Autonomous Process Control via AI-Driven Spectrometer Feedback
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Solution Overview
Problem
Existing methods for controlling biological, chemical, or physical processes face challenges in precisely and reproducibly adjusting process parameters, such as temperature and substance flow, leading to unstable and non-reproducible outcomes.
Innovation Solution
A method and apparatus that measure and evaluate the process response to adjustments in effect parameters, using computer-implemented evaluations to optimize setting values for these parameters, enabling continuous and autonomous control of processes without external intervention, employing AI for learning and adjusting settings based on process responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to adjust process parameters, then the apparatus can operate with simple control mechanisms, but the control precision and stability deteriorate
Solution Approach 1:
The patent implements a feedback mechanism where the apparatus measures the process response to adjustments in effect parameters, evaluates this response using computer-implemented methods, and uses the evaluation results to determine subsequent adjustments. This closed-loop feedback system enables precise and stable control by continuously adapting to actual process outcomes rather than relying on open-loop conventional control.
Solution Approach 2:
The apparatus performs autonomous control by independently measuring process responses, evaluating them through computer-implemented algorithms, and self-adjusting effect parameters without external intervention. This self-service capability allows the system to optimize its own control strategy, achieving high precision while maintaining operational simplicity through automation.
2Productivity
If manual control methods are used, then the apparatus requires less computational resources, but the productivity and information gathering speed deteriorate
Solution Approach 1:
The patent replaces manual mechanical control with computer-implemented evaluation systems that automatically measure process responses and determine parameter adjustments. This substitution of computational methods for manual operations dramatically increases information gathering speed and productivity while enabling full autonomous control capability through algorithms that process data and make control decisions without human intervention.
3Productivity
If multiple processes are run in parallel, then the overall productivity increases, but the control stability of individual processes deteriorates
Solution Approach 1:
The patent applies segmentation by independently controlling each parallel process through separate effect parameters that can be individually adjusted based on their specific process responses. The computer-implemented evaluation system processes feedback from each process independently, allowing customized control strategies for each parallel operation while maintaining overall system coordination, thus preserving control stability even at high throughput.
Data Source
Figure 1
AI summary
To improve the autonomous control of a process (2) by means of an apparatus (1) through the adjustment of at least one controlling parameter (3) of the process (2), it is proposed that a process response (4), which the process (2) transmits to its immediate environment in response to an adjustment of the at least one controlling parameter (3), be measured by a measuring instrument (17), preferably a spectrometer (18) integrated into the apparatus (1), and be evaluated by computer, preferably using artificial intelligence, and that the at least one controlling parameter (3) be automatically readjusted based on this evaluation. This approach is applicable to biological, chemical, and physical processes (Fig. 1).