Digital Twin Process Resequencing for Production Module Changes
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Solution Overview
Problem
Conventional industrial production processes require extensive manual efforts and are time-consuming due to the need for shutdowns and manual recalculation of production lines when physical production modules are altered or replaced, leading to sub-optimal process sequences.
Innovation Solution
A process optimizer apparatus comprising a watchdog component to detect configuration changes, a model comparator to identify deviating digital twin data model elements, and a process resequencer to dynamically optimize production processes, allowing for automatic resequencing and minimizing installation and adaptation times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual recalculation of production lines is performed when physical production modules are altered or replaced, then production process accuracy is maintained, but installation and adaptation times increase significantly
Solution Approach 1:
The patent replaces manual mechanical recalculation operations with an automated computer-based system. The process optimizer apparatus automatically detects configuration changes through watchdog components, compares digital twin data models using model comparator components, and performs process recalculation without human intervention, thereby maintaining accuracy while dramatically reducing time loss.
Solution Approach 2:
The system enables self-service automation where the production plant automatically monitors its own configuration changes through watchdog components, self-evaluates deviations using model comparator components, and self-optimizes processes through process resequencer components without requiring external manual intervention.
2Reliability
If production lines are shutdown to alter or replace physical production modules, then system reliability is maintained, but productivity decreases due to extended downtime
Solution Approach 1:
The system performs preliminary automated detection and evaluation actions before physical module changes are completed. Watchdog components monitor configuration changes in real-time, and model comparator components prepare deviation analyses beforehand, enabling seamless process optimization without requiring production line shutdowns.
Solution Approach 2:
The patent enables continuous operation of production lines during module alterations by maintaining automated monitoring and process optimization throughout the transition period. The watchdog and model comparator components continue to evaluate configurations in real-time, ensuring uninterrupted useful action and eliminating productivity losses from shutdowns.
3Manufacturing precision
If extensive manual activities are performed for physical installations and software-related changes, then configuration accuracy is ensured, but device complexity increases
Solution Approach 1:
The patent merges multiple separate manual activities (physical installation verification, software configuration, process recalculation) into a single integrated automated system. The watchdog component detects configuration changes, the model comparator evaluates deviations, and the process resequencer optimizes workflows, combining these functions into one unified apparatus that reduces overall system complexity while maintaining configuration accuracy.
4Productivity
If complete process recalculation is performed by ERP system or manual operators for critical production module changes, then process optimization is achieved, but loss of time increases
Solution Approach 1:
The patent replaces manual ERP system recalculation operations with automated process optimizer apparatus. The model comparator component automatically identifies deviating model elements and the process resequencer component dynamically optimizes production processes, achieving the same productivity improvements as manual recalculation but in a fraction of the time without human intervention.
Data Source
AI summary
Provided is a process optimizer apparatus for optimizing dynamically an industrial production process of a production plant including physical production modules, the process optimizer including a watchdog component adapted to monitor the production modules of the production plant to detect configuration changes within the production plant; a model comparator component adapted to evaluate a production plant data model of the production plant including digital twin data models related to physical production modules of the production plant to identify automatically deviating model elements of digital twin data models related to physical production modules of the production plant affected by the configuration changes detected by the watchdog component; and a process resequencer component adapted to perform a dynamic process optimization of the at least one production process of the production plant depending on the deviating model elements identified by the model comparator component.