Product Quality Intelligence

An American multinational manufacturing company founded in 1963 headquartered in Boston. The company works in several divisions, including aerospace and energy. Our Client has pioneered technologies that transformed industries and improved millions of lives. The firm has 6000+ employees.

Problem Statement

The company’s existing quality control processes relied heavily on manual inspections and sampling, which were time-consuming, subjective, and prone to errors. With increasing product complexity and production volumes, the traditional approach was no longer scalable or effective. The manufacturer recognized the need for a more data-driven, intelligent quality management system.

Our Solution

We implemented an AI-powered product quality intelligence platform with the following key components:
  • Computer Vision and Image Analysis: High-resolution cameras were installed at critical points in the production line to capture images of assembled products. Advanced computer vision algorithms were used to detect defects, measure key dimensions, and identify anomalies with a high degree of accuracy.
  • Sensor Data Analytics: Sensor data from various stages of the manufacturing process, such as temperature, pressure, and vibration, were analyzed in real-time using machine learning models. This enabled the early detection of process deviations that could lead to quality issues.
  • Predictive Maintenance: The AI platform leveraged historical data on equipment performance, maintenance logs, and sensor readings to predict when critical machinery was likely to fail. This allowed the company to proactively schedule maintenance and avoid unplanned downtime.
  • Closed-Loop Quality Control: The insights generated by the AI platform were fed back into the manufacturing process, enabling automated adjustments to process parameters, tool settings, and material inputs to maintain optimal quality.
  • Augmented Reality (AR) Quality Inspection: AR-enabled tablets were provided to quality inspectors, allowing them to overlay computer vision-based defect detection results onto physical products. This enhanced the inspectors’ ability to identify and classify defects accurately.

Business Benefits

  • Defect Reduction: The AI-powered quality control system reduced the incidence of defects by 28%, leading to significant cost savings and improved customer satisfaction.
  • Increased Productivity: By automating repetitive inspection tasks and providing real-time process insights, the platform enabled a 15% increase in production throughput.
  • Improved Yield: The closed-loop quality control and predictive maintenance capabilities resulted in a 12% improvement in manufacturing yield.
  • Enhanced Traceability: The system provided comprehensive data on product quality, process performance, and equipment health, enabling better traceability and root cause analysis.
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