autonomous vehicle storage and retrieval system

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

Performance comparison of two material handling systems: AVS/RS and

The purpose of this study is to compare the performance of two material handling systems (MHSs) - autonomous vehicle storage and retrieval systems (AVS/RSs) and traditional, crane-based, automated storage and retrieval systems (CBAS/RSs) - with respect to key performance measures. First, the two MHSs are simulated using ARENA 12.0, commercial software, via 198 experiments based on the rack configurations of the warehouses, number of storage and retrieval (S/R) devices and S/R transaction rates. Five performance measures are considered - average flow time, S/R device utilisation, average waiting time in S/R device queue, average number of jobs waiting in S/R device queue and cost. We also complete a paired-t test comparison to find out the best warehouse design based on cost, flow time and utilisation of the S/R devices. An examination of the results, specifically the flow time of the S/R devices, suggests that in many cases the AVS/RS performs better than the CBAS/RS. However, the best design, when the system costs are considered, is obtained with a CBAS/RS

and retrieval system

In this paper, simulation based performance analysis of an autonomous vehicle storage and retrieval system (AVS/RS) is presented. AVS/RS represents relatively a new system for automated unit-load (UL) storage based on autonomous vehicle (AV) technology. This new system consists of AVs, lifts and storage racks. It is implemented at scores of facilities in Europe. The aim of this study is to find out near optimum values for number of AVs and lifts in the system that result in high performance under various pre-defined storage rack configuration scenarios. The storage rack of the system is defined in terms of number of aisles, bays and tiers. We consider seven rack configuration scenarios, ten and nine vehicles per zone and two arrival rates - 450 and 500 pallets/h. The performance measures considered are: average cycle time of storage and retrieval transactions, average utilizations of AVs and lifts. The simulation model of the system is developed using ARENA 12.0, a commercial software. We find that having a large number of lifts (zones) and a large footprint yield better performance. (C) 2011 Elsevier B.V. All rights reserved

networks with low service time variability

In this paper, we present an approximate method for solution of load-dependent, closed queuing networks having general service time distributions with low variability. The proposed technique is an extension of Marie's (1980) method. In the methodology, conditional throughputs are obtained by an iterative procedure. The iterations are repeated until an invalid result is detected or no improvements are found. We demonstrate the performance of the technique with 10 different examples. On average, the solutions have 5% or lower deviations when compared to simulation results. (C) 2010 Elsevier B.V. All rights reserved

Generalized model for infrared perception from an engine exhaust

A comprehensive scheme has been developed for the prediction of radiation from engine exhaust and its incidence on an arbitrarily located sensor. Existing codes have been modified for the simulation of flows inside nozzles and jets. A novel view factor computation scheme has been applied for the determination of the radiosities of the discrete panels of a diffuse and gray nozzle surface. The narrowband model has been used to model the radiation from the gas inside the nozzle and the nonhomogeneous jet. The gas radiation from the nozzle inclusive of nozzle surface radiosities have been used as boundary conditions on the jet radiation. Geometric modeling techniques have been developed to identify and isolate nozzle surface panels and gas columns of the nozzle and jet to determine the radiation signals incident on the sensor. The scheme has been validated for intensity and heat flux predictions, and some useful results of practical importance have been generated to establish its viability for infrared signature analysis of jets

performance of AVS/RS

We perform a simulation based experimental design for automated unit-load (UL) storage and retrieval systems based on autonomous vehicle technology to identify factors affecting their performance. First, we select the best combination of numbers of lifts and vehicles from pre-defined scenarios that are the key components of the system. Then, we apply design of experiment (DOE) for a system with this combination of lifts and vehicles and for various arrival rates. The factors considered in the DOE include: dwell point policy, scheduling rule, input/output (I/O) locations and interleaving rule. Three different responses, the average cycle time for storage and retrieval transactions, average vehicle utilization, and average lift utilization, are considered. However, because the ANOVA assumptions are not met for the average cycle time response, an inverse transformation method is applied on this response. The results show that there is three-way interaction effect on each response at a 95% confidence level. After determining the main and the interaction effects, a Tukey's test analysis is completed on the responses. We utilize data from a warehouse in France that utilizes the autonomous vehicle storage and retrieval system. (C) 2009 Elsevier Ltd. All rights reserved

A HYBRID SCHEDULING AND CONTROL SYSTEM ARCHITECTURE FOR WAREHOUSE MANAGEMENT

In recent years, the hybrid control framework has received attention from the research community. Variations of this control framework are available in the literature, In this paper, a hybrid intelligent agent-based scheduling and control system architecture is presented for an actual industrial warehouse order-picking problem, where goods are stored at multiple locations and the pick location of goods can be selected dynamically in near-real time. The presented architecture includes a higher level optimizer, a middle-level guide agent, and lower level agents. The need for a higher level optimizer and communication between higher and lower level controllers is demonstrated. A mathematical model and a genetic algorithm for the resource assignment problem are presented. Simulation results demonstrating efficiency of the new approach are also presented.X1134sciescopu

REALIZATION OF A SHORT CYCLE TIME IN WAREHOUSE REPLENISHMENT AND ORDER PICKING

Today's competitive and dynamic environment forces companies to be highly responsive and customer oriented to survive and be successful. This paper considers an automated gantry picking complex with 16 pick zones and 16 replenishment zones. Currently, it operates on a 24-h cycle time. A short cycle time operation allows a warehouse manager to be more responsive, flexible and competitive. For example, it allows insertion of late arriving, but high priority, orders into the current cycle. However, to operate in a short cycle environment, the warehouse operations planning and execution must be more dynamic, realtime and intelligent. To realize a short cycle time without loss of productivity, a new replenishment process logic for the gantry-picking complex is developed. The main idea of the new replenishment logic is to minimize the set-up time. Experimental results demonstrating the efficiency of the new approach are also presented.X117sciescopu