Manufacturing Execution System Dynamic Data Collection Plans
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Solution Overview
Problem
Manufacturing execution systems (MES) lack flexibility and adaptability in data collection plans, which are often rigid and not context-specific, leading to inefficient data collection and maintenance processes in manufacturing environments.
Innovation Solution
A manufacturing execution system that employs context-specific data collection plans, specified by sets of objects for defining limits, sampling, rules, and frequency, allowing for dynamic adaptation and reusability, with a service interface for providing these plans and an analytical component for processing data to trigger maintenance actions when criteria are not met.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If rigid and generic data collection plans are used in manufacturing execution systems, then system simplicity and ease of implementation are improved, but flexibility and adaptability to different manufacturing contexts deteriorate
Solution Approach 1:
The patent implements dynamic data collection plans that automatically adjust sampling rates and parameters based on real-time manufacturing context, equipment state, and product specifications. The system transitions from static, rigid plans to dynamic, adaptive plans that respond to changing conditions, resolving the contradiction between implementation simplicity and operational flexibility.
Solution Approach 2:
The system changes data collection parameters (sampling rates, data types, collection frequency) based on manufacturing context, product criticality, and process stability. By allowing parameter adaptation without redesigning the entire data collection framework, the system maintains ease of implementation while gaining flexibility.
2Adaptability or versatility
If context-specific data collection plans with multiple parameters and objects are implemented, then flexibility and adaptability are improved, but system complexity and configuration difficulty increase
Solution Approach 1:
The patent segments the data collection plan into distinct, reusable parameter objects (sampling parameters, data type parameters, frequency parameters). Each parameter is an independent, configurable object that can be selectively applied to different manufacturing contexts, reducing overall system complexity through modular design.
Solution Approach 2:
The system creates universal parameter objects that can be reused across multiple data collection plans and manufacturing contexts. A single sampling parameter object can serve multiple products, processes, and equipment types, reducing complexity through reuse rather than duplication.
3Device complexity
If default data collection plans are used for all manufacturing steps, then system simplicity is maintained, but productivity and manufacturing efficiency deteriorate due to inefficient data collection
Solution Approach 1:
The patent applies local quality by tailoring data collection parameters to specific manufacturing steps, products, and equipment based on their unique requirements. Critical processes receive higher sampling rates and more detailed data collection, while stable processes use reduced sampling, optimizing productivity without uniformly increasing system complexity.
Solution Approach 2:
The system applies partial data collection by selecting only the necessary parameters and sampling rates for each specific manufacturing context. Instead of collecting all possible data uniformly, the system collects only what is needed for each process, improving productivity by reducing unnecessary data collection overhead.
Data Source
AI summary
A manufacturing execution system for manufacturing a product is provided. The manufacturing execution system includes a manufacturing execution plan having a set of manufacturing steps to be executed for manufacturing the product, a planning component for determining a data collection plan of data to be collected during the execution of one of the manufacturing steps, a service interface for providing the data collection plan in response to a service request, and a database for storing data that has been collected in accordance with the determined data collection plan.


