Sewing Machine Work Analyzing Device for Automatic Time Classification
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Solution Overview
Problem
Conventional sewing machine work analyzing devices fail to automatically classify work times into 'regular' and 'irregular' categories, calculate idle ratios, and distinguish between necessary and non-necessary work times, leading to inefficiencies in production and productivity analysis.
Innovation Solution
A sewing machine work analyzing device that measures pitch times, calculates pitch time frequency distributions, classifies work times into regular and irregular categories, and outputs the classified times to identify idle ratios, thereby automating the classification process and eliminating the need for manual time measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual time measurement and classification methods are used, then work times can be recorded, but automatic classification into regular and irregular work times cannot be achieved
Solution Approach 1:
The system automatically classifies work times into regular and irregular categories without human intervention. The pitch time frequency distribution calculating unit and work time classifying unit enable the system to self-analyze and categorize time data, eliminating the need for manual classification while maintaining simplicity through automated algorithms.
Solution Approach 2:
The patent replaces manual mechanical time measurement and classification methods with automated electronic computing. The pitch time measuring unit, frequency distribution calculating unit, and work time classifying unit form an electronic system that substitutes human operators and manual recording processes, achieving automation without proportionally increasing physical device complexity.
2Measurement precision
If all work times are measured and analyzed in detail, then productivity analysis can be improved, but the time and resources required for measurement increase
Solution Approach 1:
The patent segments work times into distinct categories (regular work times and irregular work times) based on pitch time frequency distributions. This segmentation allows precise analysis of different work types while reducing the overall measurement burden by grouping similar activities together rather than analyzing each individual task separately.
Solution Approach 2:
The system uses pitch time frequency distributions as a representative model to classify and analyze work times. Instead of measuring every single work time event in detail, the system creates frequency distribution patterns that capture the essential characteristics of work time usage, providing precise analysis with reduced measurement requirements.
3Productivity
If idle ratio calculation is implemented, then productivity optimization can be achieved, but the complexity of data processing increases
Solution Approach 1:
The system automatically calculates idle ratios without requiring external intervention or complex manual computations. The work time classifying unit and idle ratio calculating unit work together to self-determine productivity metrics, simplifying the process by embedding the calculation logic directly into the automated classification system.
Solution Approach 2:
The idle ratio calculation provides feedback on productivity efficiency, enabling continuous optimization. The system processes classified work time data to generate idle ratio metrics that can be used to adjust and improve production processes, creating a feedback loop that enhances productivity while maintaining manageable data processing complexity through automated algorithms.
Data Source
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AI summary
According to one exemplary embodiment, a sewing machine work analyzing device includes: a pitch time measuring means for measuring a pitch time; a pitch time frequency distribution calculating means for calculating a pitch time frequency distribution based on the measured pitch time; a work time classifying means for classifying a work time into a regular work time and an irregular work time based on the calculated pitch time frequency distribution; and an output means for outputting the classified regular work time and irregular work time in an identifiable manner.