Workflow Dataset Automation for Lean Manufacturing Variance Detection
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Solution Overview
Problem
Conventional methodologies for capturing, analyzing, and sharing manufacturing and supply operations data rely heavily on manual-intensive tasks, leading to inefficiencies, human error, and compatibility issues between disparate systems, hindering continuous improvement processes.
Innovation Solution
A system and technique for generating, analyzing, and sharing manufacturing and supply operations data by integrating lean manufacturing principles into computing components, utilizing graphical user interfaces to identify operational improvements, and providing real-time status and predictive assessments through data analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual-intensive tasks are used for capturing, analyzing, and sharing manufacturing data, then system complexity is reduced, but productivity and measurement precision deteriorate
Solution Approach 1:
The patent replaces manual-intensive mechanical tasks with automated computing components and algorithms. Data capture, analysis, and sharing functions are automated through software systems that process manufacturing data without human intervention, thereby increasing productivity while managing system complexity through digital transformation.
Solution Approach 2:
The system enables self-service data processing where computing components automatically capture, analyze, and share manufacturing data without requiring manual operation. The automated system serves itself by continuously processing data flows and generating insights, improving productivity while reducing the need for complex manual coordination.
2Measurement precision
If manual tasks are used for data capture and analysis, then device complexity is minimized, but measurement precision and reliability worsen due to human error
Solution Approach 1:
Manual data analysis tasks are replaced with automated computing components that perform data processing without human error. The system uses algorithms and computational methods to analyze manufacturing data with consistent precision, eliminating the variability and errors associated with manual analysis while managing complexity through standardized digital processes.
3Adaptability or versatility
If disparate systems are integrated manually, then adaptability is reduced, but device complexity increases due to compatibility issues
Solution Approach 1:
The patent implements a universal data processing framework that can handle multiple data sources and formats through standardized computing components. The system is designed to be multi-functional, accommodating various manufacturing data types and sources without requiring complex custom integration for each system, thereby improving adaptability while managing integration complexity through universal interfaces.
Data Source
AI summary
Lean manufacturing principles are integrated into computing components for the generation, collection, analysis, and propagation of real-time manufacturing and supply operations data. A set of role card objects determined to correspond to a received electronic plan can be selected for generating a workflow dataset representative of a standard workflow. The workflow dataset, including the selected set of role card objects, can be displayed via a graphical user interface. The GUI can facilitate scheduling, assignment, and execution of various tasks defined within the role card objects. Timed durations of executing such tasks can be compared to standard durations defined in each role card object of the workflow dataset, such that deviations from the standard durations can be determined. As variances can be problematic to operational efficiencies, techniques for dynamically generating, assigning, and analyzing datasets associated with identified problematic areas, such as variances, are provided.