Workpiece Classification System for Balanced Production Goals
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Solution Overview
Problem
Current methods for classifying workpieces, such as food products, into multiple groups for producing different end products are not accurate and do not consider overall production goals, often resulting in imbalanced production quantities.
Innovation Solution
A method that calculates parameter values for each incoming product to determine its suitability for producing various end products, normalizes these values to meet specific production goals, and adjusts the portioning process to optimize the production of multiple types of end products while ensuring the production goals are met.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If workpieces are classified into multiple groups based on simple rules of thumb (e.g., weight-based classification), then the classification process is simple and quick, but the classification accuracy is low and production goals cannot be met
Solution Approach 1:
The patent transforms the classification approach from simple weight-based rules to a multi-parameter evaluation system that considers workpiece dimensions, shape characteristics, and multiple physical properties. This parameter expansion enables accurate classification into multiple end product groups while meeting complex production goals, resolving the contradiction between classification accuracy and system complexity.
Solution Approach 2:
The patent replaces simple mechanical weighing-based classification with an integrated scanning and computing system that uses optical scanners, dimension sensors, and computer algorithms to evaluate multiple workpiece parameters simultaneously. This substitution enables precise classification while maintaining operational efficiency, addressing the contradiction between accuracy and complexity.
2Productivity
If workpieces are classified based solely on weight, then the classification method is simple to implement, but the production quantities of different end products become imbalanced and production goals are not met
Solution Approach 1:
The patent performs preliminary scanning and parameter measurement of all incoming workpieces before classification decisions are made. By预先获取 workpiece dimensions, shape, and physical properties, the system can optimize classification assignments to meet production goals while maintaining operational simplicity through automated computer-controlled sorting mechanisms.
Solution Approach 2:
The patent implements a feedback mechanism where the computer system continuously monitors production quantities of different end products and adjusts classification assignments in real-time. This feedback loop ensures production goals are met by dynamically optimizing which workpieces are directed to which end product groups, resolving the contradiction between productivity and manufacturing simplicity.
3Measurement precision
If multiple parameters are considered for classifying workpieces into different end product groups, then the classification accuracy improves and production goals can be met, but the processing time and system complexity increase
Solution Approach 1:
The patent implements continuous scanning and parameter measurement as workpieces move along the conveyor system, eliminating the need for stopping or sequential measurement. Multiple sensors operate simultaneously to capture dimensions, shape, and physical properties in real-time, enabling accurate multi-parameter classification without increasing processing time.
Solution Approach 2:
The patent combines multiple measurement functions (dimension scanning, shape analysis, physical property detection) into an integrated classification system controlled by a single computer. This merging of functions enables simultaneous multi-parameter evaluation, achieving high classification precision while minimizing processing time through coordinated operation of all sensors and algorithms.
Data Source
AI summary
A method is provided for classifying incoming products (e.g., chicken butterflies) to be portioned into two or more types of end products (e.g., sandwich portions, strips, nuggets, etc.) to meet production goals. The method includes generally five steps. First, information on incoming products is received. Second, for each incoming product, a parameter value (e.g., the weight of an end product to be produced from the incoming product) is calculated for each of the two or more types of end products that may be produced from the incoming product. Third, the calculated parameter values for the incoming products for the two or more types of end products, respectively, are normalized so as to meet the production goals while at the same time achieving optimum parameter values. Fourth, for each incoming product, the end product with the best (e.g., largest) normalized parameter value is selected as the end product to be produced from the incoming product. Fifth, each incoming product is portioned to produce the end product selected in the fourth step.