Manufacturing Site Data Management for Root Industry Automation
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Solution Overview
Problem
Small-scale root industry companies face limitations in establishing process automation and efficiently managing manufacturing operations due to the lack of tailored systems that can effectively handle the unique characteristics of processes like casting, molding, welding, and heat treatment.
Innovation Solution
A manufacturing site integrated management system and method that utilizes a server to generate standard data through big data learning, analyze manufacturing site data, and produce management data, including energy usage and carbon emissions, to estimate production volumes and apparatus lifetimes, while also classifying data by field, apparatus, process, and product, and using simulation models to optimize production and lifetime predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If large company systems like MES are implemented in small-scale root industry companies, then automation capability is improved, but system complexity and cost increase beyond what small companies can sustain
Solution Approach 1:
The system segments manufacturing data into distinct categories (casting, molding, welding, plastic processing, surface treatment, heat treatment) with field-specific parameters and analysis methods. This segmentation allows the system to handle diverse manufacturing processes through modular, standardized interfaces rather than requiring a single complex monolithic system.
Solution Approach 2:
The server-based system provides universal functionality across multiple manufacturing fields by implementing a common data collection, analysis, and optimization framework that adapts to different process types through configurable parameters rather than requiring separate specialized systems for each manufacturing domain.
2Measurement precision
If comprehensive monitoring and analysis systems are deployed, then management precision is improved, but implementation cost and complexity increase for small companies
Solution Approach 1:
The system implements automated data collection from manufacturing equipment and self-directed analysis through AI algorithms that automatically process manufacturing data, generate insights, and provide optimization recommendations without requiring extensive manual intervention or specialized analytical expertise from company personnel.
Solution Approach 2:
The system replaces complex manual data collection, analysis, and decision-making processes with automated server-based data acquisition and AI-driven analytical algorithms, substituting human analytical effort with computational intelligence that provides precise measurements and insights more efficiently.
Data Source
AI summary
Provided are a manufacturing site integrated management system and method for root industry. The method is a manufacturing site integrated management method for root industry that is performed by a server, and includes generating standard data by repeatedly learning big data based on root industry, receiving manufacturing site data for a manufacturing site, analyzing the received manufacturing site data, and generating manufacturing analysis data, and generating manufacturing management data using the manufacturing analysis data on the basis of the standard data, wherein the generating of the manufacturing management data includes extracting energy usage and carbon emissions using the manufacturing analysis data to measure an actual production volume of a product and an actual lifetime of an apparatus and generate management measurement data, and analyzing the management measurement data to estimate an estimated production volume of the product and an estimated lifetime of the apparatus for remaining lifetime excluding the actual lifetime on the basis of a total lifetime of the apparatus and generate management estimation data using data that matches the standard data.