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CELDi. Center for Engineering Logistics & Distribution. Louisville Research Overview: Center for Engineering Logistics and Distribution (CELDi). Logistics Initiatives at the University of Louisville. Optimization, Simulation Information Technologies, Engineering Bias. CELDi (Ind. Eng.).

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Louisville Research Overview: Center for Engineering Logistics and Distribution (CELDi)


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    1. CELDi Center for Engineering Logistics & Distribution Louisville Research Overview:Center for Engineering Logistics and Distribution (CELDi)

    2. Logistics Initiatives at theUniversity of Louisville Optimization, Simulation Information Technologies, Engineering Bias CELDi (Ind. Eng.) Increased Networking Opportunities, Potential For Matching Funds Continuing Education, MS Logistics Engineering U of L LOGISTICS Emphasis LODI Independent Projects Educational Programming, Inter-college Coordination Varied Research in Several Disciplines Increased Resource Base

    3. Efforts atLouisville, KY • Louisville is a major manufacturing center and distribution hub that is well placed relative to population and infrastructure. • Ohio River, 3 major interstate highways, 10th busiest freight airport in the world, UPS air hub, ACBL headquarters, Ford assembly plants. • The U of L lists logistics as a top priority. • At the J.B. Speed Scientific School… • New Logistics Center (LODI & CELDi) & Endowed Chairs • Developing an MS in Logistics Engineering • Several New Courses • New Business Partners

    4. CELDi Center for Engineering Logistics & Distribution CELDi Organization University of Arkansas Intelligent Material Handling & Fleet Maintenance Intelligent Systems / Value-chain Integration / Field Service Logistics University of Oklahoma Material Handling / Shop Floor Logistics / Fleet Supportability Strategic Logistics Intelligent Transportation & Distribution / Reverse Logistics Systems • Partnerships • ITaL (OU) • LODI (UL) • MTBC (UA) • OTC (OU) • SCMRC (UA) Integrated Logistics Systems / Fleet Reliability Distribution, Transportation, & Reliability Modeling and Analysis University of Louisville

    5. Fleet Planning, Scheduling and Optimization American Commercial Barge Line LLC Researchers: G. Don Taylor, Gail W. DePuy & D.J. Drossos Problem Definition: Planning for optimal usage of a boat fleet is a daunting task. Building barge tows with common destinations minimizes downstream handling but adds to barge dwell time. On the other hand, minimizing dwell time leads to excessive downstream handling. Concurrently, it is necessary to utilize company-owned boats whenever possible to reduce sub-contract costs. Objective: Provide an easily solved model to assist in optimizing the assignment of barges to boats on the Ohio River to minimize total handling and dwell costs.

    6. Methodology/Benefit Methodology: • Review current methods and literature • Initial integer programming formulation • Separation of grouping and selection routines to make the problem tractable • Concurrent development of a simulation- based evaluation system Targeted Benefit: Reduce the cost of making fleet assignments while better utilizing fleet boats and better serving customer needs

    7. Seeking Cost Effective Solutions for Flat Mail Preparation United States Postal Service Researchers: G. Don Taylor, John S. Usher, and Jamie Little Problem Definition: Postal automation programs, in terms of sortation and material handling systems, have been so successful that flat mail preparation areas cannot keep pace. The current methods of preparing flat mail for induction to automated systems is very labor intensive. Objective: To examine the possible alternative flat mail preparation systems, both procedural and physical, that would reduce the costs associated with present, labor intensive mail preparation systems.

    8. Methodology/Benefit Methodology: • Review current methods and literature • Visit multiple USPS facilities, major mailers & printers • Enumerate options for procedural and physical changes • Make final recommendations based on efficacy and cost Targeted Benefit: Reduce the cost associated with preparing flat mail for automated systems without violating basic system constraints

    9. Automated Production Planning for Repairable Units Naval Surface Warfare Center, Crane, Indiana Researchers:Gail W. DePuy John S. Usher, Julie Raisor, Jonathan Gagel, and Jason Embry Problem Definition: NSWC-Crane refurbishes many different types of mechanical and electrical devices used in military ships and aircraft. Crane receives inoperable units and attempts to salvage the repairable components so that good units can be produced. Unfortunately, it is difficult to know how many good or repairable components will arrive within the carcasses. This in turn makes it difficult to accurately predict production requirements needed to meet demand. Objective: To develop an automated tool to be used to predict Crane’s ability to meet future demand and red flag those periods where demand may not be met. This tool predicts potential supply deficiencies far enough in advance to allow management intervention and correction.

    10. Methodology/Benefit Methodology: • Review current production planning software • Develop automated tool to perform probabilistic production planning analysis based on expected values • Validate tool using two production lines • Provide Software Training to Crane Managers Targeted Benefit: Predicts potential supply deficiencies far enough in advance to allow management intervention and correction.

    11. A Microsimulation Model of DailyHousehold Activity-Episode Generation Researcher: Darren M. Scott, Ph.D. Problem Definition: The Urban Transportation Modeling System (UTMS) is the most commonly used model for forecasting travel demand in urban areas. However, there is much concern about its ability to meet the challenges of contemporary and future transportation planning. Objective: To develop one module of an activity-based forecasting model to remedy the deficiencies of UTMS.

    12. Methodology and Benefits • Methodology: • Develop and estimate trivariate ordered probit models • Develop an object-oriented microsimulation model • Evaluate the policy sensitivity of the model • Benefits: • One step in the development of an activity-based travel demand forecasting system that is policy sensitive

    13. Concluding Remarks • Louisville is one of the world’s great logistics cities • The University of Louisville lists logistics as one of two major thrust areas for the entire university • The three-university partnership brings synergies & opportunities for member companies—each campus brings unique skills • Multi-campus research projects are encouraged • CELDi research is pragmatic, cost-effective and often leads to a quantifiable payback

    14. Question and Answer Period