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The Logistics Institute University of Arkansas Project Overview John R. English

TLI – Arkansas . The Logistics Institute University of Arkansas Project Overview John R. English Director, The Logistics Institute Professor and Head, Industrial Engineering May 2001. Overview. New Faculty Overview of Projects. New Faculty. Scott Mason, Assistant Professor ASU Ph.D.

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The Logistics Institute University of Arkansas Project Overview John R. English

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  1. TLI – Arkansas The Logistics Institute University of Arkansas Project Overview John R. English Director, The Logistics Institute Professor and Head, Industrial Engineering May 2001

  2. Overview New Faculty Overview of Projects

  3. New Faculty • Scott Mason, Assistant Professor • ASU Ph.D. • Production systems, electronics manufacturing • Heather Nachtmann, Assistant Professor • University of Pittsburgh Ph.D. • Industrial cost, activity based costing, fuzzy sets • Richard Cassady, Assistant Professor • VPI Ph.D. • Logistics, quality and reliability

  4. University of ArkansasCurrent TLI Projects Logistics Planning and Design Dynamic Scheduling - Competing Multi-stage Demands Avaya Inc. Administrative Analysis Wal-Mart Stores, Inc. Production Planning Tyson Foods, Inc. Performance Evaluation Selective Maintenance Strategies Pine Bluff Arsenal Contract Manufacturing Avaya Inc. Stock Positioning in Military Logistical SystemsDefense Logistics Agency Transportation Systems Integration of Warehouse and Trucking Functions Global Concepts Inc.

  5. Dynamic Scheduling for Competing Multi-Stage Demands -Phase 2 (TLI-AR00-1) Avaya Inc. Researchers: Mike Cole, Scott Mason and Mike Liow G. Don Taylor, University of Louisville Description: Identify scheduling heuristics and inventory sizing in a general “n/m” job shop environment. Objectives: Develop schedules that “minimize” makespan Size finished goods buffer to reduce stockouts and overtime

  6. Methodology/Conclusions Methodology: • Scheduling: Excel-based emulator using standard heuristics • Buffer sizing: cost equations, expert rules Conclusions: • Emulator provides a powerful means of evaluating standard scheduling heuristics • Dynamic buffer sizing is complicated in the “real world”

  7. Administrative Analysis Based on Time Studies and Work Sampling(TLI-AR01-01) Wal-Mart Neighborhood Market Study Researchers: Terry R. Collins, Earnest W. Fant, Manuel D. Rossetti and Michelle R. Kincannon Problem Definition:Appropriate staffing is sought to adjust for the fluctuation of customer arrivals. In addition, efficiency is sought in the material handling of merchandise to establish patterns for staffing. Objective: Identify time spent on performing specific tasks and number of customers in queue. Establish a successful organizational structure that would address the staffing issues Provide oral and written reports to Wal-Mart personnel

  8. Methodology/Benefits Methodology:Identify a Staffing Technique Based On: • Queuing Theory for the Front-end • Productivity Rates for the In-store Logistics • Economic Justification for Self-serve Checkout Stations Benefits: Customer service due to time spent in queue Productivity of department managers Productivity of stockers

  9. Production Planning Model Validation(TLI-AR01-02) Tyson Foods, Inc. Researchers: Heather Nachtmann, Scott Mason, Earnest Fant, Andres Angulo Problem Definition:Tyson’s is currently striving to determine appropriate inventory levels while maintaining high levels of customer service through the development and validation of production planning methodologies. Objective: To validate current Target Inventory Methodologies with an initial focus on Replenishment Lead Times

  10. Methodology/Benefit Methodology: • Review current Target Inventory Methodologies • Analyze underlying assumptions • Data collection and analysis • Evaluate methodology • Revise methodology Targeted Benefit: Reduce cost by determining appropriate inventory levels while maintaining high customer service levels.

  11. Development of Productivity-Based Selective Maintenance Strategies(TLI-AR01-03) Pine Bluff Arsenal (PBA) Researchers: Earnest W. Fant, C. Richard Cassady, Julie Watson, and Kellie Inklebarger (REU) Problem Definition: The maintenance actions performed by an organization are limited by the maintenance resources available. How should an organization allocate the resources available for performing maintenance to the equipment that is in need of maintenance? Objective: Establish a methodology for prioritizing and executing preventive and corrective maintenance actions.

  12. Methodology/Benefits Methodology: • Define system, equipment performance characteristics, and system performance measures • Optimize equipment PM intervals • Develop facility maintenance plans considering limited maintenance resources Targeted Benefits:  Reliability, Cost Savings & Labor Utilization  Response Time  Downtime

  13. Contract Manufacturing’s Impact on the Electronics Manufacturing Supply Chain (TLI-AR01-04) Avaya Inc. Researchers: Michael H. Cole, Scott J. Mason, Tze-Chen Hau Description:Traditional manufacturers are now focusing on company core competencies, choosing to outsource the actual manufacturing of their products. Objective:Assess the impacts of contract manufacturing on the electronics manufacturing supply chain. Methodology: • Mixed Integer Programming • Simulation

  14. Stock Positioning for Retail & Spare Parts Inventory in Military Logistical Systems (TLI-AR01-05b) Defense Logistics Agency - Defense Distribution Center (DLA-DDC) TLI-Research Team • Manuel D. Rossetti, Erhan Kutanoglu, Nancy Sloan • The purpose of this TLI Research Project is to examine the effect of pushing DLA wholesale inventories as close to the end customer as possible, thereby eliminating several (within service) inventory echelon layers from the supply chain pipeline.

  15. Integrating the Warehousing and Transportation Functions of the Supply Chain—A Pull Model (TLI-AR01-06) Global Concepts, Inc. Project Director: Scott J. Mason Description:Optimizing key components of the supply chain in isolation, while promoting locally optimum solutions, can result in globally sub-optimal performance. Objective:Explore the potential advantages of integrating these two critically-linked segments during supply chain optimization using a pull model with the goal of establishing a virtual warehouse.

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