Technical System Configuration Using Sequence Pattern Automation
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Solution Overview
Problem
The configuration of technical systems is a complex and time-consuming process, requiring extensive domain-specific knowledge, and existing methods either require manual rule definition by users or provide non-personalized recommendations, making automation inefficient.
Innovation Solution
A computerized method that automatically introduces system components into a technical system based on previous configurations, using an automation unit trained by user-specific data to personalize the configuration process, thereby automating repetitive steps and reducing user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual rule definition is used for automation, then automation capability is improved, but labor intensity and time consumption increase
Solution Approach 1:
The system automatically learns configuration patterns from user actions and generates automation rules without requiring manual rule definition. The automation unit trains on stored configuration sequences and autonomously identifies reusable patterns, making the system self-configuring rather than requiring manual programming of rules.
Solution Approach 2:
The system performs preliminary learning by storing and analyzing configuration sequences in advance. The training data is accumulated from user configurations before automation is activated, allowing the system to pre-process and understand configuration patterns before they are needed for automation.
2Productivity
If personalized automation is implemented, then user-specific efficiency is improved, but system complexity increases
Solution Approach 1:
The system segments the configuration process into distinct sequences of system components that can be independently analyzed and stored. Each configuration sequence is broken down into discrete steps that can be individually learned and reused, reducing the complexity of managing personalized automation rules.
Solution Approach 2:
The system creates copies of configuration sequences from stored training data and applies them to new configurations. Instead of managing complex personalized rules, the system replicates proven configuration patterns from the training database, simplifying the automation mechanism while maintaining personalization.
3Measurement precision
If sequence pattern mining is used, then automation accuracy is improved, but computational complexity increases
Solution Approach 1:
The system applies pattern mining locally to specific configuration sequences rather than analyzing the entire configuration space globally. By focusing on local patterns within individual configuration sequences and storing them for reuse, the system achieves high automation accuracy without the computational burden of comprehensive global analysis.
Data Source
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AI summary
The invention specifies a computerized method for configuring a technical system comprising a sequence (Pi) of system components (Si), whereby each sequence (Pi) of system components (Si) can be assigned to a sequence pattern and whereby the sequence comprises at least one system component (Si), whereby the method comprises the following steps: - specifying a support threshold for sequence patterns (M1) by a user, - starting the configuration of the technical system (M2) by choosing a sequence of system components (Si) by the user (U), - analysing (M3) the chosen sequence (Pi) of system components (Si) and extracting sequence patterns by an automation unit (A), and - introducing (M4) at least one further system component (Si) based on the extracted sequence pattern and according to the support threshold by the automation unit (A). The invention further specifies a computer program product and a computer-readable storage medium.