Merging Mobile Robotics and RFID Technologies for an Automated Asset Locating System (AALS)

Objectives:

• A new, automated system widely applicable to inventory and asset management (No human-in-the-loop)
• Proof-of-concept demonstration in a representative environment
• Matlab RFID toolbox & proof-of-concept hardware tech specs available to CELDi members

Deliverables:

• A successful demonstration of proof-of-concept system with an actual robot platform
• Detailed system specifications provided to CELDi members
• An RFID Matlab/C++ toolbox - dual format will appeal to both researchers who need a higher level interface for rapid development (Matlab), as well as CELDi industrial partners in developing production ready solutions (C++)
• AALS Wiki site established for CELDi members

Researchers: John R. Spletzer, Emory Zimmers at Lehigh University

A Software Tool for Intermittent Demand Analysis

Problem in context: Intermittent (sporadic) demand forecasting is extremely difficult Choosing the best forecast technique to use is difficult Deliverables - A software that: Assists managers in choosing a forecasting method and stocking policy for a particular item that has intermittent demand Is capable of: Data analysis Forecasting (comparison, batch mode, etc.) Inventory analysis Simulation modeling of inventory system under intermittent demand More information on this project Researchers: Manuel D. Rossetti, Edward A. Pohl, Vijith Varghese, Hugh Medal at University of Arkansas

Improve Inventory Accuracy through Optimal Cycle Counting

Problem in context:

• The inventory record in the computer does not match the actual inventory record in the warehouse
• 65% is inaccurate for a large retail chain
• Accurate inventory records for auditing purpose

What can CELDi members use?

• Developed a cycle counting scheduler Optimal cycle counting policy
• When to count and what sequence to count
• Helps manage inventory
• Reduce counting cost and improve inventory accuracy
• Convenient for user to use
• Written in Java and portable

Researchers:

Yongpei Guan, Tieming Liu, Simin Pulat, and Zhili Zhou University of Oklahoma and Oklahoma State University

Logistics Network Design for Less-than-Truckload Consolidation More info

Problem in context:

Many manufacturing and retail companies operate large but sparse domestic distribution networks consisting of highly dispersed origins and destinations and varying levels of shipment volumes. The problem is to evaluate the existing LTL transportation network for possible shipment consolidation strategies, and optimize it to get the maximum transportation cost savings.

What can CELDi members use?

• A modeling methodology and solution algorithm for large-scale but sparse logistics networks
• An Excel based evaluation version of the logistics network design software using a spreadsheet model which is easy to adapt
• A C/C++ based optimization version of the logistics network design software

Researchers:

Wooseung Jang, James Noble, Zhongwei Yu and Phichet Wutthisirisart, University of Missouri

Problem in context:

Six Sigma is frequently implemented by training a large number of employees to be 'Green Belts' and depending on them to execute small projects in the field to improve operations. Since training for this designation is often a one week class, even the most well intentioned freshly minted Green Belt can get overwhelmed and literally not know where to start.

For a CD containing the CELDi Green Belt Software contact CELDi researcher, Bill Ferrell, Clemson University

What can CELDi members use?

• Simple to use software that helps the Green Belt determine the most likely tools from their training that will help resolve a specific problem.
• The software will provide several levels of details: abbreviated step-by-step process for experienced users, more detail for someone who has forgotten, and identification of a reference for those requiring substantial assistance
• Members who have implemented Six Sigma can give the software to their Green Belts to put on their computers for immediate use
• Members who have not trained employees in Six Sigma can use the tool to identify tools that can assist in resolving problems and will have references for those who have never used the tools

Development of Logistics Efficiency Metrics

Problem in context:

The costs associated with product logistics represent one of the main drivers of a product's final cost(approximately 8% of the final price). Therefore, it is important to assess and monitor the performanceof individual components of the logistics system to identify opportunities for improvement and correction. Currently, techniques for the continuous monitoring and control of costs from the shippers' perspective are rare in the industry.

Deliverables:

• A quarterly Index (CELDI/CAPS) to track the availability and utilization of transportation capacity
• Availability, dissemination and use of index resulting in CELDi national name recognition

What can CELDi members use?

• A Methodology for measuring logistic and supply chain performance
• Information for planning transportation contracts
• Tools for monitoring and continuous improvement of logistics performance

Researchers:

Rene Villalobos, Arnold Maltz, Phillip Carter and Liangjie Xue, Arizona State University

Supply Chain Network Simulator Using Cloud Computing

Project Objectives:

• Develop an effective model for the simulation of large supply chains involving thousands of stock keep units stocked at different locations
• Develop the software through a Software as a Service(SaaS) architecture that leverages the resources available within cloud computing

What can CELDi members use?

• Simulation software, the software's application programming interface (API), and a users guide for the use of the software
• A screen capture based recorded video demonstration webinar of the software
• A project report that summarizes the research and development related to the
• A white paper on SaaS and cloud computing, conference article, and an article in IIE Solutions magazine

CELDi Researchers:
Manuel Rossetti, University of Arkansas and Ricki Ingalls, Oklahoma State University

Improved Input Data Management for Logistics Analysis

Have you ever asked a project team, “Can you bring our historical data into this approach and make sure the system being modeled can incorporate the data properly?” This is an extremely common, yet often troubling question that exists in both research and application contexts.

This research will provide a framework for integrating database information and expert knowledge to extract low error probability distributions that capture the interactions between recorded factors with a minimum of assumptions. This will position CELDi members at the forefront of research in this field. The work will contribute to the expansion of knowledge in the fields of simulation modeling and statistical analysis.

The goal of this CELDi Center Designated Project is the development of multivariate probability algorithms and software tools for application to databases of historical information from complex processes.

Project Deliverable:

• A tool that will allow industry partners to properly assess their historical data (and prepare it for use in future analytical studies)
• Dissemination via research papers and presentations of the new methodology and results from large-scale testing on healthcare- and maintenance-based data

CELDi Researcher:
Kevin Taaffe, Clemson University

Decision Support for Warehouse Design

Project Objectives:

The goal of this project is to improve the design of real-world warehouses by providing practitioners with a means by which to evaluate several design alternatives.

Project Deliverables:

• An Excel-based tool that supports the design process, allowing a comparison of several design alternatives
• A report documenting the methodology with an example to illustrate use of the tool
• A webinar to disseminate the results of the project within CELDi

What can CELDi members use?

This research will be beneficial for CELDi members if they design or reconfigure a distribution center. Based on our experience with previous CELDi research and other organizations, reductions in both operating expenses (labor costs, primarily) and facility costs (building, land costs, etc.) are expected. Given that both of these cost categories annualize to millions of dollars, 10% reductions are significant possible savings.

CELDi Researcher:
Russ Meller, University of Arkansas

CELDi Knowledge Management System

Project Objectives:

Create a self-sustainable push and pull knowledge management system consisting of industry and center directed projects, researcher expertise, and industrial opportunities that may be readily searched through Google style queries.

Project Deliverables:

• Past projects and researcher profiles are being summarized and inputted into database.
• A screen capture based recorded video demonstration webinar of the software
• Both the webpage and iPhone app will be functional and aesthetically pleasing
• The database will “learn” which projects are most likely to be of interest to the queried phrase and will display in this order

CELDi Researchers:
Tim Matis, Texas Tech University