How to use /SAPPO/RESI_TIME - Residenzzeit für PPO-Aufträge

SAP Transaction Code - Details

• Transaction Code: /SAPPO/RESI_TIME

  Description: Residenzzeit für PPO-Aufträge

  Release: S/4HANA and ECC 6

• • Program:

    Screen: 0

    Authorization Object:

  • Development Package: /SAPPO/ARCHIVING

    Package Description: PPO Archiving

    Parent Package: /SAPPO/MAIN

  • Module/Component: CA-GTF-TS-PPO

    Description: Postprocessing Office

Smart SAP Assistant

• SAP Tcode: /SAPPO/RESI_TIME - Residenzzeit für PPO-Aufträge

  
  Overview: 
  The SAP transaction code /SAPPO/RESI_TIME is used to view the residence time for production orders in the Production Planning and Control (PP/DS) module. This transaction code allows users to view the residence time of production orders in the system, which is the amount of time a production order spends in a certain status. 
  
  Functionality: 
  The /SAPPO/RESI_TIME transaction code provides users with an overview of the residence time of production orders in the system. It displays the residence time for each status of a production order, such as released, started, and completed. This information can be used to analyze and optimize production processes. 
  
  Step-by-step How to Use: 
  1. Enter the transaction code /SAPPO/RESI_TIME into the command field. 
  2. Select the desired plant and enter a date range for which you want to view the residence time. 
  3. Select the desired order type and enter an order number if desired. 
  4. Click “Execute” to view the residence time for each status of the production order. 
  5. To view more detailed information, click on “Details” in the top right corner of the screen. 
  6. To export the data, click on “Export” in the top right corner of the screen and select your desired file format. 
  
  Other Recommendations: 
  It is recommended that users analyze their production processes regularly to ensure that they are running efficiently and effectively. The /SAPPO/RESI_TIME transaction code can be used to identify areas where improvements can be made in order to optimize production processes. Additionally, it is recommended that users export their data regularly in order to track changes over time and identify trends in their production processes.