1. Client: North Texas Food Bank Senior Design 2010 Nafees Ahmed Prajyot Bangera Shahrzad Rahimian Pablo De Santiago May 10, 2010 “Passionately pursuing a hunger-free community” 1

2. Client Background NTFB was established in 1982 to deal with the critical issue of hunger in the North Texas area They provided over 400,000 meals during their first year of operations; Last year, over 37 million meals distributed Currently, their goal is to reach 50 million meals distributed by 2011 Their vision is to see a hunger-free world 2

3. Management Summary Met with Director of Operations, Sean Gray, and toured the facility It was determined that the best area of focus for us would be determining bottlenecks as to why the freezer and cooler operations were not as efficient as they could possibly be Observations Observed how cold food comes to NTFB, is stored, sorted, ordered, and delivered to agencies Data collection – online inventories and ordering system Determined main metric to measure improvement would be time Used a simulation to model the system and determine recommendations 3

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5. Problem Description Concerns with the freezer/cooler operations Organization of items inside Time wasted looking for items or moving items around to get to another item – this time could be better utilized Optimizing usage of the limited space Perhaps we could see a problem that was going unnoticed in the operations Cooler/freezers items brought out once agency physically shows up Data Collection Organization – no tracking of cycle time Plenty of inventory data available Observations and process timing 5

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7. Situation Analysis Speak with operations and facilities managers Concerns with freezers/cooler New ideas for system improvements Spoke to some agencies that come to pick up food Layout East dock Primarily assigned to NTFB trucks to deliver and pick-up items Used to receive items in the afternoon West dock Primarily for agency pick-ups 7

8. Direct Observation Pictures and videos taken, so we can track each process and time them as well Interviews with truck drivers, forklift operators, front office management, and agencies provided different viewpoints to the same problems 8

9. Situation Analysis Conclusion of analysis NTFB runs a very efficient operation Recommendations would most likely be on small changes that will add up to an overall increased efficiency Based on the concept of “kaizen” - Japanese for "improvement" or "change for the better“…focuses on constant, little improvements to a system to make it run more smoothly 9

10. Creating the Simulation Model 10

11. ProModel Locations are like variables Set constraints through locations Set times of processes based on our direct observation data 11

12. ProModel Used expected values from historical data NTFB’s online ordering system and inventory database; sign in sheets Performed an A-B-C pareto analysis on the C/F inventory to determine realistic probabilities and values 12

13. Analysis of Results Possible to run thousands of simulations with different scenarios We chose to run 4 variations of our base line model with possible scenarios, and then a 5 th variation with extremely ideal conditions and parameters, to be able to see how the results would vary Since space within freezers and coolers is limited and is not something we can create, it is a constant in our model Each model variation ran 10 times, over the course of 8 hours, using 15 minute time slots Results were given as averages from the 10 simulation runs 13

14. Analysis of Results Name Scheduled Time (HR)CapacityTotal Entries Avg Time Per Entry (MIN) Avg Contents% Utilization docks83534.36.990.501.42 freezer18309.1168.573.1810.61 freezer28308.8141.252.708.99 cooler83015.5163.975.4017.98 weighting point 18133.84.540.3131.50 weighting point 2819.946.840.9493.72 Delivery queue818.951.310.9292.12 gate2817.96.490.1110.56 Base-Line Model: Base-Line Model [45-55 min agency wait, 1 agency pick up dock, 1 queue line] Name Scheduled Time (HR)CapacityTotal Entries Avg Time Per Entry (MIN) Avg Contents% Utilization docks83532.97.200.501.42 freezer18308149.972.498.30 freezer28309.2134.482.688.95 cooler83014.9155.394.8216.06 weighting point 18132.54.110.2727.38 weighting point 28110.344.400.9392.56 Delivery queue819.350.190.9493.53 gate2828.35.960.105.13 Scenario 1 [45-55 min agency wait, 2 agency pick up docks, 1 queue line] 14

15. Analysis of Results Name Scheduled Time (HR)CapacityTotal Entries Avg Time Per Entry (MIN) Avg Contents% Utilization docks83534.97.380.541.56 freezer183010.2100.132.187.26 freezer28307.694.991.765.86 cooler83016.5106.093.8212.72 weighting point 18134.63.860.2827.99 weighting point 28118.721.840.8383.50 Delivery queue8217.747.971.7386.67 gate28115.76.100.2019.83 Scenario 2 [45-55 min agency wait, 1 agency pick up docks, 2 queue lines] Name Scheduled Time (HR)CapacityTotal Entries Avg Time Per Entry (MIN) Avg Contents% Utilization docks835337.250.501.42 freezer18308.6126.882.397.97 freezer28308.4120.452.217.35 cooler83015.3124.704.1813.93 weighting point18132.54.000.2727.24 weighting point 28113.930.660.8686.15 Delivery queue8112.934.910.9191.17 gate28111.96.190.1515.50 Scenario 4 [30-40 min agency wait, 1 agency pick up dock, 1 queue line] 15

16. Recommendations & Conclusion Simulation results showed that the main problem/bottleneck lies with the agency waiting line, and once that problem can be eliminated, the process for the cooler/freezers will become more steady as well (due to items only coming out once agency arrives) Add an extra shelf in the back corner of the cooler to utilize vertical space; will minimize time moving things around to get to item in back Label designated areas within cooler/freezers Increase organization/decrease cycle time Group items together Look into possibility of opening another dock for P&W customers Record cycle times of items Recommend looking into other O.R. methods, like waiting line queuing theory to further optimize operations By implementing some of these recommendations, we feel that it will really help the NTFB make their operations more efficient, and help them reach their goal of 50 million meals by 2011 16

17. Thank you! 17