Production Cell Variable Selection for Operator-Focused Monitoring
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Solution Overview
Problem
The prior art faces challenges in processing a large number of process variables from actuators and sensors in a production cell, leading to high demands on processing capacity and the risk of overwhelming operators with irrelevant information.
Innovation Solution
A computer-implemented method that selectively processes only relevant process variables by determining a subset based on criteria such as configuration, history, and logical dependencies, reducing the number of variables processed and the information overload for operators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all process variables from actuators and sensors are processed, then complete information is available for monitoring and control, but processing capacity requirements (memory, computing power, communication bandwidth) increase significantly
Solution Approach 1:
The patent extracts and processes only the most relevant process variables from the complete set of available variables. The control system identifies and selects a subset of process variables that are most critical for the current production context, excluding less relevant variables to reduce processing demands while maintaining essential monitoring and control capabilities.
Solution Approach 2:
The patent applies different processing quality levels to different process variables based on their relevance. Critical process variables receive full processing attention with real-time monitoring and control, while less critical variables receive reduced processing. This local differentiation optimizes resource allocation by concentrating computing power where it is most needed.
2Loss of information
If all process variables are provided to the operator, then complete information is available for decision-making, but the operator risks being overloaded with irrelevant information
Solution Approach 1:
The system extracts and presents only the most relevant process variables to the operator based on the current production context, machine state, and operational priorities. This selective presentation filters out irrelevant information while maintaining access to critical data needed for effective decision-making.
Solution Approach 2:
The set of process variables presented to the operator is dynamic and adapts based on the current production situation. The system automatically adjusts which variables are prioritized and displayed based on real-time conditions, such as machine state, production phase, and detected anomalies, ensuring the operator receives context-appropriate information.
3Power
If a subset of process variables is processed, then processing capacity requirements are reduced, but the risk of missing relevant information increases
Solution Approach 1:
The system performs preliminary analysis and classification of process variables before the production process begins. Based on historical data, production plans, and machine configurations, the system pre-identifies which process variables are likely to be most relevant for each production scenario. This preliminary preparation enables efficient real-time processing while maintaining reliability by ensuring critical variables are selected in advance.
Solution Approach 2:
The system continuously monitors the performance and relevance of selected process variables and adjusts the subset based on feedback from the production process. If previously excluded variables become relevant due to changing conditions or detected anomalies, the system dynamically includes them in the processed set, ensuring reliability is maintained while optimizing processing capacity utilization.
Data Source
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AI summary
Computer-implemented method for processing a plurality of process variables (Pi) of a production cell (1) which comprises at least one shaping machine as a subunit (2) of the production cell (1), the method using at least one processing unit (5) and comprising at least the steps of: a. for at least one subunit (2) of the production cell (1), the at least one subunit (2) having a plurality of actuators (3) and/or sensors (4), providing to or determining by at least one processing unit (5) a totality (Π) of process variables (Pi) which is available for processing for the plurality of actuators (3) and/or sensors (4) of the at least one subunit (2) b. using at least one processing unit (5) to determine at least one subset (Si) of process variables (Pi) out of the totality (Π) of process variables (Pi) c. processing, during production of a production lot, those process variables (Pi) which belong to the determined at least one subset (Si) of process variables (Pi) d. for those process variables (Pi) which do not belong to any of the determined at least one subset (Si) of process variables (Pi), processing a selected number of process variables (Pi), production cell having at least one processing unit (5) configured to carry out such a method and computer program implementing such a method.