Mechanical Production Line Productivity Monitoring Training Course with SVG Graphics

This training course helps students, technicians, and engineers in the field of electrical engineering and automation to enhance their knowledge and gain experience.

Duration: 1 Session – Learning Format: Online via Google Meet

We are giving away high-quality and multi-disciplinary ATSCADA training materials to our students.

Why should you take the SCADA course at ATSCADA?

Web Based SCADA Systems for modern industrial monitoring with cloud connectivity and realtime remote monitoring dashboard

ABOUT US

ATSCADA helps businesses grow further through comprehensive automation solutions.

ATSCADA Lab, a subsidiary of ATPro Corp, was formed and developed from the ATSCADA platform established in 2009, marking the beginning of our journey to build “Made in Vietnam” SCADA solutions. With a shared aspiration and long-term vision, we continuously research, develop, and refine core technology platforms, aiming to build a SCADA software “empire” with a distinct Vietnamese identity, capable of competing in regional and international markets.

Who should participate in the ATSCADA training course?

Final year engineering students

CEO – Company Leader

Automation Engineer

Electrical and Electronics Engineers

Many engineers struggle with SCADA systems because they rely solely on: Online tutorials that don’t require actual equipment – Disjointed documentation – Outdated training methods

What was the result? Slow progress, poor practical skills, and limited career advancement opportunities. ATSCADA has completely changed this.

Training Course Content: Monitoring Mechanical Production Line Productivity with SVG Graphics

Phase 1: PLC Programming & Server Connection This phase involves connecting the hardware and software, creating a real-world data flow for the production line.

PLC simulation code: Write program logic under PLC to simulate mechanical productivity data (cycle time, number of items passed/failed, machine running/fail status).
ATDriver Server Configuration: Set up the communication protocol (Modbus/Ethernet) to connect the ATDriver Server to the PLC.
Data collection: Initialize and test the Tags on the ATDriver Server to ensure that real-time data is being read correctly from the PLC registers.

Phase 2: Data Integration & Mapping Process (iSVG Workflow) The productivity data obtained in Phase 2 is then “overloaded” onto the static factory image.

Using the iSVG Editor tool: Embed the mechanical plant drawings into a web interface (Fastweb Designer).
Tag Binding Technique: Instructions on clicking on the object in the image (such as the OEE display board) and directly linking it to the PLC tag from the ATDriver Server.
Status Verification: Sets the display color for the CNC machine based on the PLC status variable (Green when Running, Red when Error).

Phase 3: Advanced Features & Animation Effects Brings the assembly line to life with optimal performance at 60 FPS.

Continuous movement (Conveyor belt): The mechanical conveyor belt configuration ensures smooth, continuous movement without causing browser lag.
Kinematic motion (Robot & CNC): Creates rotational effects for the robot arm and CNC chuck based on real-world operating signals from the PLC.
Warning Effect (Color Animation): Configure the Andon light to automatically flash red when the PLC signals a production stop or an error.

Phase 4: Building the Dashboard & Direct Interaction Transform the monitoring drawings into a two-way web-based operational dashboard.

Operational Effective Productivity Key Performance Indicators (OEE KPIs): Integrates data tables to track Overall Effective Performance (OEE) and Output directly from the PLC.
Direct control: Transform machine icons into buttons to send Start/Stop conveyor commands or Reset errors back to the PLC directly from your browser.

Monitoring Mechanical Production Line Productivity with SVG Graphics