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14.4: Summary

  • Page ID
    31020
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    This case study emphasizes a sequentially designed simulation experiment to determine the level of resources needed to operate a truck based logistics system. Minimizing the cost of the system in terms of trucks and workers trades off with the need to meet delivery targets. The idea of a level of indifference is employed. Alternatives may statistically differ significantly, but the difference may not be large enough, greater than the level of indifference, to impact system operations.

    Problems

    1. Validate the computation of the expected time a truck spends in repair per roundtrip.
    2. Tell what the entity in each of the processes in the model discussed in this chapter represents.
    3. Give verification evidence based on the information resulting from one replicate of the simulation experiment as follows:
      Number of truck round trips started: 14335
      Number of truck round trips completed: 14203
      Number of truck round trips on going at the end of the simulation: 104
      Number of trucks waiting or in inspection and repair at the end of the simulation: 28
    4. Compare the modeling and experimental issues of the logistics system discussed in this chapter to those concerning the serial line discussed in chapter 7.
    5. Tour the operation of the local office of an overnight delivery service. Write down a process model of their logistics system for organizing and delivering in bound packages.
    6. Modify the model presented in this chapter so that no worker inspects or repairs a truck during the off-shift period. Assess the effect of making the model more precise on the number of workers required.
    7. Suppose that workers were available 24 hours per day but the total number of hours worked per day could not increase. That is, there would be 2/3rds of the number of workers determine above would work each shift. Use the model developed in this chapter to determine if the number of trucks needed could be lowered.
    8. Modify the model and simulation experiment to estimate the needed capacity of the parking area for trucks at the terminal. Include trucks that are in inspection or repair.
    9. Modify the model and simulation experiment to give a profile of truck location. Estimate the average number of trucks in each possible location: in route to the customer, at the customer, in route to the terminal, in inspection, in repair, and waiting for a load.
    10. Conduct a simulation experiment to determine the number of workers needed.

    Case Study

    A new logistics system is being designed to transport one product from a factory to a terminal by rail. A simulation study is needed to estimate the following:

    1. The rail fleet size.
    2. The size of the rail yard at the factory.
    3. The size of the rail yard at the terminal.
    4. The size of the inventory needed at the terminal.

    Customer demand is satisfied each day from the terminal. Demand is normally distributed with a mean of 1000 units and a standard deviation of 200 units. Production at the factory is sufficient to meet demand on a daily basis. Policy is to ship an average of 1000 units each day from the factory to the terminal. Each rail car holds 150 units. Partial rail car loads are not shipped but included with the demand for the the next day.

    The customer service level provided at the terminal should be at least 99%. The time period of interest is one year.

    Transportation time from the factory to the terminal is triangularly distributed with a minimum of 3 days, a mode of 7 days, and a maximum of 14 days. At the terminal, a car must wait for a single unload point to unload. Unloading takes one hour. Upon return to the plant, a rail car is inspected. Inspections take 2 hours. Maintence is required for 3% of returning cars. Maintenance requires 4 days.

    Embellishment: All cars leaving the factory in a day join a single train leaving at 4:00 A.M. the next morning and have the same transportation time to the terminal. A single train containing all empty cars leaves the terminal at 4:00 A.M. each morning.

    Case Study Issues.

    1. What initial conditions concerning the arrival of trains to the terminal should be used?
    2. What target inventory level should be used?
    3. How is the policy to ship 1000 units each day from the factory implemented if rail cars hold 150 units?
    4. Embellishment: How is the requirement that all rail cars leaving the factory or terminal join a single train with a single transporation time to the other site modeled?
    5. How is the unloading constraint for rail cars modeled?
    6. In what order should the system parameters listed above be determined by the simulation experiments?
    7. What is the primary performance measure for the simulation experiments?
    8. How will verification and validation evidence be obtained?
    9. How is the size of a rail yard modeled?
    10. How is the size of the rail fleet modeled?
    11. Computed the expected fleet size and use the result in providing validation evidence.
    12. Define the processes that comprise the model.

    This page titled 14.4: Summary is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by Charles R. Standridge.

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