object detection in computer vision

Objectives

Optimizing Weld Operations for reducing quality defects.

object detection in computer vision

Industry Served

Aerospace Component Manufacturing

object detection in computer vision

Solution

Ripik Vision

What Calls for a Change

Our client is a prominent aerospace component manufacturing company. It has been a key supplier of critical components for the Indian Space Research Organization (ISRO) and has contributed to India’s space exploration and civil aviation sectors. Aiming for economic production, the firm practices welding for critical joints to ensure they are defect-free. The manual inspection phase in welding processes is time-consuming and prolongs cycle time in the Weld Shop. Innovative solutions like automated inspection technologies or real-time monitoring systems can reduce cycle time and improve welding operations efficiency in the shop. 

aerospace component welding

Problem

The challenges faced by the Aerospace component manufacturing facility head were multifaceted, as the firm majorly depended on welding for crucial joints and prioritized the assurance of defect-free products. While many welding processes are automated for precision, the inspection phase remains manual, leading to time-consuming practices and increased cycle time in the Weld Shop. This hinders overall efficiency and workflow bottlenecks.

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The Solution

Ripik.AI focuses on reducing operational variability through optimal process control. We utilized our patented Vision AI–based solution Ripik Vision to achieve advanced weld quality. This system triggers alerts for anomalies through captured video feeds, while thermal cameras installed immediately after each welding section detects the thermal profile of the weld. Our technology, employing deep-learning techniques, classifies thermal images for feasible automated inspection. Deviations are then collated and displayed in the Weld Rework Shop, enabling operators to correct welds promptly. Additionally, the system recommends optimal set points for various welding parameters, ensuring high-quality welds.

The Impact 

The technology significantly enhanced the welding quality and assurance. By triggering timely alerts for weld anomalies through video feeds and recommending optimal set points for various issues, including undercut, lack of fusion, contamination, burn-through, absence of shielding gas, and high travel speed, the solution ensures a proactive approach to quality control. This resulted in 50% reduced defects, increased operational efficiency, and a seamless welding process, ultimately contributing to elevated overall productivity and cost-effectiveness in your operations. 

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“We are happy to share that work done by Ripik.AI across the use cases exceeded our expectations and we look forward to continue our collaboration with them.”

Chief Digital Officer

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