System and method for adjusting the depth of parallelization for recipe program execution
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Solution Overview
Problem
Cooking apparatuses face challenges in efficiently executing complex food processing steps across multiple devices in parallel, leading to suboptimal cooking times and quality due to limitations in adjusting the depth of parallelization according to user preferences.
Innovation Solution
A computer-implemented method and system that dynamically adjusts the depth of parallelization for recipe program execution by identifying suitable subsets of cooking apparatuses based on user-defined constraints, such as time, automation level, and device flexibility, to optimize the execution of recipe instructions across multiple devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If recipe instructions are executed sequentially on a single cooking apparatus, then device complexity is reduced and ease of operation is improved, but cooking time increases and productivity decreases
Solution Approach 1:
The recipe program is divided into multiple independent instruction groups that can be executed in parallel on different cooking apparatuses. The control system segments the overall cooking task into sub-tasks that can be distributed across multiple devices, enabling simultaneous execution and reducing total cooking time.
Solution Approach 2:
Multiple cooking apparatuses are merged into a coordinated system under centralized control. The control system combines the capabilities of multiple devices to execute a unified recipe program, allowing parallel processing of different cooking instructions while maintaining overall recipe coherence.
2Productivity
If multiple cooking apparatuses are used in parallel, then cooking time is reduced and productivity is improved, but the depth of parallelization becomes difficult to control and system complexity increases
Solution Approach 1:
The system dynamically adjusts the depth of parallelization based on user preferences and constraints. The control system can adaptively determine how many cooking apparatuses to activate and how to distribute instructions, allowing flexible control over parallelization depth to optimize between cooking time and system complexity.
Solution Approach 2:
The system changes operational parameters such as the number of parallel apparatuses, instruction distribution strategy, and coordination level based on user-defined constraints. By adjusting these parameters, the system can optimize performance for different scenarios ranging from simple sequential execution to complex parallel operations.
3Loss of time
If the depth of parallelization is increased to reduce cooking time, then productivity improves, but coordination complexity increases and reliability may decrease
Solution Approach 1:
The control system implements feedback mechanisms to monitor the execution status of parallel instructions and coordinate activities across multiple apparatuses. This feedback enables real-time adjustments to maintain cooking result consistency and reliability, even when multiple devices operate in parallel with different timing and parameters.
Solution Approach 2:
The control system acts as an intermediary between multiple cooking apparatuses, coordinating their operations and ensuring proper synchronization. This intermediary function manages the complexity of parallel coordination while maintaining reliability by enforcing proper execution sequences and monitoring overall recipe progress.
4Manufacturing precision
If specialized cooking apparatuses are used to improve food quality, then manufacturing precision is improved, but device complexity increases and ease of operation decreases
Solution Approach 1:
The control system provides universal management capabilities that work across different types of cooking apparatuses. By implementing a unified control interface and standardized instruction set, the system makes operation simple for users while still leveraging the specialized capabilities of different device types for high-quality cooking results.
Data Source
AI summary
Recipe instructions may be executed by one or more cooking apparatuses, and annotated with one or more device types suitable to execute the respectively annotated recipe instructions. A parallelization constraint associated with a particular cooking user may influences a degree of parallelization of the food preparation with regard to the parallel use of the registered cooking apparatuses. A program analyzer module determines one or more subsets of the registered cooking apparatuses by identifying execution options for the recipe instructions on said one or more subsets resulting in a recipe execution in compliance with the parallelization constraint. The execution option providing a best match with the received parallelization constraint in accordance with predefined matching rules is selected recipe deployment instructions are provided in relation to the respective one or more cooking apparatuses of the selected execution option in accordance with the corresponding annotations for preparing the food product.