Hi everyone, recently @Arun Kr posted this idea to add a utilization vs. time chart to the available chart types in FlexSim. I had previously build a relatively easy to set up Statistics Collector for use in our models. I have since cleaned up the design a bit and thought to post it here, since this seems to be a commonly desired feature. utilization_vs_time_collector_24_0_fm.fsm All necessary setup is done through labels of the collector. The first three are actually identical to labels found on the default Statistics Collector behind a state bar chart. - Objects should point at a group that contains all objects the collector should track the utilization for. - StateTable is a reference to the state table that will be used to determine which state counts as 'utilized'. - StateProfile is the rank of the state profile that should be read on the linked objects (0 for default state profile). - MeasureInterval is the time frame (in model units) over which the collector will take the average of the utilization. - NumSubIntervals determines how often that measurement is actually taken. In the example image above (and the attached model) the collector measures the average utilization over the last 3600s 12 times within that interval of every 300s. Each meausurement still denotes the utilization over the complete "MeasureInterval". The graph on the left takes a measurement every 5 minutes, the one on the right every 60 minutes. Each point on both graphs represents the average utilization over the previous hour from that time point in time. - StoredTimeMap is used to allow the collector to correctly function past a warmup time, by storing the total utilized value of each object up to that point. This should no be manually changed. Since this last label has to be automatically reset, remember to save any changes made to the other labels by hitting "Apply". The collector works by keeping an array of 'total utilized time' value for each object as row labels. Whenever a measurement is taken, the current value is added to the array and the oldest one is discarded. The difference between the newest and oldest value is used to calculate the average utilization over the measurement interval. The "NumSubIntervals" label essentially just controls how many entries are kept in that array. To copy the collector into another model you can create a fresh collector in the target model. Then copy the node of this collector from the tree of the attached model and paste it over the node of the fresh collector. I hope this can help to speed up the modeling process for some people (at least until a chart like this is hopefully implemented in FlexSim) or serve as inspiration for how one can use the Statistics Collector. I might update the post with a user library version if I get to creating it (and if there is demand for it). Best regards Felix Edit: Added user library with the collector as a dragable icon to the attached files. Edit2: I noticed a bug while using the collector. Having the tracked objects enter states that are marked as "excluded" in the state table would lead to incorrect utilization values (possibly even below 0 or above 100%). Replaced the library with an updated version that fixes this. Edit3: I fixed another bug that resulted in a wrong utilization value for the first measurement after the warmup time if the object spent time in an excluded state prior to the warmup. utilization-vs-time-collector-library-20250212.fsl

ContinuousUtilization_4.fsm In the attached model, you'll find a Utilization vs Time chart driven by a Statistics Collector and a Process Flow. This article is an alternative approach to the chart shown here: https://answers.flexsim.com/content/kbentry/158947/utilization-vs-time-statistics-collector.html Thanks @Felix Möhlmann for putting that article together. The concept in this model is very similar, but this is a different approach. There are pros and cons to each method. This method offers some performance improvements at the cost of writing more FlexScript code. This method also doesn't handle Warmup time, where the other method does. The general idea in this model is to keep a history of state changes for the previous hour (or other time interval). The history adds new info as states continue to change and drops old info as it "expires" by being older that the time interval. I chose to use a Bundle (stored on a token label) for the history. Bundles are optimized to add data to the end. If a bundle is paged (they are by default), then they are also optimized to remove data from the beginning. [Begin Technical Discussion - TLDR; Bundles are fast at removing the first row and adding new rows] A paged bundle keeps blocks of memory (pages) for a certain number of rows. If a page fills up, it allocates another page. It keeps track of the location in the page for the next entry. Similarly, it keeps track of the location of the first entry on the start page. If you remove the first row, that start location is moved forward on the page. If the start location gets to the end of a page, that page is dropped and the start location moves to the next page. [End Technical Discussion] The Process Flow maintains the history table. Whenever the object's state changes, the Process Flow adds a new entry to the history table. This part is straightforward. The tricky part is properly "expiring" the data. To do this, a second set of tokens wait for the last of the oldest data to expire. When the oldest set of data should expire, the tokens remove any rows that are too old and then wait for the next oldest row. If there are no expired rows, the tokens wait for one "time interval" and then check again. This is because if there is no expired data, data can't expire for at least one time interval. In this way, the history table is always kept up to date. The Statistics Collector is configured to post-process the history table. It calculates the total utilization, including the state that the object is currently in, as well as the state being "phased out" from the history table. The Statistics Collector can do this calculation at any point in the model. So the sampling interval (called Resolution in the model) is independent from the time window.