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When will you need this?

To analyze your raw data and prepare it to represent the arrivals.

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Daily Pattern Arrivals

Model Object

The following Model Object will be used to prepare arrival data: Arrivals \ Daily Pattern Arrivals.

  1. ‘Insert’ this Model Object into your model.
  2. Connect from the black box to the start of your model.
  3. Change the name of the entity on the route created in step 2, to meet your needs.
  4. Open the attached Microsoft Excel Import Sheet.
  5. Enable Macro if prompted.
  6. Paste your data into the worksheet following the instructions provided in the worksheet.
  7. Press the “Prepare Arrival Data for ProcessModel” button.
  8. Copy each days arrival separately, paste them in Stat::Fit, take / export the distribution from Stat::Fit and paste it in the ‘Arrival per quantity’ field of the relevant days arrival route.
  9. Click ‘Send Data to ProcessModel’ and wait for the confirmation prompt.
  10. The data will be automatically imported into your model.

Once you click the Prepare Arrival Data for ProcessModel, depending on the raw data provided you should see upto three new worksheets in the same Excel file.

  1. Daily Pattern Daily Qtys
  2. Daily Pattern Hourly Qty
  3. Daily Pattern Acuity

The default tab after clicking button will always be Daily Pattern Daily Qtys.

Analyzing the Daily Pattern Daily Qtys

The Daily Pattern Daily Qtys worksheet is divided into three parts.

1. Raw Daily Arrivals

The first section of the Daily Pattern Daily Qtys is the Raw Daily Arrivals, you can review the raw data and see how the outliers change the way data is presented. The Whisker chart on the right helps review the outliers in more detail with the dots (•) representing any outliers. If you added holidays data with your raw arrivals, you should see the days with holidays highlighted in green.

Raw Daily Arrivals

2. Daily Arrivals Outliers

In the second section you can review only the outliers. This section can be referenced to know what the data that was removed from the final data that will come below.

Daily Arrivals Outliers

3. Daily Arrivals without Outliers

In this section you can review and use the final arrivals data with outliers removed. This section contains 3 steps that must be followed, the steps are highlighted in red.

Step 1. Click the Copy button on each of the rows representing the day of the week to copy the particular day arrivals, go back to ProcessModel and use Stat:Fit to fit a distribution.

Daily Arrivals without Outliers Step

Step 2. Copy/Export the distribution from Stat:Fit and paste it in the associated purple box.

Daily Arrivals without Outliers Step

Step 3. Click the Send Data to ProcessModel button. This will import all the raw data into ProcessModel, once the import is completed you will receive a prompt informing you of the same.

Daily Arrivals without Outliers Step3

See Chapter 3.12.2 – Convert Raw Data to Distributions of the User’s Guide to learn more about Stat:Fit.

Analyzing the Daily Pattern Hourly Qty

The Daily Pattern Hourly Qty worksheet contains the hourly distribution of arrivals and has charts on the right for each  day that show the hourly distribution of arrivals for each day of the week, scroll down to review charts for all the days. There is no interaction required on this worksheet as it only displays useful  daily hourly patterns for review.

Distribution of Hourly Arrivals

Analyzing the Daily Pattern Acuity

The Daily Pattern Acuity worksheet contains a table that shows the distribution of priority across all entities. There is no interaction required on this worksheet as it only displays useful  priority information for review.

Distribution of Priority

Advanced Topic

Question: How the Daily Pattern Arrivals model was created and why you see an object instead of a separate entity and activities.

Answer: The Daily Pattern Arrivals model object has multiple entities and routes that need to be updated with the raw data, all the activities and routes, which the  user does not need to change individually are grouped together with an object on top of  it.

Daily Pattern Arrivals Exploded View

Daily Pattern Arrivals Exploded View