Industrial Bottleneck Detection With Clean Data and Real-Time Analysis
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Solution Overview
Problem
Current industrial processes for bottleneck detection in manufacturing and supply chain environments are inefficient, relying on manual analysis and siloed data, which limits the ability to quickly identify and resolve bottlenecks, leading to increased costs and reduced productivity.
Innovation Solution
A computer-based Industrial Bottleneck Detection and Management System (IBDMS) that processes and analyzes time-stamped data to identify and prioritize bottlenecks in real-time, using data cleansing and multivariate analysis to provide continuous clean data for statistical calculations, and offers improved user feedback through heat maps and charts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual data collection and analysis methods are used, then data accuracy can be maintained through human verification, but the detection speed and productivity are significantly reduced
Solution Approach 1:
The patent replaces manual mechanical data collection and analysis processes with an automated computer-based system that continuously collects, cleanses, and analyzes process data. The system uses automated algorithms to detect bottlenecks without human intervention, achieving both high speed and maintained accuracy through systematic data processing procedures including outlier detection, data validation, and statistical analysis.
Solution Approach 2:
The system enables self-service bottleneck detection by automatically monitoring its own process data, identifying bottlenecks without external human analysis. The automated system continuously collects data from process systems, performs data cleansing, executes analysis algorithms, and generates bottleneck identification results independently, eliminating the need for manual professional analysis while maintaining detection accuracy.
2Device complexity
If data are siloed and manually collected from different sources, then data integration complexity is reduced, but the analysis time and resource requirements increase significantly
Solution Approach 1:
The patent merges multiple data sources and processes into a single integrated analysis system. The computer-based system collects data from multiple process systems simultaneously, consolidates them into a unified data structure, and performs comprehensive bottleneck analysis that considers interactions across all processes. This integration approach reduces overall analysis time by processing all data together rather than separately.
Solution Approach 2:
The system performs preliminary data collection and organization from multiple sources before analysis begins. Data is continuously collected and pre-processed in real-time, with validation and cleansing performed ahead of the actual bottleneck detection analysis. This preliminary preparation eliminates the need for time-consuming manual data gathering and integration during the analysis phase.
3Device complexity
If periodic sampling is used for visual analysis, then data processing requirements are reduced, but the continuity and real-time detection capability are compromised
Solution Approach 1:
The patent implements continuous data collection and analysis rather than periodic sampling. The computer-based system continuously monitors process data, performs ongoing data cleansing and validation, and maintains continuous bottleneck detection capability. This continuous operation provides real-time detection while the automated processing manages data volume through efficient algorithms and selective analysis of relevant parameters.
Data Source
AI summary
The present invention includes: (a) a method for improving data to be processed for bottleneck detection, by cleaning corrupt or outlier data; (b) a method for improved analysis of bottleneck data using a plurality of rules for categorization; and (c) a method for improved display and/or allowing improved user feedback for bottleneck data using multivariate analysis and display. These methods can be used alone, or preferably be combined in whole or in part together to improve performance of an industrial process. A system is also provided.