Reducing Capacity of a Fixed Resource As Case Scenarios

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Vyk_k asked Mar 20, '23 Jason Lightfoot commented Mar 29, '23

Reducing Capacity of a Fixed Resource As Case Scenarios

Hello Everyone, I am wondering if I could be given a clue as to how to reduce the capacity of any of my fixed resource in the experimenter. For example, if I wanted to introduce a disturbance to my model, and I wish to represent the disturbance in terms of capacity reduction in experimenter. How do I go about it.

If I am to reduce the capacity of say a PLANT (represented by a Processor or Queue) in terms of output to say 35, 50, 0r 70% in other to observe the effects of these on the performance at the final node ( say average available content at the retailer), how can one use the experimenter or Optimization tool to alter these and make them as case scenarios? Thanks for your time

Software Version:

FlexSim 23.1.0 beta

optimization experimenter statistics reducing the operational capacity

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Jason Lightfoot ♦ commented · Mar 29, 2023 at 03:13 PM

Hi @Vyk_k, was Joerg Vogel's answer helpful? If so, please click the "Accept" button at the bottom of their answer. Or if you still have questions, add a comment and we'll continue the conversation.

If we haven't heard back from you within 3 business days we'll auto-accept an answer, but you can always unaccept and comment back to reopen your question.

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Answer 1 · 2023-03-20T06:51:18Z

Joerg Vogel answered Mar 20, '23 Vyk_k commented Mar 20, '23

This is a question of a viewpoint. You build a model without any statistical distributions, because everything works in perfect manner. Then you introduce disturbances by statistical distributions. Results are varying. You want to get an overall relative result, then you need a base value what is 100 percent.
Methods to achieve disturbances are breakdowns (Tool MTBF/MTTR). Varying of times by statistical distributions and their functional parameters.
Availability of products, like you wanted to setup a model parameter, can you interpret as an interval of time. A time interval is short enough to satisfy any demand or not.

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Vyk_k commented · Mar 20, 2023 at 01:58 PM

Thanks, @Joerg Vogel for your input. Could you, please, show me a sample of any of the methods you highlighted( for example, using the MTBF/MTTR) method? Using a basic system comprising of two SOURCES, two PROCESSORS, QUEUES , and SINK with initial 100 or 95% performance and later using MTBF/MTTR to reduce the capacity would be really appreciated becasuse it would givevme the sense of the HOW. Thanks

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Jason Lightfoot ♦ Vyk_k commented · Mar 20, 2023 at 02:30 PM

The MTBF/MTTR tool is well documented on this site and here in the online documentation. Please try to implement something and come back here if you get stuck. We encourage students to do their own models as much as possible.

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Vyk_k Jason Lightfoot ♦ commented · Mar 20, 2023 at 03:17 PM

Thanks for your contribution, @Jason Lightfoot. I appreciate the link you sent as well. The point I just want to make is that examples of certain concepts are still being made for students even after the explanation of the concept. What I am doing is self-learning of FlexSim to use it for my personal project. And I agree with you that students should do their own models as much as possible. However, having an example of the HOW in order to apply it to a more complex model may not be a bad idea. I appreciate your contribution, once again, @Jason Lightfoot.

I have gone through the resource material, and will try to apply it to my model. If I need further clarification, I will appreciate your contribution. Thanks for your time.

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