Page 322 - ExtendSim User Guide

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Statistics and Model Metrics
Commonly used blocks
Remember that, by itself, simulation does not provide exact answers or optimize a system. Instead, a well-built model will capture important data and report statistical results. These met- rics should provide the information needed for the analysis and decision-making process.
This chapter discusses specific methods for statistically analyzing discrete event models, such as:
• Gatheringstatisticsforspecifictypesofblocks
• Clearingstatisticalaccumulatorsafterawarm-upperiod
• UsingtheHistoryblocktogetiteminformation
• Trackingchange-of-stateinformationaboutitems
• Using attributes to accumulate information about items
• Determining cycle time by timing the flow of items
• When to use time weighted statistics
For a more generalized discussions of statistical analysis, see also the following chapters: • “Math and Statistical Distributions” starting on page 693
• “Analysis”startingonpage641
☞ The models illustrated in this chapter are located in the folder \Examples\Discrete Event\Statis- tics.
Commonly used blocks
The following blocks will be the main focus of this chapter. The block’s library and category appear in parentheses after the block name.
Clear Statistics (Value > Statistics)
Clears statistics in other blocks, eliminating the statistical bias of the warm-up period.
Display Value (Value > Outputs)
Displays and outputs the value that is input.
History (Item > Information)
Records information about items and their properties, such as the value of an attribute, the item’s arrival time, its priority, and so forth.
Information (Item > Information)
Reports item statistics such as a count of the number of items, the throughput rate, cycle time, and the time between item arrivals.
Mean & Variance (Value > Statistics)
Calculates a mean, variance, standard deviation, and confidence interval.
Statistics (Value > Statistics)
Summarizes statistics for a particular type of block, such as activities or queues.
Reports results in a table. Information is calculated using a specified statistical method, which can be customized.
Discrete Event
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