Dishwasher Load Forecasting for Automatic Cleaning Cycle Timing
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Solution Overview
Problem
Users of household dishwashers often face challenges in timing the cleaning cycles, leading to either insufficient clean dishes or unnecessary energy consumption due to unpredictable dish loading patterns, which can result in either a lack of clean dishes when needed or inefficient use of resources.
Innovation Solution
A dishwasher with a data memory that forecasts dish loading patterns, allowing for automatic or suggested start times of cleaning programs based on predicted payload requirements, optimizing energy use and ensuring adequate clean dishes are available when needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the cleaning program is started immediately when the dish baskets are full, then clean dishes are made available quickly, but energy is consumed unnecessarily when the loaded dishes can still accommodate more capacity
Solution Approach 1:
The control system performs preliminary analysis of the data set containing forecast information about future dish loading patterns. Before activating the cleaning program, the system predicts whether the tub will have sufficient capacity to accept additional dishes, and only then decides to start the cleaning program. This preliminary forecasting action prevents unnecessary energy consumption while ensuring clean dishes are available when needed.
2Use of energy by moving object
If the cleaning program is delayed to save energy, then energy consumption is reduced, but clean dishes may not be available when needed
Solution Approach 1:
The control system continuously monitors the data set containing forecast information about future dish loading patterns. Based on this feedback about predicted loading times and quantities, the system dynamically adjusts the timing of the cleaning program. The feedback mechanism ensures that cleaning is delayed only when forecasts indicate sufficient capacity, and activated promptly when forecasts predict the tub will be full, thus balancing energy savings with clean dish availability.
3Productivity
If the dishwasher capacity is used to maximum, then loading efficiency is improved, but the risk of insufficient capacity for unexpected loads increases
Solution Approach 1:
The control system performs preliminary analysis of forecast data about future dish loading patterns before making decisions about cleaning program activation. By predicting future loading times and quantities in advance, the system can determine the optimal moment to start cleaning that maximizes current capacity utilization while ensuring sufficient room remains for predicted future loads, thus maintaining both high loading efficiency and reliable capacity availability.
4Productivity
If the cleaning program is run frequently to ensure clean dishes are available, then clean dish availability is improved, but energy consumption and water usage increase
Solution Approach 1:
The control system uses feedback from the data set containing forecast information about future dish loading patterns to intelligently determine when cleaning programs are truly necessary. The system analyzes predicted loading times and quantities to identify optimal cleaning moments, running cleaning programs only when forecasts indicate the tub will be full or nearly full. This feedback-driven approach eliminates unnecessary frequent cleaning cycles, reducing energy and water loss while maintaining adequate clean dish availability.
Data Source
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AI summary
A dishwasher, in particular a household dishwasher, comprises a tub (1) which can be loaded with a quantity of dishes, wherein the tub (1) has at least one dish rack (2a, 2b, 2c) for receiving dishes. The dishwasher also includes a data storage device (9b) with a data record defining at which times a load of a specific quantity of dishes is to be expected into the tub (1). Depending on the data record, a controller 9a activates a start release at a specific release time to execute a cleaning program.