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Project #3: Production Cost Savings at Washington Post

Project #3: Production Cost Savings at Washington Post. SYST 798/OR 680 Progress Report #1 10 March 2011 Thomas Kuklinski Timothy Smith Ling Wu Vladimir Zivkovic. Clients Problem Statement Methodology/Technical Approach Task Breakdown Structure and Status Earned Value Management

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Project #3: Production Cost Savings at Washington Post

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  1. Project #3: Production Cost Savingsat Washington Post SYST 798/OR 680 Progress Report #1 10 March 2011 Thomas Kuklinski Timothy Smith Ling Wu Vladimir Zivkovic

  2. Clients Problem Statement Methodology/Technical Approach Task Breakdown Structure and Status Earned Value Management Issues/Concerns Way Forward Questions Overview

  3. Clients • Kent Renk, Materials Handling Foreman, Washington Post, renkk@washpost.com, 703-916-2471 (office), 703-916-2471(cell) • Kim Hammett, Assistant Superintendent for Materials Handling, hammettk@washpost.com, 703-916-2447 (office), 703-869-2463 (cell)

  4. Background Fall of 2010 GMU students did initial static analysis of the Washington Post’s Shipping and Receiving Department in Springfield, VA They conducted a process evaluation, an analysis of labor, and an analysis of routes which resulted in three recommendations: Labor cuts (implemented) Route simplifications Improved data tracking Problem Statement Our objective will be to maximize the efficiency of the Washington Post’s materials handling system at their four work centers in an effort to generate cost savings to the overall operation We would like to bring to life and build upon the static analysis done by previous group in a dynamic simulation model of the helper component of the work centers Stakeholders Materials Handling Foreman(Kent Renk) Problem Statement

  5. Process Analysis (started) Build upon last group’s work done on process evaluation Develop a complete and detailed qualitative understanding of how the Shipping and Receiving Department operates Data Collection and Analysis (started) Collect data from both the materials tracking system (i.e. MTC) and subject matter experts Obtain descriptive statistics on each component of the system Model Selection and Construction (started) Evaluate model alternatives based on quantitative/qualitative data and client needs Construct and test model (e.g. turn system processes into Arena modules) Output Analysis (not started) Evaluate output in terms of cost and throughput Iterate Methodology/Technical Approach

  6. Process Analysis Trucks 1. Daily Insert Ads & Sunday Packaging ---> Materials Handling 2a. Daily Insert Ads ---> Racks 3. Completed Jackets <---- Daily Insert 2c. Jackets Run of Press Headsheets (outside scope) Sunday Packaging 2a. Sunday Packaging ---> Run of Press 4. Collated Sunday Packaging <----

  7. Process Analysis

  8. Data Collection and Analysis • Labor data • Obtained labor markup data for this period • Broken down by work center, day, shift, and role • Labor assignments are being zoned to different routes within our process

  9. Data Collection and Analysis • Route data • Obtained Summary Report for February 7-12 created by MTC • Data obtained for a “normal” week of work • Contains pallet moves for all materials throughout the system • MATLAB and MS Excel parsers are being developed to determine (1) raw material arrival processes, (2) production targets, and (3) route locations, frequencies by day/shift, and time • Mapping of location IDs in the MTC data are being linked to locations in our system • Client will fill in gaps in the processes not collected in MTC • Materials not scanned properly

  10. Discussion with client and additional system understanding has allowed us to settle with an Arena simulation model It is very important for the client to be able to use the model to forecast the impact of different labor markups on production targets for both daily inserts and Sunday packaging Phase 1 - Develop an Arena model that allows the client to play with “what-if” labor markups to hit production targets (required) Phase 2 – Add on an optimization engine that determines labor markups at minimal cost to the client to hit production targets (desired) Currently constructing a straw man Arena simulation model and researching Arena modules that would be compatible with our system Model Selection and Construction

  11. Model Selection and Construction Monday, Shift 1 Raw Materials Normal(2, 4) U(6,8) EXP(10) C1 Machine Dock Dock S1Machine U(2,5) Production Targets U(4,5) Run of Press Jackets EXP(5)

  12. Task Breakdown Structure and Status

  13. Earned Value Management

  14. Issues/Concerns • Defining labor zones and their interactions with components in the Arena simulation model • Extracting useful information from the given Pallet Summary Report (missing data) • Packaging the Arena simulation model • Graphical User Interface • Model for each day vs. Large dynamic model

  15. Way Forward • Data Collection and Analysis • Finish extracting relevant data from the Pallet Summary Report • Determine raw material arrival processes • Determine production targets • Determine route distributions • Modeling • Complete straw man model • Labor zones!! • Create the initial draft of the Arena simulation model using straw man model • Meet with sponsors to go over the draft Arena simulation model • Modify the model based on feedback and clarification from sponsor

  16. Questions

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