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Learning Simio Lab Series Lab Module 05 Entity Routing Copyright © 2013 - Jeffrey S. Smith and Simio LLC | All Rights Reserved1.

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Presentation on theme: "Learning Simio Lab Series Lab Module 05 Entity Routing Copyright © 2013 - Jeffrey S. Smith and Simio LLC | All Rights Reserved1."— Presentation transcript:

1 Learning Simio Lab Series Lab Module 05 Entity Routing Copyright © Jeffrey S. Smith and Simio LLC | All Rights Reserved1

2 Objectives and Outline Lab Objectives –Continue learning basic Simio modeling –Learn two different methods to route entities in Simio Link Selection Weights Dynamic routing using node lists Lab Outline –Video 1 – Using Selection Weights for probabilistic routing –Video 2 – Using Selection Weights for conditional routing –Video 3 – Using Node Lists for dynamic routing –Video 4 – Assignments Copyright © Jeffrey S. Smith and Simio LLC | All Rights Reserved 2

3 Video 1 – Using Selection Weights for Routing TV final adjustment and inspection process –TVs arrive at the rate of 20/hour (exponential interarrival times) –Adjustment takes approximately 2 minutes (uniformly distributed between 1.75 and 2.25) –Inspection takes approximately 1.75 minutes (exponentially distributed) –20% of inspected TVs are found to need re-adjustment –Interested in Time In System, Number In System, Utilizations of Adjust and Inspect 3 Copyright © Jeffrey S. Smith and Simio LLC | All Rights Reserved Adjust Arrive Inspect Depart 80% Pass 20% Fail

4 Re-entrant Flow and Effective Arrival Rate 4 Copyright © Jeffrey S. Smith and Simio LLC | All Rights Reserved p 1-p

5 Selection Weights 5 Copyright © Jeffrey S. Smith and Simio LLC | All Rights Reserved w1w1 w2w2 wnwn Link selection probability for link i :

6 Video 2 – Conditional Routing Using Selection Weights TV final adjustment and inspection process –TVs arrive at the rate of 20/hour (exponential interarrival times) –Adjustment takes approximately 2 minutes (uniformly distributed between 1.75 and 2.25) –Inspection takes approximately 1.75 minutes (exponentially distributed) –20% of inspected TVs are found to need re-adjustment –Interested in Time In System, Number In System, Utilizations of Adjust and Inspect 6 Copyright © Jeffrey S. Smith and Simio LLC | All Rights Reserved Adjust Arrive Inspect Depart 80% Pass 20% Fail Maximum of 3 adjustments for a given TV

7 Video 3 – Dynamic Routing Using Node Lists 7 Copyright © Jeffrey S. Smith and Simio LLC | All Rights Reserved Server1 Arrive Depart Server2 Server3 Approx. 10 minutes Approx. 5 minutes Approx. 1 minute Arrival rate: 60/hour

8 Video 4 - Assignment 8 Copyright © Jeffrey S. Smith and Simio LLC | All Rights Reserved Using the TV Adjust/Inspect model: –Fix the issue where the TVs are adjusted the 4 th (and inspected) time even though we know that they will be rejected after inspection. Hint: Start by inserting a Basic Node in the path from the Inspect server back to the Adjust server. –Create a reference property for the maximum number of adjustments allowed and develop an experiment that compares the configurations with values 1, 2, 3, 4, 5, 100.

9 Video 4 - Assignment 9 Copyright © Jeffrey S. Smith and Simio LLC | All Rights Reserved Using the dynamic routing model (from the third video): –Develop an experiment with 25 replications using a run length of 500 hours with a 250 hour warm- up and responses for the three server utilizations, the entity time in system (TIS) and entity number in system (NIS) –Using the base model, compare the 5 performance metrics using the following routing alternatives: 1.Probabilistic routing using the selection weights 6/78, 12/78, and 60/78 2.Preferred order with capacity 5 buffers at each server 3.Using AssociatedStationOverload with no buffers (capacity 0 buffers) 4.Using AssociatedStationOverload with capacity 5 buffers 5.Using the shortest queue length with infinite capacity buffers


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