Computer Vision Cycle Time Measurement for Assembly Lines
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Solution Overview
Problem
Traditional manual methods for measuring cycle time in manufacturing assembly lines are inefficient for long-term and continuous monitoring, leading to inaccurate productivity statistics.
Innovation Solution
A computer-based method and apparatus that identifies start and end actions in image frames to determine cycle time by detecting hand movements, using imputation to fill gaps in missing data and averaging ground truths for accurate cycle time estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual measurement using stop-watch is used, then measurement simplicity is maintained, but measurement precision and continuity deteriorate
Solution Approach 1:
The patent replaces the manual mechanical stop-watch system with an automated computer vision system. The system uses cameras to capture images of workers performing tasks, processes these images through computer algorithms to automatically detect task completion, and records cycle times without human intervention. This substitution eliminates the limitations of manual sampling while maintaining operational simplicity through automation.
Solution Approach 2:
The system enables self-service measurement where the workers themselves are the subject of measurement without requiring manual observation. The automated system continuously monitors and measures cycle times as workers naturally perform their tasks, eliminating the need for separate manual measurement operations and ensuring continuous, unbiased data collection.
2Device complexity
If manual sampling measurement is used, then device complexity is reduced, but reliability of long-term monitoring deteriorates
Solution Approach 1:
The patent implements continuous monitoring by having the camera system operate throughout the entire work shift without interruption. The system continuously captures images, processes them in real-time, and maintains an ongoing record of cycle times. This continuous action eliminates the reliability issues associated with periodic sampling while the automated nature of the system keeps complexity manageable through standardized algorithms.
Solution Approach 2:
The patent introduces a computer processing system as an intermediary between the camera and the measurement output. This intermediary automatically analyzes images, identifies task completion events, and calculates cycle times, thereby bridging the gap between simple data collection and reliable measurement. The intermediary handles the complexity of continuous processing while maintaining measurement reliability.
3Measurement precision
If video analytics is used instead of manual measurement, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent segments the complex video analytics system into distinct functional modules: image capture, image processing, task detection, and cycle time calculation. Each module handles a specific aspect of the measurement process independently, making the overall complex system more manageable and easier to implement. This segmentation allows the system to achieve high measurement precision through specialized processing while keeping device complexity organized and controllable.
Data Source
AI summary
A method, an apparatus (70) and a program(s) for measuring productivity are provided. The method comprises: identifying a first movement based on at least one image frame, wherein the first movement matches a start action which define a cycle of movements (S1); identifying a second movement based on at least one image frame, wherein the second movement matches an end action which define the cycle (S2); and determining a period of time between the identified first movement and the identified second movement to measure productivity (S3).