MI – Manufacturing Intelligence (Big Data / AI)
Advantages of MI (Manufacturing Intelligence)
Talk to Mr. Rungroj, Managing Director of CSI Group, a company with over 30 years of experience working in industrial software, about the importance of Industry 4.0 and how businesses and industries can adapt themselves to be 4.0
What is Industry 4.0?
Mass production with Mass customization what's the difference
How will Industry 4.0 and AI contribute to industrial production?
How to adapt the factory to Industry 4.0?
CSI solutions to help adapt to Industry 4.0
Low Cost when compare to old Technology and Architecture
Top Management
Responsibility and Production System
Responsibility for Directors
Corporate strategic, Business unit strategic and team strategic and team strategic
Production System
BI (Business Intelligence)
Business Planning & Logistics
Responsibility for Management
Planning, Logistics, Sales, HR …
Production System
ERP (Enterprise Resource Planning)
Manufacturing Operations Management
Responsibility for Operators
Operational, Production Management and optimization
Production System
MES (Manufacturing Execution System)
MDC (Manufacturing Data Collection)
Industrial Automation
Responsibility for Technicians
Monitoring.
Process Control and Process Execution
Production System
SCADA (Supervisory Control And Data Acquisition)
MACHINE
Information about MI Platform
Data Lake – Raw Data Storage & Processing
Store all your data in a central repository of any size.
A data lake is a central repository that allows you to store structured and unstructured data at any size. You can store data as it is without structuring. Different types of analytics can also be used, from dashboards and visualizations to big data processing, real-time analytics, and machine learning to make better decisions.
What is a Data Lake AWS Website
▶ Handles structured and unstructured data
▶ Hadoop based
▶ Map reduce algorithms
Data Warehouse
What is a Data Warehouse?
A data warehouse is a central repository of information that can be analyzed to make better informed decisions. Data flows into a data warehouse from transactional systems, relational databases, and other sources, typically on a regular cadence. Business analysts, data scientists, and decision makers access the data through business intelligence (BI) tools, SQL clients, and other analytics applications.
Data Warehouse Concepts AWS Website
▶ Handles only structured data
▶ MPP based (massively parallel processing)
▶ Column based
▶ Cloud (Google/Redshift)
Visualization and Analytics
Analyzing & Visualizing your Data for Business Analytics
Business Analytics & Data Visualization are two faces of the same coin. You need the ability to chart, graph, and plot your data. Just as a picture is worth a thousand words, a visual is worth a thousand data points. A key aspect of our ability to understand what's going on is to look for patterns, and these patterns are often not evident when we simply look at data in tables. The right visualization will help you gain a deeper understanding in a much quicker timeframe.
Data Visualization AWS Website
▶ Handles structured data
▶ Supportd visualization and reporting in ”exploratory” mode
Get to know the situation in real time (monitoring)
By displaying the status and results of production in real time after the data has been simplified. It is not only useful to caregivers. But it also helps the on-site staff to be aware of the plan information and the production results as well.
Recognize the results of work
By recognizing and analyzing the results of the machine operation, it is possible to increase the production capacity of the machine or the production rate. and can calculate the production cost more accurately. The production base makes it possible to plan production and handle urgent goods efficiently and reduce wastage.
Anomalies can be discovered and corrected early with the Andon system (display alarm).
Intercepting alarm data from machines And if an error occurs, it will send the information to the next production process Including notifying to the front office staff and caregivers as well. This makes it possible to find and fix problems early.
Analyze and clean up big data.
The collected big data can then be used to analyze low-quality production lines or low-performing processes. This leads to quality improvement and overall work process development. In addition, the information gathered may also contain duplicate or inaccurate information and therefore need to be taken. “Cleaning data (Data Cleansing)” or organizing data. to make the information more accurate
Related information
The CSI Group is certified as an AWS Partner ( Amazon Web Service).
The CSI Group has been certified as an AWS (Amazon Web Service) Partner starting January 1, 2019.
Partner Level
Select Consulting Partner
Introducing CSI on AWS Official Website
CSI joined the exhibition “Digital Innovation Meets Business @ CEBIT ASEAN Thailand 2018” which was held for 3 days between 18 October – 20 October 2018.