Washing Machine Control Panel with Self-Learning Mode Prioritization
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Solution Overview
Problem
Current washing machines lack intuitive control methods for managing various washing modes and options, requiring users to manually select and edit settings, which can be cumbersome and inconvenient, especially when controlling external devices like dryers.
Innovation Solution
A washing machine with a control panel featuring a display and inputter that automatically prioritizes frequently used washing modes, allows mode editing, and enables remote control of external devices through a communication circuitry, allowing users to easily select and manage washing modes and options via a jog dial interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If washing machines provide multiple washing modes and options, then washing functionality and adaptability are improved, but control complexity and user operation difficulty increase
Solution Approach 1:
The control panel automatically learns and stores frequently used washing mode combinations, then presents them as pre-configured options to users. This self-learning mechanism reduces the need for users to manually navigate through multiple settings, as the system proactively provides commonly needed configurations based on past usage patterns.
Solution Approach 2:
The system pre-configures washing modes by automatically combining frequently selected washing options into ready-to-use packages. By performing this configuration action in advance and storing it in memory, the system eliminates the need for users to repeatedly manually set the same parameters, thereby simplifying subsequent operations.
2Measurement precision
If washing machines require manual selection and editing of washing modes, then control precision is improved, but user convenience and time efficiency deteriorate
Solution Approach 1:
The control panel autonomously monitors user selections and automatically identifies frequently used washing mode combinations. This self-service learning process occurs in the background without requiring user intervention, allowing the system to accumulate data and generate optimized presets while users simply operate the machine as needed.
Solution Approach 2:
The system continuously receives feedback from user selections and uses this information to update its understanding of preferred washing configurations. By analyzing usage patterns and adjusting the presented options accordingly, the system refines its recommendations over time, maintaining control precision while reducing the time users spend on manual configuration.
3Ease of operation
If washing machines automatically provide frequently used washing modes, then user convenience is improved, but device complexity increases
Solution Approach 1:
The control panel incorporates a self-learning capability that automatically monitors and analyzes user selections of washing modes and options. This self-service function enables the system to autonomously identify patterns and generate frequently used mode combinations without requiring external programming or complex user setup procedures.
Solution Approach 2:
The system creates simplified copies of frequently used washing mode combinations by storing the essential parameter sets in memory. Instead of requiring users to navigate through all original settings each time, the system presents condensed versions that replicate the most commonly needed configurations, thereby reducing operational complexity while maintaining functionality.
4Productivity
If washing machines store and recall washing mode selections, then operational efficiency is improved, but memory and data management requirements increase
Solution Approach 1:
The control panel extracts and stores only the essential elements of frequently used washing mode combinations - specifically the core parameter sets that define each mode. By isolating and saving only these critical data points rather than storing complete configuration records, the system achieves efficient recall functionality while minimizing memory consumption.
Solution Approach 2:
The system implements partial storage by maintaining records only for washing modes that are actually frequently used, rather than storing all possible mode combinations. This selective approach ensures that memory resources are allocated to storing data that provides tangible operational benefits, avoiding unnecessary data management overhead for rarely or never-used configurations.
Data Source
AI summary
Disclosed herein is a washing machine and a control method thereof, and more particularly, to a technology capable of controlling washing modes in various manners by manipulating a control panel of the washing machine. The washing machine includes a display configured to display a washing mode, an inputter configured to receive a washing mode select command, a storage configured to store a selected washing mode, and a controller configured to allow a washing mode, which has the largest number of times selected during a predetermined number of times of washings, to be displayed on a first screen of the display, and in response to the number of the washing mode having the largest number of selection times being plural, configured to allow a washing mode, which is the last selected among the plurality of washing modes, to be displayed on the first screen of the display.