Simio Module Introduction - Video 2 Notes

Overview

• Continuation from the first video where an initial Simio model of a two-station flow line was built.
• Objectives for this video:
  • Specify object properties for the model.
  • Introduce Simio experiment concepts.

Model Components

• Source Object: Creates entities.
• Servers: Process entities.
• Sync Object: Tabulates results and destroys entities.

Arrival and Service Rates

• Customer arrival rate: 25 per hour.
• Service times:
  • Server 1: 2 minutes on average.
  • Server 2: 1.71 minutes on average.
• Reality Check:
  • Service rates:
    • Server 1: 30 per hour (60 min / 2 min).
    • Server 2: 35 per hour (60 min / 1.71 min).
  • Arrival rate (25) is less than service rates (30 and 35), indicating the system is nominally stable.

Distribution of Times

• Arrival and service times are assumed to follow an exponential distribution:
  • Arrival time mean: 2.4 minutes.
  • Service time mean for Server 1: 2 minutes.
  • Service time mean for Server 2: 1.71 minutes.
• Use of Simio Expressions in modeling:
  • Random Exponential: Expression random.exponential(mean) is utilized.

Setting Object Properties

• Source Object (Source One):
  • Set arrival time property to mean of 2.4 minutes.
• Server Object:
  • Set processing time property for Server 1 and Server 2 using the Expression Builder.
  • Server 1: random.exponential(2).
  • Server 2: random.exponential(1.71).

Running the Model

• Updated parameters were applied to the model.
• Results are similar to previous runs, maintaining system stability.
• A verification method checks if around 600 entities flow through the system over 24 hours.
  • Expected: Arrival rate (25) * Time (24) = 600.

Simio Expressions Overview

• Common distributions available in Simio:
  • Uniform, Triangular, Exponential, Normal, Log Normal.
• Expression Builder: Assists in building expressions by providing tooltips and sublists for ease of use.

Simio Experiments

• Transition from interactive modeling to simulation experiments:
  • Set the ending time to a run length of 240 hours.
  • Observations should be around 6000 for this duration.
• Explanation of Predictable Randomness:
  • The model yields consistent results due to the random number generator starting at the same point each run unless altered.

Running Experiments

• Created a new experiment in Simio with default settings (10 replications).
• Results show statistical summaries:
  • Minimum, Maximum, Average of observations across replications.

Conclusion

• Next video will focus on using experiments for interpreting results.