Research

This project analyzes ways to minimize issues regarding decision making within a multi-cultural group and creates a culture-bases group decision behavior model to support group decision maiking.

The objective of this project is to develop a Balance Between Material Flow Efficiency, Service Quality, and Security

Sponsor: U.S. Army Defense Ammunition Center Research Team: Kurt Gramoll Universities Involved: University of Oklahoma Start Date: 10/01/08 End Date: 10/01/09 Summary: not available at this time

The objective of this project is to identify stock/process vulnerabilities and strategies of a process to manage both.

This project develops a model to address the issue of uncertain demand by means of labor planning.

The goal of this project is continuous process improvement in field service logistics

Sponsor: U.S. Army Defense Ammunition Center Research Team: Kurt Gramoll Universities Involved: University of Oklahoma Start Date: 10/01/06 End Date: 10/01/07 Summary: The current proposal, Phase IV, plans to extend the features and methods used in the current MLAT system to include various new innovations. As the system has been […]

This project explores the adoption of a new environmentally friendly and worker friendly machine for a process.

Sponsor: U.S. Army Defense Ammunition Center Research Team: Kurt Gramoll Universities Involved: University of Oklahoma Start Date: 10/01/06 End Date: 10/01/07 Summary: Use of the fielded program identified the need to research and develop new enhancements to the application that will allow better and more efficient access to data and […]

The objective of this project is to develop a single user system for enabling paraplegics to drive a motor vehicle.

This project developed optimization models for fleet location/routing, inventory, and treatment procedures for winter/snow removal operations.

Sponsor: AFRL Research Team: Edward A. Pohl, Raymond R. Hill, Laura Militello Universities Involved: University of Arkansas Start Date: 12/01/05 End Date: 09/30/06 Summary: The goal of this project is to identify approaches to assist military planners in anticipating and responding to potential CBR attacks with an emphasis towards impacts […]

This project creates an Information-Based Scheduling and Prediction Systemt to support on-site inventory management.

This project focuses on developing tools to estimate market potential and to design the distribution network and operational plans for a new product delivery system.

This project will model and analyze the Distribution Network of a process and conduct a complete evaluation of the Center Point Distribution Network to determine current utilization levels, routing strategies, and operational procedures.

The goal of this CELDi Center Designated Project is to enhance previously developed multi-echelon supply chain simulation software so that it can be used by CELDi organizations through a SaaS architecture that leverages the resources available within cloud computing (CC) At the end of this project, CELDi member organizations will have available to them a SaaS/Cloud computing application capable of evaluating the performance of multi-echelon supply networks through simulation. This software architecture will facilitate software benefits based on a usage model and develop expertise within the center for this new computing architecture.

Routine maintenance, repair, and overhaul (MRO) of aircraft includes mostly standard work, but often there are "Over and Above" work requests for unanticipated repairs • These requests require a certain level of on-hand inventory in order to continue working on aircraft and minimize delays • Each piece of inventory requires an inventory cost investment Project objectives are to improve processes managing materials by • Reducing total inventory investment without increasing stockout risk • Increasing the visibility of supplier-related data (e.g. lead time) to reduce the need for additional buffer inventory • Reclassifying work requests to encourage holding predictable inventory requirements

This project seeks to extend and generalize the computer based system we developed for SPAWAR that assisted Green Belts in working through a LSS project and that provide a way for PM's to communicate project scope and details as well as check the project status. The first objective is accomplished by developing and coding a logic tree that has a series of questions, tasks and suggestions for the Green Belt. This leads the Green Belt through a progression of data collection and analysis tasks that follows the DMAIC process. The system is not prescriptive in the sense of providing the correct answer; rather, it "requires" Green Belts to perform certain functions for all projects like developing a process flow diagram and value stream map but only "suggests" possible tools based on answers to the questions. The Green Belt still has to think and decide - we just attempt to ensure that he or she has collected the right information to make the decision and limit the possible answers to those that are most likely applicable. The second objective is accomplished by providing PM's a standard format within the system to communicate problem details to the Green Belt. Project status is automatically recorded by the Green Belt as he or she performs tasks and answers and both the Green Belt and PM have access to the progress summary. This research will expand this system in several ways. There will be more tools contained in the system's repertoire. This means that the underlying logic that directs the Green Belt must be expanded and refined. In addition, the type of information and how it is presented to the Green Belt will be improved and expanded. Of high importance to the research team is a more thorough field testing process with (hopefully) several CELDi industry members so that both the Green Belt tool identification process and the PM monitoring process can be improved. If time remains, we will try to help the PM determine an appropriate measurement that will track sustainability of improvements through time. Ideally, the system would automatically prompt the appropriate person when it is time to input and measurement and display a simply chart to facilitate assessment.

The purpose of this project is to evaluate the preferred size of tanks to allocate to customer sites (and also at production facilities and intermediate distribution centers) with the objective of minimizing distribution costs and investment costs in tanks.

The focus of this project is dynamically determining routes of shipments for tactical level decision support for railroads. The objective is to determine an approach to effectively route shipments on trains such that total distance and travel time is minimum while honoring capacity constraints on trains.

Forecasting and optimization have traditionally been approached as two sequential components of inventory management: the random demand is first estimated based on historical data, and the forecast is then used as input to the optimization module. This method suffers from several limitations: (i) the best forecasting method might not be known a priori, and may vary depending on the product considered, (ii) the forecasting module does not take into account the over and underage costs of the inventory model, and instead penalizes over and under-predicting demand equally, although backorder costs are typically much higher than holding costs. This provides motivation for devising an operating strategy that builds upon the information revealed over time and remains flexible to integrate forecasting and inventory control in a framework that can be applied to large numbers of products. In preliminary work, the PI and Co-PI have demonstrated the potential of adaptive forecasting, and achieved cost reductions of up to 5% on test problems. To establish the relevance of the Adaptive and data-driven forecasting and inventory control allows companies to recognize changing demand conditions and mitigate the risk of costly demand estimation errors by (i) tracking the performance of forecasting methods available to the manager and (ii) relying on historical data as much as possible without making assumptions on the underlying probability distributions. It has emerged as an important tool to help companies satisfy customer demand in fast-changing environments. This technical report discusses the challenges related to traditional demand management techniques, motivates the relevance of the data-driven approach to address these issues, and provides a high-level description of the solution tools implemented in this project.

CELDi researchers at Virginia Tech will collaborate with Special Education teachers in the Montgomery County Public School (MCPS) System to redesign a task in an existing distribution center so that it can be effectively completed by people with special needs. The research team will include Dr. Kimberly Ellis, Dr. Tonya Smith-Jackson, and two special education teachers from middle schools in MCPS. The research team will visit the Walgreens Distribution Center in Anderson, SC, to learn more about their inclusive environment. The research team will then visit another distribution center (either the UPS distribution center in Roanoke, VA, or the Target Distribution Center in Stuarts Draft, VA) to select a task for redesign. The team will employ the Systems Engineering Design Process (Blanchard and Fabrycky, 2007) to determine the requirements for the selected task from both the operational perspective as well as the operator perspective. Based on the requirements, the team will conduct preliminary system design and detailed design while incorporating accessibility and universal design guidelines. The team will then implement the design (either in the laboratory or at the facility) and assess the effectiveness and accessibility of the redesign.