Every industry and sector in the world need its mission-critical assets to be manufactured somewhere by some manufacturer. As a result, manufacturing companies remain under constant pressure to produce top-quality components at the highest possible efficiency. However, production defects are inevitable. So, for manufacturers all over the globe, the ability to identify production defects in real-time can be a game changer. And, that is what HCLTech’s AI-powered solution has been engineered for.
The Challenge
Reducing cost, increasing efficiency, enhancing quality and improving decision-making
The manufacturing industry grapples with challenges that directly impact quality, productivity, and profitability. Many manufacturers reject up to 20% of their output due to quality issues, leading to material wastage and higher production costs. Similarly, undetected defects result in quality complaints, product recalls, and, most importantly, reputation damage. Besides, manufacturers also struggle with inefficient decision-making as they rely considerably on subjective human assessments. Since most manufacturing machinery generates output at a very high speed, depending upon what is being manufactured, real-time quality checks by a human become impossible. So, manufacturers need to:
- Minimize material wastage
- Reduce downtime
- Optimize the production process
- Decrease rework cost
- Increase throughput
- Accurate root cause analysis
- Optimize energy consumption
- Ensure consistent quality
- Ensure proactive maintenance
- Improve factory-floor decision-making
- Enhance quality assurance
The Objective
Defect detection and classification, root cause analysis and real-time processing
HCLTech’s Insight solution is designed to bring the potential of GenAI to the manufacturing industry. It is an industry-focused repeatable solution, meaning it’s deployment-ready for all enterprises facing similar challenges across industries.
The solution aims at:
- Reducing product defects
- Preventing production defects
- Minimizing material waste
- Shortening the turnaround time
The Solution
Insight – GenAI-powered real-time manufacturing anomaly detector and beyond
Insight includes AI-powered cameras and IoT sensors to identify defects in real-time, enabling production managers and operators to take immediate corrective actions. It accurately categorizes defects to facilitate accurate root cause analysis and targeted corrective measures. Leveraging machine learning, the solution analyzes historical data and facilitates preventive maintenance, resulting in minimized downtime. Insight also provides real-time guidance and support to shop floor operators, empowering them to make informed decisions and resolve issues efficiently.
Other potential use cases of Insight include but are not limited to:
Surface defects detection, Printed circuit board (PCB) inspection, Dimensional defect detection, Electric powertrain components assessment, Electronics and infotainment systems inspection, Material composition analysis, Raw materials inspection, Predictive maintenance, Assembly line defect detection, Automated X-Ray inspection, HVAC and control panel defect detection, Print quality inspection, Pumps and fluid leakage detection & Upholstery inspection.
The Impact
~50% reduction in inspection costs and more
Leveraging the power of GenAI, Insight offers the following benefits and beyond
- Improved product quality- Enhanced defect detection and classification lead to higher-quality products and reduced customer complaints.
- Increased operational efficiency- Streamlined production processes, minimized downtime, and optimized resource utilization contribute to improved operational efficiency.
- Reduced costs- Lower inspection costs, reduced waste, and optimized resource allocation result in significant cost savings.
- Enhanced decision-making- Data-driven insights and real-time analytics empower decision-makers to make informed choices.
- Improved safety- Reduced human intervention in hazardous environments enhances worker safety.
- Enhanced sustainability- Optimized production processes and reduced waste contribute to environmental sustainability.
