Making a production plan and checking it twice, gonna find out what’s naughty and nice.
For many years simulation has been used to determine the best method of designing production lines, services systems and also helping engineers make decisions about how to make those operations more effective.
Seasonality along with varying types of items or services being offered can impact everything from storage of raw materials, changeovers, and warehousing. Arena allows users to better understand how these factors work together and their impact on production. The key is having an accurate model that reflects the variability in the real world system. We do this in a few ways –
- Expressions - Arena’s ability to reference expressions and read in expressions from outside data sources allows our clients to analyze how their system may react to changes specifically when there are varying processing times based on the types of entities flowing through the system.
- Variability - The effect of seasonality on an operation is generally modeled by varying the arrival rate of orders or perhaps patients into a system. Arena’s Arrival Schedules can be used and populated with variable values that can be read in from data sources as well to give you the maximum amount of flexibility in comparing scheduling scenarios.
- Direct Read - Arena’s Direct Read functionality makes it easier to read in variables and expressions to test out differences in schedules and to determine what scenarios to focus upon for further analysis. To learn more about Arena's Direct Read functionality, check out Nancy's article on Connecting Models to Live Data!
- Changeovers - Modeling the effect of changeovers on a system is one instance in which we frequently are asked to design. We can create the model to handle the logic of the changeover so that when different schedules are read in, the client can see how it affects the throughput of items through the system.
Below is one of the simplest methods of handling changeovers that also utilizes Arena’s Expressions. If you would like a copy of this model, please reach out to us at email@example.com.
A variable is used to keep track of the current product that is in process. Once the next item in queue is able to seize the equipment the decision logic determines if the current product on the equipment is the same thing or different. If it is different then a setup time is defined and the product in process is updated accordingly. If it is the same, the setup time is set to zero and won’t impact the line.
As seen in the Assign module for defining a setup time for the part, it is defined via referencing an expression and using the part type attribute to detemrine which array member’s equation will be used to assign the setup that is appropriate for the part. When no setup is required the attribute a_SetupTime is set to zero.
Incorporating this type of logic into a model can help to determine whether or not a highly variable product schedule is impacting the throughput. If that is the case, then the user can proceed to incorporate logic into the model that would mimic business rules around reordering queues for products or various types of schedules can be tested.