Mechanical Engineering and Assembly Production (PP + PS)

Production and assembly, e.g. in mechanical engineering, are often complex processes, operated over several manufacturing levels and containing many tasks such as planned orders, production orders or network plans (when using SAP ERP PS-module). A collective order like this, is manageable by strictly linking definitions (make-to-order production, project connections from SAP ERP PS). If certain restrictions are met, such as a particular production level or special materials, make-to-stock production is usually applied.

Comprehensive view: If there is a need to view all steps necessary for project success at once, a network of elements has to be established, which considers static links as well as relations determined by dynamic pegging.

The capacity planning of SAP-Modules PP + PS is considered in their entirety: objects from the SAP PS-module in the form of network plans, as well as planned orders and production orders, send information to actual capacity demands at the assembly line. ORSOFT Manufacturing Workbench unifies information from both the modules SAP PP and SAP PS into one user interface and one temporary in-memory data model.

Up-to-date information: Latest and reliable ATP and CTP information is available at any time with this in-memory solution. Highly efficient algorithms, processed in the RAM database, allow users to constantly update dynamic pegging relationships across all networks and chains whenever an object is modified.

Transparency: An intelligent alarm and conflict management ensures transparency along the entire supply chain, which may easily consist of many thousand BOM components across several production stages.

Planning within the control circuit instead of hierarchical structures: Modifications of SAP PS objects have an impact on SAP PP objects and vice versa. Both data areas remain consistent.

Simulation scenarios: Implemented planning actions allow several simulated planning scenarios to be conducted. That way adequate compromise for existing bottlenecks can be identified and customer orders can be prioritized.