Commercial Dishwasher Vision Control for Adaptive Washware Cleaning
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Solution Overview
Problem
Conventional commercial dishwashers lack automatic differentiation of washware types, leading to inefficient resource usage and suboptimal cleaning results due to factory-preset programs that compromise on washware categories, resulting in overwashing or insufficient cleaning.
Innovation Solution
A commercial dishwasher equipped with a camera system and evaluation device that learns from usage patterns to adjust treatment parameters automatically, optimizing resource consumption and cleaning efficiency by identifying and adapting to specific washware categories and usage behaviors through machine learning algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If factory-preset treatment programs are used for all washware, then the dishwasher can operate with simple control logic, but resource consumption increases and cleaning efficiency decreases due to overwashing or insufficient cleaning
Solution Approach 1:
The system dynamically changes treatment parameters (temperature, water flow rate, chemical dosage, cycle duration) based on the detected washware category. The control device selects different parameter sets from stored programs corresponding to different washware types, enabling optimized resource usage while maintaining effective cleaning for each specific category.
Solution Approach 2:
The dishwasher transitions from static factory-preset programs to dynamic adaptive control. The system continuously observes washware characteristics, identifies the category in real-time, and adjusts treatment parameters accordingly during operation, making the cleaning process responsive to actual conditions rather than following fixed predetermined cycles.
2Manufacturing precision
If factory-preset treatment programs are used for all washware, then device complexity remains low, but cleaning precision deteriorates due to compromise settings that cannot optimize for specific washware categories
Solution Approach 1:
The system replaces manual program selection with automatic optical detection and machine learning-based identification. The camera system captures images, the evaluation device processes them using machine learning algorithms to identify washware categories, and the control device automatically selects appropriate treatment programs, eliminating the need for manual intervention while achieving precise cleaning optimization.
Solution Approach 2:
The dishwasher performs self-identification of washware categories and self-adjustment of treatment parameters without operator intervention. The system autonomously observes the washware, determines the category through machine learning, and automatically configures the optimal cleaning program, making the complex identification and decision-making processes transparent to the user.
3Ease of operation
If manual program selection is required for different washware types, then treatment can be optimized for specific categories, but ease of operation decreases due to additional manual steps
Solution Approach 1:
The system autonomously performs washware identification and program selection without requiring manual input from the operator. The camera system automatically captures images, the evaluation device identifies the washware category using machine learning, and the control device selects and executes the appropriate treatment program, completely eliminating manual program selection steps while maintaining optimal cleaning precision.
Solution Approach 2:
The system implements a closed-loop control where the detection of washware characteristics provides feedback that automatically triggers the selection and execution of the corresponding optimized treatment program. This feedback mechanism ensures that the most appropriate cleaning parameters are always applied based on the actual washware present, without requiring manual intervention.
Data Source
AI summary
A commercial dishwasher includes at least one washing system for washing washware, having at least one rinsing system for rinsing the washed washware, and optionally a drying system for optimal drying of the rinsed washware. The dishwasher includes a camera system configured to capture at least one image of the washware to be treated in the dishwasher. An evaluation device is further provided, which is configured so as to create a pattern relating to the temporal usage behavior of the operator of the dishwasher, in particular in the course of a profiling process based on the captured images.