a model is developed to calculate the cycle time of a robotic cell where the part processing time element is stochastic. This model provides parametric results for expected value of and variance of the cycle time, which can be used for evaluating the productivity of the scenarios.