Flexible sequence control and method for automated cleaning system of a cooking device
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Solution Overview
Problem
Current automated cleaning systems for hot-air-steamers lack the ability for operators to adjust or customize cleaning sequences based on specific needs, such as varying soiling levels, resource usage, and cost considerations, leading to inefficient resource consumption and lack of cost monitoring.
Innovation Solution
A controller system with a user interface that allows operators to set and adjust cleaning parameters like time, temperature, mechanical action, and chemical action, enabling customization of cleaning sequences for optimized resource use and cost management, including the ability to store and recall successful cleaning cycles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current automated cleaning systems use fixed preset cleaning sequences, then the system is simple to operate, but the system cannot adapt to varying soiling levels and operational needs
Solution Approach 1:
The cleaning system transitions from fixed preset sequences to dynamically adjustable parameters. Operators can modify cleaning time, temperature, mechanical action intensity, and chemical action levels in real-time based on actual soiling conditions and operational requirements, making the system adaptive without requiring complete redesign
Solution Approach 2:
The system allows operators to change key cleaning parameters (time, temperature, mechanical action, chemical action) to adapt to different soiling levels and operational needs. This enables versatility while maintaining a relatively simple interface by focusing on critical parameter adjustments
2Reliability
If cleaning sequences are extended to achieve better cleaning results, then cleaning effectiveness improves, but cleaning time increases
Solution Approach 1:
The system enables operators to adjust multiple parameters simultaneously (time, temperature, mechanical action, chemical action) to achieve optimal cleaning effectiveness for different soiling levels. For lightly soiled ovens, shorter cycles with appropriate parameters maintain effectiveness without unnecessary time consumption
Solution Approach 2:
The system allows operators to apply partial cleaning actions for lightly soiled areas and excessive/intensive actions for heavily soiled areas. This selective approach optimizes cleaning time by applying appropriate intensity only where needed
3Productivity
If resource consumption (detergents, water, energy) is increased to clean heavily soiled ovens quickly, then cleaning speed improves, but resource usage increases
Solution Approach 1:
The system allows operators to adjust resource-intensive parameters (chemical action level, water flow rate, energy input, mechanical action intensity) based on actual soiling conditions. This enables higher productivity when needed while avoiding unnecessary resource consumption for lightly soiled ovens
Solution Approach 2:
The system enables selective application of resource-intensive cleaning actions only where and when needed. Operators can apply intensive cleaning with high resource consumption for heavily soiled areas while using minimal resources for lightly soiled areas, optimizing the productivity-resource consumption balance
Data Source
AI summary
Disclosed is a cooking device having a flexible sequence control for automatic cleaning of an oven cavity. A customizing aspect allows for the inputting of values for a combination of parameters of a cleaning system. These parameters may include degree of soiling, cleaning time, energy consumption, water consumption, cleaner consumption, rinse agent consumption, and/or overall cost of cleaning. The sets of parameters can be entered, saved and recalled, or deleted. While setting values of the parameters, any undefined parameter(s) are automatically changed accordingly to achieve an optimal result. Unreasonable or impossible combinations of parameters are blocked. The parameters may be visualized as user friendly touch-activated bars. Selection can be made from several optimizing options, such as cost optimization, time optimization, resource optimization, and ecological optimization that reduce the consumption of resources.