A leading CPG (Consumer Packaged Goods) company, struggling with the limitations of manual inspection processes, sought Quantzig's expertise to develop an automated inspection system. Their goals were to streamline inspections, ensure consistent quality, and gain valuable data insights.
Traditional manual inspections were a significant bottleneck in the production process, consuming valuable time and resources.
Manual inspections were prone to errors and inconsistencies, leading to quality issues and rework.
Certain inspection tasks involved working in hazardous conditions, posing risks to workers' safety.
As production volumes increased, manual inspection methods struggled to keep pace, leading to delays and bottlenecks.
Manual inspections provided limited data, making it difficult to identify trends, analyze root causes, and implement targeted improvements.
Quantzig's innovative solution leveraged a low code no code platform, empowering users with minimal technical expertise to implement and manage the automated quality inspection system. This user-friendly platform offered several core functionalities, and the implementation of this automated inspection system yielded significant benefits for the CPG company:
Quantzig's low-code, no-code platform empowers users with minimal technical expertise to implement and manage the automated inspection system. The core modules include:
Cameras and sensors: High-resolution cameras and sensors are used to capture images or videos of the products or components being inspected. Image preprocessing: Techniques like image enhancement, noise reduction, and normalization are applied to improve image quality and prepare them for analysis.
Convolutional Neural Networks (CNNs): Advanced deep learning models, such as Faster R-CNN or YOLO, are used to detect and localize objects within the images.
Deep Feature Extraction: Deep learning models extract meaningful features from the images, such as edges, textures, and shapes.
Machine Learning Algorithms: Classifiers like Support Vector Machines (SVM), Random Forest, or Gradient Boosting Machines are trained to classify detected objects as defective or non-defective based on their extracted features.
Microsoft Power Automate: Part of the Power Platform, it automates workflows and connects with different services, including sensor or machine outputs from the inspection process.
Microsoft Power BI: Developed dashboards and visualizations to present inspection results, track trends, and generate reports.
Quantzig's automated inspection system for quality inspection & reporting powered by a low-code, no-code platform, revolutionized the CPG inspection processes. The solution streamlined operations, ensured consistent quality, and provided valuable data insights for continuous improvement.
Is your business struggling with outdated inspection systems? Contact Quantzig today to learn how our low-code solutions can automate & empower your business for success.
Automated inspection systems offer advantages across various industries, including manufacturing, food and beverage, pharmaceuticals, and automotive.
While powerful, low-code, no-code platforms may have limitations in handling highly complex tasks requiring extensive customization.
Data quality and training are crucial. Using high-quality training data and employing robust validation techniques are essential for ensuring the accuracy of automated quality inspection systems.
Quantzig prioritizes data security. We implement robust security measures to protect sensitive data throughout the inspection process.
Yes, Quantzig’s solutions are designed to integrate seamlessly with various enterprise systems.
