Productivity analysis in a robotic cell

• Published in: International journal of production research Vol. 47; no. 23; pp. 6651 - 6662
• Main Authors: Shafiei-Monfared, S., Salehi-Gilani, K., Jenab, K.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis Group 01.12.2009; Taylor & Francis; Taylor & Francis LLC
• Subjects: Applied sciences; cellular manufacturing; Comparative analysis; Computer science; control theory; systems; Control theory. Systems; cycle time; Exact sciences and technology; flow-graph; Inventory control, production control. Distribution; Manufacturing cells; Operational research and scientific management; Operational research. Management science; Operations research; Process control. Computer integrated manufacturing; productivity analysis; robotic cell; Robotics; Robots; simulation; Stochastic models; Studies; cycle time; simulation; Processing time; productivity analysis; Stochastic process; Modeling; Robotics; Data flow; Cellular manufacturing; robotic cell; Fluence graph; flow-graph; Localization; Deterministic approach; Sequencing; Single machine; Completion time; Execution time; Productivity; Script; Probabilistic approach; Unloading; Graph flow; Gripper; Robot; Dynamic load
• ISSN: 0020-7543; 1366-588X
• DOI: 10.1080/00207540802372298

In this paper, we study the productivity advantage of a variety of scenarios in a robotic cell by comparing their cycle times. The robotic cell is made up of several machines and a single gripper robot in the centre of the cell, which loads, unloads and moves the parts. Considering deterministic robot travelling, loading and unloading time elements and stochastic part process time element, this paper focuses on examining the scenarios composed of the single part type part sequencing methods and the robot moves in a cell. First, the decrease (increase) virtual robotic cell, in which its machines are virtually arranged in order of processing time regardless of their physical location, is introduced to calculate the cycle time. Second, a flow-graph based model is developed to analyse the cycle times for the scenarios when the part processing time element is stochastic. A robotic cell composed of three machines and a robot in the centre of the cell is used as a base example throughout the paper to illustrate the application of the models.