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Overview

We are excited to announce updates to our standard analytics data model, which includes the addition of sub-job data. If your plant is using the sub-job feature in shoplogix, then you will find this data helpful to get more detailed and flexible insights into sub-job level production insights.

What are Sub-Jobs?

Sub-Jobs are a feature in shoplogix that allows users to manage subproducts with different cycle times for the same job. Sub-Jobs are defined as part of the job import process into shoplogix.
If you are interested in using sub-jobs, or want to learn more, reach out to your shoplogix representative to see if this feature is right for you.

Deployment and Data Refresh

When these updates are deployed:

  • Live Data Update: All live data (data within the last 60 days, as of the deployment date in May 2024) will be updated to include the new dimensions.

  • Historical Data: Historical data will not automatically include the new dimensions. To update historical data, a history refresh must be requested from our support team.

New Dimensions and Fields

The following new dimensions and fields have been added:

  • Dim SubJobs

  • Fact Subjob Scrap

image-20240416-172735.pngimage-20240416-172817.png

New Formulas

Two new formulas have been introduced for accurate sub-job reporting:

  • SubJob Total Production

    sum([Total  Production])/(sum([Total Job Cycle Factor])/sum([Total sub_job_cycle_factor]))
  • SubJob Good Production

    sum([Total  Production])/(sum([Total Job Cycle Factor])/sum([Total Subjob Cycle Factor])) - [Total Subjob Scrap Amount]

Dedicated formulas and data fields are required to report sub-jobs in analytics. These formulas/fields must be used when reporting on sub-jobs. The existing formulas/values from fact core WILL NOT work.

Supported Use Cases

The following metrics and use cases are now supported:

  • Metrics:

    • Sub-Job Scrap Amount

    • Sub-Job Scrap Reason with Scrap Amounts

    • Sub-Job Total Production

    • Sub-Job Good Production

    • Sub-Job Cycle Factor

    • Other core data such as total hours, downtime hours, and uptime hours by sub-job

  • Use Cases:

    • Breakdown of sub-job level data by Job and/or Job Instance

image-20240403-234239.png

Notice above that the “Total Production” value is duplicated. That is why we must use the “SubJob Total Production” value, as it uses a formula to derive its value based on the sub-job cycle factor

  • Rollup/Summary by Sub-Job across multiple days or job instances

image-20240403-231925.png
  • Scrap reasons and amounts by sub-job, also at rollup level across multiple job instances

image-20240403-234422.png
  • Breakdown of sub-job level data by Shift

image-20240416-170818.png

Limitations

While the new dimensions and fields enhance the reporting capabilities, there are some limitations:

  • Sub-Job Total Production Reporting: Reporting on Sub-Job Total Production in the same widget that is pivoted by scrap reason is not supported.

image-20240329-165540.png

Notice that the second widget (without a scrap reason) has 2 extra job instance records that are missing in the first widget. If you add a scrap reason to a widget, it will filter out Fact Core records that do not have scrap assigned.

Scrap reasons should only be used in a widget that measures the actual sub-job scrap amount

  • Calculated Metrics Including Scrap (e.g., OEE): These metrics can only be accurately calculated at the parent job level.

image-20240403-232542.png

Notice above that the OeeProductive value (which is used to calculate OEE in Analytics) is the same for both sub-jobs even though one of them had scrap.
In order to accurately calculate OEE, it should be done at the parent job level, as this will ensure all sub-job level scrap is included in the calculation

By following these guidelines, you can ensure accurate and insightful reporting on your sub-job data. If you have any questions or need assistance with the updates, please contact our support team.

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