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 recipe programs across multiple devices with varying functions, leading to suboptimal cooking times and quality due to sequential processing, which limits user control over automation and device flexibility.
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, allowing for simultaneous 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 available devices, enabling simultaneous execution and reducing total cooking time.
Solution Approach 2:
The system employs multiple cooking apparatuses of different device types (oven, microwave, steamer, etc.) that can handle different cooking functions. Each apparatus brings its specialized capabilities to the parallel execution, allowing the system to leverage diverse cooking methods simultaneously for different portions of the recipe.
2Productivity
If multiple cooking apparatuses are used in parallel, then cooking time is reduced and productivity is improved, but device complexity and coordination requirements increase
Solution Approach 1:
The control system continuously monitors the execution status of recipe instructions on each cooking apparatus and adjusts the distribution of remaining instructions dynamically. Based on feedback about which apparatuses have completed their tasks and which are still processing, the system optimizes the allocation of subsequent instruction groups to minimize total cooking time.
Solution Approach 2:
The parallelization depth and apparatus assignment are not fixed but dynamically adjusted during recipe execution. The control system can change the distribution of instruction groups based on real-time conditions, such as apparatus availability, cooking progress, and user-defined constraints, allowing flexible optimization of cooking efficiency.
3Loss of time
If the depth of parallelization is increased, then cooking time is reduced, but user control over automation and device flexibility is reduced
Solution Approach 1:
The system allows users to specify partial parallelization by defining constraints such as maximum number of apparatuses to use, minimum automation level required, or specific device types preferred. Rather than fully parallelizing all possible instructions, the system applies parallelization selectively based on user preferences, achieving time reduction while preserving user control.
Solution Approach 2:
The system accepts user-defined parameters that control the degree of parallelization, such as parallelization depth limits, automation level thresholds, and device flexibility constraints. By changing these parameters, users can adjust the balance between cooking time reduction and maintaining control flexibility, with the system adapting its parallelization strategy accordingly.
Data Source
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AI summary
System (100), method and computer program product for recipe instruction provisioning in relation to one or more registered cooking apparatuses (210, 220, 230) for preparing a food product. A recipe program file (281) with machine readable recipe instructions for preparing the food product is received. The recipe instructions are configured to be executed by one or more cooking apparatuses (210, 220, 230), and are annotated with one or more device types (DT1, DT2, DT3) suitable to execute the respectively annotated recipe instructions. A parallelization constraint (11) associated with a particular cooking user (1) influences the degree of parallelization of the food preparation with regard to the parallel use of the registered cooking apparatuses. A program analyzer module (120) determines one or more subsets (S1, S2) of the registered cooking apparatuses by identifying execution options (121) for the recipe instructions on said one or more subsets resulting in a recipe execution in compliance with the parallelization constraint (11). The execution option providing a best match with the received parallelization constraint (11) in accordance with predefined matching rules is selected recipe deployment instructions (P1, P2) are provided in relation to the respective one or more cooking apparatuses (210, 230) of the selected execution option in accordance with the corresponding annotations for preparing the food product.