Clothes Dryer Cycle Modifier Selection Using Historical User Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Laundry treating appliances, such as clothes dryers, often require user intervention to adjust cycles based on feedback due to inconsistent drying results, which can be time-consuming and inconvenient, especially when previous cycles were not satisfactory.
Innovation Solution
A method and system for a clothes dryer that uses historical user feedback to automatically adjust cycle modifiers, such as drying time and temperature, without soliciting feedback if previous cycles were satisfactory, and solicits feedback if previous cycles were not, to update settings for future cycles of the same type.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the dryer solicits user feedback after every cycle to improve drying accuracy, then the precision of drying results is improved, but the operation time and user burden increase
Solution Approach 1:
The system performs preliminary actions by storing historical feedback data and pre-processing it into performance indicators before they are needed. When a new drying cycle is initiated, the system retrieves and analyzes previously stored feedback information, allowing it to make informed adjustments without waiting for real-time user input during the current cycle.
Solution Approach 2:
The dryer system serves itself by automatically analyzing historical feedback data and adjusting its own drying parameters without requiring continuous user intervention. The system maintains a database of user responses and uses this information to autonomously optimize future drying cycles, reducing the need for users to manually adjust settings each time.
2Adaptability or versatility
If the dryer automatically adjusts cycle parameters based on historical feedback, then the adaptability to user preferences is improved, but the system complexity increases
Solution Approach 1:
The feedback processing system is segmented into distinct functional modules: a feedback collection module that gathers user responses, a data storage module that archives historical information, an analysis module that processes the stored data, and a parameter adjustment module that applies learned preferences to future cycles. This modular architecture manages complexity by separating concerns and allowing each component to be independently optimized.
Solution Approach 2:
The system introduces an intermediary data layer between the user feedback and the drying parameters. Historical feedback is stored and processed through intermediate algorithms that translate qualitative user responses into quantitative parameter adjustments. This intermediary processing layer simplifies the overall system by providing a structured method for converting diverse feedback into actionable adjustments.
3Ease of operation
If the dryer requests feedback only when necessary based on cycle comparison, then the ease of operation is improved, but the speed of adapting to preferences may be reduced
Solution Approach 1:
The feedback solicitation strategy is made dynamic rather than static. The system adaptively determines when to request feedback based on multiple factors including whether the current cycle type matches previous cycles, the confidence level of existing performance indicators, and the consistency of historical feedback patterns. This dynamic approach allows the system to minimize user interactions while maintaining effective adaptation.
Solution Approach 2:
The system changes its operational parameters based on the accumulation of historical data. Initially, the system may request feedback more frequently to build a sufficient data foundation. As more historical feedback is collected and analyzed, the system adjusts its parameter to request feedback less frequently, trusting its learned patterns. This parameter change over time balances adaptation speed with ease of operation.
Data Source
AI summary
Selecting cycle modifiers for a clothes dryer is provided. Responsive to a requested cycle of operation for drying a load and a previous cycle being the same cycle type, and further responsive to historical information for the previous cycle indicating positive user feedback that dryness of the load was correct, cycle modifiers corresponding to the requested cycle are applied, and the clothes dryer is operated without soliciting further user feedback. Responsive to the requested cycle and the previous cycle being different cycle types, or responsive to the historical information for the previous cycle indicating negative user feedback that the dryness of the load was incorrect, apply the cycle modifiers corresponding to the requested cycle, operate the clothes dryer, and solicit further user feedback with respect to the cycle of operation of the clothes dryer to update cycle modifiers for use in future cycles of the same cycle of operation.