Throughput Optimization in Robotic Cells with Input and Output Machine Buffers: A Comparative Study of Two Key Models

European Journal of Operational Research, 2010

Mays Business School Research Paper No. 2012-56

13 Pages Posted: 16 May 2012

See all articles by Inna Drobouchevitch

Inna Drobouchevitch

affiliation not provided to SSRN

Neil Geismar

Texas A&M University - Mays Business School

Chelliah Sriskandarajah

Texas A&M University

Date Written: 2010

Abstract

We consider the problem of scheduling operations in a robotic cell processing a single part type. Each machine in the cell has a one-unit input buffer and a one-unit output buffer. The machines and buffers are served by one single gripper robot. The domain considered is free-pickup cells with additive intermachine travel time. The processing constraints specify the cell to be a flow shop. The objective is to find a cyclic sequence of robot moves that minimizes the long-run average time to produce a part or, equivalently, maximizes throughput. Bufferless robotic cells have been studied extensively in the literature. However, the few studies of robotic cells with output buffers at each machine have shown that the throughput can be improved by such a configuration. We show that there is no throughput advantage in providing machine input buffers in addition to output buffers. The equivalence in throughput between the two models has significant practical implications, since the cost of providing additional buffers at each machine is substantial.

Keywords: robotic cells, input/output, machine buffers, cyclic scheduling

Suggested Citation

Drobouchevitch, Inna and Geismar, Neil and Sriskandarajah, Chelliah, Throughput Optimization in Robotic Cells with Input and Output Machine Buffers: A Comparative Study of Two Key Models (2010). European Journal of Operational Research, 2010; Mays Business School Research Paper No. 2012-56. Available at SSRN: https://ssrn.com/abstract=2061270

Inna Drobouchevitch (Contact Author)

affiliation not provided to SSRN ( email )

Neil Geismar

Texas A&M University - Mays Business School ( email )

Wehner 401Q, MS 4353
College Station, TX 77843-4218
United States

Chelliah Sriskandarajah

Texas A&M University ( email )

Langford Building A
798 Ross St.
77843-3137

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