Method and system for setting parameters of a treatment cycle
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Solution Overview
Problem
Household appliance users face challenges in setting optimal treatment cycle parameters, such as temperature, duration, and cleaning agent dosage, due to the complexity of interdependent parameters and lack of user-specific settings, leading to suboptimal cleaning performance and resource efficiency.
Innovation Solution
A method and system that use a predictive model, based on sensor data and user inputs, to determine the best combination of configuration parameters for achieving desired treatment performance, such as cleanliness, energy efficiency, or eco-friendliness, by analyzing variance and using design of experiments approaches like I-optimal and response surface methodology.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users set all parameters individually, then customization capability is improved, but operation complexity increases and requires technical expertise
Solution Approach 1:
The patent introduces an intermediary system (the method and data processing device) that mediates between the user's simple performance target input and the complex parameter setting. The system automatically translates the user's performance goal into optimized parameter combinations, eliminating the need for users to directly handle complex parameter interdependencies while still achieving customized treatment cycles.
Solution Approach 2:
The system enables self-service by allowing users to simply input their desired treatment performance without needing to understand the underlying parameter complexity. The automated device performs the parameter optimization work itself, making the system serve the user's needs directly without requiring their technical expertise.
2Ease of operation
If preset programs are used, then ease of operation is improved, but treatment performance precision deteriorates due to standard settings not reflecting user-specific needs
Solution Approach 1:
The patent transforms static preset programs into dynamic, adaptive parameter settings. Instead of fixed standard settings, the system dynamically generates optimized parameter combinations based on the user's specific performance targets and the modeled interdependencies, allowing the treatment cycle to adapt to precise user needs while maintaining ease of operation.
Solution Approach 2:
The system enables precise treatment performance by allowing flexible adjustment of parameters based on user-defined targets. Rather than being constrained to fixed preset values, the optimized parameters can be dynamically changed to match specific performance requirements, achieving both ease of operation and precision.
3Manufacturing precision
If complex parameter combinations are used, then treatment performance is improved, but device complexity increases
Solution Approach 1:
The patent extracts the complexity of parameter interdependencies from the user interface and concentrates it in the data processing device. By taking out the complex modeling and optimization calculations from the user's task and placing them in the automated system, the patent achieves high treatment performance without exposing users to the underlying complexity.
4Adaptability or versatility
If manual parameter setting is used, then adaptability to user needs is improved, but time consumption increases due to lack of precise guidance
Solution Approach 1:
The patent applies preliminary action by pre-modeling the interdependencies between parameters before the user needs to set them. The system prepares optimized parameter recommendations in advance based on the user's performance targets, eliminating the time-consuming trial-and-error process that would otherwise be required to achieve adaptability to user needs.
Data Source
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AI summary
A method and system for setting parameters of a treatment cycle in a household appliance is provided. First a model establishing a relationship between sets of configuration parameter values of achievable treatment performance is obtained. Then a target treatment performance for the treatment cycle is obtained. Values for a subset of a configuration parameter are fixed, the subset comprising at most all configuration parameters but a remaining configuration parameter. Then, a value for the remaining configuration parameter is determined. For this value, a difference between the target treatment performance and an achievable treatment performance predicted by the model using said value is below a predetermined threshold. Finally, the parameters of the treatment cycle, which can be setting parameters of the treatment cycle in the household appliance are output. The parameters comprise the determined value and the fixed values.