Considerations When Designing an AutoStoreTM System

Designing an AutoStoreTM system is a complex undertaking with many interacting decision variables. In this paper we first provide a detailed description of an AutoStore system from the perspective of the main components of the system. We then define the design problem by stipulating the design requirements and decision variables. We then discuss how the decision variables impact the objective function. In so doing we provide many avenues for quantitative modeling by the research community

A Frame Work and Analysis to Inform the Selection of Piece-level Order-fulfillment Technologies

Thepiece-levelorder-fulfillmenttechnologyselectionproblemisanimportantstrategicproblemthatsignificantlyimpactsdistributioncentercosts andoperations,andistypicallysolvedbasedonempiricalexperiences.Given ademandcurveandasuiteofavailablepiece-levelorder-fulfillmenttechnologies, weanalyzewhereinthedemandcurvedifferentorder-fulfillment technologiesshouldbeapplied. Todoso, wedevelopaframeworkthat jointlydeterminesthebestcombinationofpiece-levelorder-fulfillmenttechnologiesandtheassignmentofSKUstothesetechnologies, whichrelaxes thesequential-modelingapproachofpreviousresearch. Wevalidateour methodologywithindustrydataandshowthatour modelprovidestechnologyrecommendationsandSKUassignmentsthatareconsistent with successfulimplementations. Throughasetofnumericalexperimentsand statisticalanalysis,weidentifykeyfactorsinimplementingmanualversus automatedorder-fulfillmenttechnologiesandprovideobservationsintothe applicationofdifferentorder-fulfillmenttechnologystrategies.Finally,we presentconclusionsandfutureresearchdirections

An Experimental Study of the Impact of Warehouse Parameters on the Design of a Case-picking Warehouse

The best design for a warehouse is based on its ability to meet the demands placed on the warehouse, which are typically characterized by warehouse parameters like the order , inventory requirements, etc. Consequently, these parameters should be considered in the design process. In this paper we characterize the design of a case-picking ware- house with design variables and identify the warehouse parameters that have the greatest impact in setting the values of these variables. With our analysis, the search for the optimal design can be reduced by limiting the design space considered

Optimizing Distribution Center Configuration: A Practical View of a Multi-objective Problem

The shape of a distribution center, as well as whether dock locations are on one side or two sides of the facility, impacts measures like travel distances and the number of dock locations that may be utilized. Thus, for a required number of pallet locations, there are multiple combinations of distribution center shape and dock configurations that should be evaluated against multiple measures. We have developed a practical model for making such evaluations and illustrate the model with data reflective of a partner in the Center for Engineering Logistics and Distribution

Modeling the Inventory Requirement and Throughput Performance of Picking Machine Order-fulfillment Technology

Picking machines, also known as remote-order-picking systems, are an example of a stock-to-picker piece-level order-fulfillment technology that consists of two or more pick stations and a common storage area. An integrated closed-loop conveyor decouples the pick stations from the storage area by transporting the needed totes to and from the storage area and the pick stations. We develop a probabilistic model capable of quantifying the inventory differences between order-fulfillment technologies that pool inventory with technologies that do not pool inventory. To determine the throughput of a picking machine, we develop a methodology that incorporates existing analytical models for the picking machine’s subsystems. We present a case study comparing a picking machine to a carousel-pod system to illustrate how a manager could use our methodology to answer system design questions. Finally, we present conclusions and future research

Panel Session #2: Ecom Fulfillment and the Physical Internet: Some Motivation and a Persistent Challenge

Panel Session 2 Panelists: Benoit Montreuil, Russell Meller, and Eric Ballot Moderator: Kimberly Elli

Towards a Physical Internet: the Impact on Logistics Facilities and Material Handling Systems Design and Innovation

Aiming for a radical sustainability improvement, the Physical Internet has the potential of revolutionizing the fields of material handling, logistics, transportation and facilities design. It exploits the enabling concept of standardized, modular and smart containers as well as the universal interconnectivity of logistics networks and services. Its underlying paradigm shift creates a tremendous breakthrough innovation opportunity for the material handling and facility logistics community in terms of equipment, systems and facility design and operation. This paper provides a primer overview of a key subset of the physical elements serving as the foundation of the Physical Internet infrastructure, classified in three categories: containers, movers and nodes. Each element introduced is characterized and illustrated to enable visualization of their innovative nature. The paper helps uncover a wide variety of potent research avenues

Collaborative Freight Transportation to Improve Efficiency and Sustainability

Collaborative distribution offers the potential for substantial improvements in freight transportation. As collaboration increases, more loads are available for sharing among transportation service providers, leading to more fully loaded trailers that travel fewer miles and reduce the cost per load on average. In this study, we develop approaches to analyze improvements in key performance measures as collaboration increases in freight transportation. For the data sets analyzed, improvements include a 34% increase in trailer fullness, a 29% reduction in average costs per load, and a 25% decrease in average miles per load. Based on this analysis, collaboration provides substantial improvements for transportation service providers and opportunities for increased driver retention. Drivers would benefit from a better quality of life, more local routes, and more time home with their families. In addition to the economic and social benefit, the environmental benefit include reducing the miles driven and the resulting CO2 emissions