Automated Storage/Retrieval Systems (AS/RS) are storage systems capable of providing random access to all stored items (Sarker and Babu,1995). AS/RSs are being widely used in the logistics industry (Van den Berg, 2000). Major advantages of AS/RS include high throughput, efficient use of space, high reliability and improvement of safety (Rosenblatt et al., 1993). However, economic factors, such as initial high investment, inflexible layout and fixed storage capacity, force to carefully evaluate system structures (e.g. layout and size of the racks, S/R mechanism, number of the spans and of the levels) and operational policies (e.g. allocation of storage cells and scheduling of the tasks). The performance of an Automated Storage/Retrieval System depends on the storage rack dimension, on the number of cranes and aisles, and on the applied control policies such as the dwell point position, the material clustering, etc. The dwell point position of crane is the location where the stacker lies when it is inactive. Different strategies about dwell point result in significant gaps in term of performance (e.g. throughput and costs). The presented research deals with the optimal dwell point evaluation considering a large set of conditions, both concerning the physical AS/RS configuration (e.g. number of spans, number of levels, etc.) and the characteristics of the requested mission profile (in terms of inter-mission time and of dual or single command). In this paper, results dealing with the random storage assignment are presented. Considering different dwell point strategies, applied to different AS/RS configuration (in terms of number of spans, number of levels, statistical distribution of the requested missions, etc.) a model supported by a software platform has been developed. For each instance 1000 runs have been executed and the following parameters have been evaluated: - travel time: the time spent by a stacker crane to complete a mission (storage/retrieval); - distance traveled: the distance traveled by a stacker crane to complete a mission (storage/retrieval); - idle time: the time that a stacker crane lies in its position, waiting for a requested mission (depending the position on the used policy); - waiting time: the time that a loaded unit must wait for being “served” (stored and/or retrieved) because the stacker crane is employed by another request.
REGATTIERI A., SANTARELLI G. (2011). Innovative policies for the AS/RS design and management. BRUSSELS : European Logistics Associations.
Innovative policies for the AS/RS design and management
REGATTIERI, ALBERTO;
2011
Abstract
Automated Storage/Retrieval Systems (AS/RS) are storage systems capable of providing random access to all stored items (Sarker and Babu,1995). AS/RSs are being widely used in the logistics industry (Van den Berg, 2000). Major advantages of AS/RS include high throughput, efficient use of space, high reliability and improvement of safety (Rosenblatt et al., 1993). However, economic factors, such as initial high investment, inflexible layout and fixed storage capacity, force to carefully evaluate system structures (e.g. layout and size of the racks, S/R mechanism, number of the spans and of the levels) and operational policies (e.g. allocation of storage cells and scheduling of the tasks). The performance of an Automated Storage/Retrieval System depends on the storage rack dimension, on the number of cranes and aisles, and on the applied control policies such as the dwell point position, the material clustering, etc. The dwell point position of crane is the location where the stacker lies when it is inactive. Different strategies about dwell point result in significant gaps in term of performance (e.g. throughput and costs). The presented research deals with the optimal dwell point evaluation considering a large set of conditions, both concerning the physical AS/RS configuration (e.g. number of spans, number of levels, etc.) and the characteristics of the requested mission profile (in terms of inter-mission time and of dual or single command). In this paper, results dealing with the random storage assignment are presented. Considering different dwell point strategies, applied to different AS/RS configuration (in terms of number of spans, number of levels, statistical distribution of the requested missions, etc.) a model supported by a software platform has been developed. For each instance 1000 runs have been executed and the following parameters have been evaluated: - travel time: the time spent by a stacker crane to complete a mission (storage/retrieval); - distance traveled: the distance traveled by a stacker crane to complete a mission (storage/retrieval); - idle time: the time that a stacker crane lies in its position, waiting for a requested mission (depending the position on the used policy); - waiting time: the time that a loaded unit must wait for being “served” (stored and/or retrieved) because the stacker crane is employed by another request.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.