Process Stream Segmentation for Material Efficiency Measurement
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Solution Overview
Problem
In the processing industry, there is a lack of effective solutions to measure and improve material efficiency, leading to significant resource losses due to inefficiencies in data collection and visualization, which are exacerbated by the challenges of 'big data' and the complexity of identifying bottlenecks in production processes.
Innovation Solution
A method that subdivides the main process stream into process side streams, defines measuring points, records and evaluates data using measuring systems, and assigns markings to collection containers to track and optimize workpieces, allowing for the precise measurement and quantification of parameters such as weight and processing speed, enabling data-driven process improvements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data collection systems are implemented to measure process parameters, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system divides the production process into multiple measuring points along the process stream, with each measuring point independently recording specific parameters. This segmentation allows precise measurement of process parameters at different stages without requiring a single complex centralized system, thereby improving measurement precision while managing device complexity through modular distribution.
2Loss of information
If comprehensive data collection is implemented across the production process, then information completeness is improved, but loss of time in data processing increases
Solution Approach 1:
Data from measuring points is automatically recorded and preliminary evaluated as the process stream moves through the production line. By performing data collection and initial evaluation in advance at distributed measuring points rather than centralizing it later, the system achieves comprehensive data completeness while reducing the time required for data processing and analysis.
3Manufacturing precision
If material efficiency monitoring is implemented, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The system combines multiple measurement functions at integrated measuring points along the process stream. By merging data collection, parameter measurement, and material efficiency monitoring into unified measuring points rather than using separate specialized devices, the system achieves improved manufacturing precision and material efficiency monitoring while reducing overall device complexity through functional integration.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables the detection and quantification of material losses, optimizing resource usage and improving material efficiency by providing actionable insights through data visualization and real-time feedback, thereby reducing waste and enhancing production line efficiency.
Implementation Method 1
the measured weight of the workpieces collected in the collection container is measured as parameters
Data Source
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AI summary
The invention relates to a method and a computer program for acquiring and quantifying parameters of a process, comprising a main process stream of workpieces (4, 20, 21), comprising the steps of: - dividing the main process stream (1) into process by-streams (2) of workpieces (4, 20, 21) to be investigated, - defining measuring points (3) for the process, wherein each measuring point (3) is assigned a process by-stream (2) to be investigated, - acquiring data for each measuring point (3) for the process by-stream (2) to be investigated assigned to it with at least one measuring system (6), wherein the data contain at least one measured parameter of the respective process by-stream (2) to be investigated, - evaluating (9, 10, 11) the acquired data for at least one measuring point (3).