Simulation-based regression analysis for the rack configuration of an autonomous vehicle storage and retrieval system

• Published in: International journal of production research Vol. 48; no. 21; pp. 6257 - 6274
• Main Authors: Ekren, Banu Yetkin, Heragu, Sunderesh S.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis Group 01.11.2010; Taylor & Francis; Taylor & Francis LLC
• Subjects: agent based systems; Applied sciences; automated manufacturing systems; Automated storage retrieval systems; Autonomous; Autonomous vehicles; Computer programs; Computer science; control theory; systems; Computer simulation; Control theory. Systems; Exact sciences and technology; Inventory control, production control. Distribution; Kraftfahrzeug; Lagerhaltungsmodell; Lagertechnik; Linear inference, regression; Mathematical analysis; Mathematical functions; Mathematical models; Mathematics; Operational research and scientific management; Operational research. Management science; optimisation; Optimization techniques; order picking methods; Probability and statistics; Process control. Computer integrated manufacturing; production management; queuing networks; Queuing theory. Traffic theory; Racks; reconfigurable manufacturing systems; Regression; Regression analysis; Regressionsanalyse; Retrieval; Sciences and techniques of general use; shop floor control; Simulation; Software; Statistical analysis; Statistics; Studies; Vehicles; warehouse design; warehousing systems; Warteschlangentheorie; France; Automated storage retrieval system; agent based systems; queuing networks; Automated guided vehicle; Queueing network; Modeling; Waiting time; automated manufacturing systems; optimisation; Warehousing; Regression function; Reconfigurable architectures; Completion time; shop floor control; Production system; order picking methods; warehousing systems; Script; Statistical analysis; Storage time; Process control; Order picking; warehouse design; Regression analysis; Transaction processing; Production management; Multiagent system; Regression model; Time average; reconfigurable manufacturing systems; Firm
• ISSN: 0020-7543; 1366-588X
• DOI: 10.1080/00207540903321665

In this paper, a simulation-based regression analysis for the rack configuration of an autonomous vehicle storage and retrieval system (AVS/RS) is presented. The aim of this study is to develop mathematical functions for the rack configuration of an AVS/RS that reflects the relationship between the outputs (responses) and the input variables (factors) of the system under various scenarios. In the regression model, we consider five outputs: the average cycle time of storage and retrieval transactions, the average waiting time for vehicle transactions, the average waiting time of vehicles (transactions) for the lift, the average utilisation of vehicles and the average utilisation of the lifts. The input variables are the number of tiers, aisles and bays that determine the size of the warehouse. Thirty regression models are developed for six warehouse scenarios. The simulation model of the system is developed using ARENA 12.0 commercial software and the statistical analyses are completed using MINITAB statistical software. Two different approaches are used to fit the regression functions-stepwise regression and the best subsets. After obtaining the regression functions, we optimise them using the LINGO software. We apply the approach to a company that uses AVS/RS in France.