Unit load storage systems are pervasive throughout global supply chains. Significant reductions in their automation costs could have significant economic impact. A new alternative to traditional crane-based automation uses flexible autonomous vehicles in storage and retrieval operations. This technology has not significantly penetrated commercial markets for warehouse automation due to a lack of design tools for evaluating its performance. This precludes direct comparisons of autonomous vehicle technology with crane-based technology in the pre-engineering or “design conceptualization” stage of system development where key technology selection decisions are made. To address this problem, this chapter proposes computationally efficient cycle time models for Autonomous Vehicle Storage and Retrieval System that use scalable computational procedures for large-scale design conceptualization. Simulation based validation studies suggest that the models produce high accuracy. The procedure is demonstrated for over 4,000 scenarios corresponding to enumeration of the design spaces for a range of sample problems.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 email@example.com
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 firstname.lastname@example.org