TEKNOPAR Industrial Automation Case Studies Real-Time Welding Optimization with Welding Robot

	Real-Time Welding Optimization with Welding Robot TEKNOPAR Industrial Automation

Real-Time Welding Optimization with Welding Robot

TEKNOPAR Industrial Automation

Technology Category	Analytics & Modeling - Digital Twin / Simulation Analytics & Modeling - Predictive Analytics
Applicable Industries	Equipment & Machinery Metals
Applicable Functions	Discrete Manufacturing
Use Cases	Condition Monitoring Digital Twin Predictive Maintenance Predictive Quality Analytics
Services	Data Science Services Software Design & Engineering Services System Integration
Challenge	Automating welding processes with robots enhances productivity and environmental friendliness. However, the quality of robotic welding can deteriorate due to various factory conditions. Continuous monitoring and adjustments are necessary to maintain high standards. Read More
About Customer	Manufacturing of pressed sheet metal parts in the automotive industry. Read More
Solution	TEKNOPAR integrated data from multiple sensors, including microphone and vibration sensors, environmental sensors, fiberoptic laser sensors, and Magmaweld devices, to create a comprehensive real-time monitoring system. Advanced regression models analyzed these data streams to detect potential quality issues, allowing immediate adjustments to the robot's parameters. Read More Log in to view content
Data Collected	Acceleration, Humidity, Microphone, Pressure, Temperature Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Digital Twin / Simulation

Analytics & Modeling - Predictive Analytics

Applicable Industries

Equipment & Machinery

Metals

Applicable Functions

Discrete Manufacturing

Use Cases

Condition Monitoring

Digital Twin

Predictive Maintenance

Predictive Quality Analytics

Services

Data Science Services

Software Design & Engineering Services

System Integration

Challenge

Automating welding processes with robots enhances productivity and environmental friendliness. However, the quality of robotic welding can deteriorate due to various factory conditions. Continuous monitoring and adjustments are necessary to maintain high standards.

About Customer

Manufacturing of pressed sheet metal parts in the automotive industry.

Solution

TEKNOPAR integrated data from multiple sensors, including microphone and vibration sensors, environmental sensors, fiberoptic laser sensors, and Magmaweld devices, to create a comprehensive real-time monitoring system. Advanced regression models analyzed these data streams to detect potential quality issues, allowing immediate adjustments to the robot's parameters.

Data Collected

Acceleration, Humidity, Microphone, Pressure, Temperature

Impact #1	[Cost Reduction - Waste] 50% less scrap and near-zero defects in automotive parts manufacturing.
Impact #2	[Efficiency Improvement - Production Uptime] Increased process efficiency by reducing downtime by 15%.
Impact #3	[Process Optimization - Real Time Monitoring] Real-time data collection from welding machines and robots was achieved.

Impact #1

[Cost Reduction - Waste]

50% less scrap and near-zero defects in automotive parts manufacturing.

Impact #2

[Efficiency Improvement - Production Uptime]

Increased process efficiency by reducing downtime by 15%.

Impact #3

[Process Optimization - Real Time Monitoring]

Real-time data collection from welding machines and robots was achieved.

Benefit #1	In automotive parts manufacturing processes, quality control has been improved by applying advanced AI-based models for optimization and restructuring, producing 50% less scrap, waste and near-zero defect parts.
Benefit #2	Increased process efficiency by reducing downtime by 15%.

Benefit #1

In automotive parts manufacturing processes, quality control has been improved by applying advanced AI-based models for optimization and restructuring, producing 50% less scrap, waste and near-zero defect parts.

Benefit #2

Increased process efficiency by reducing downtime by 15%.

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Overview

Real-Time Welding Optimization with Welding Robot

Operational Impact

Quantitative Benefit