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Artificial Intelligence in - Manufacturing

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Objectives

This training focuses on applying AI to improve plant efficiency, optimize supply chains, and automate quality inspections. It covers predictive maintenance, demand forecasting, and defect detection through machine learning and computer vision. By integrating AI into OT/IT infrastructure and Industry 4.0 systems, the course demonstrates how organizations can reduce downtime, improve operational accuracy, and achieve measurable ROI from intelligent automation.



Course Outcome

Implement AI solutions to predict equipment failures and minimize unplanned downtime.
Build demand forecasting models to optimize supply chain and inventory management.
Apply computer vision techniques for automated quality inspection and defect detection.
Integrate AI into manufacturing systems such as SCADA, MES, and ERP to support real-time decision making.
Evaluate AI investments by measuring ROI and business impact in manufacturing operations.
Navigate safety protocols, ethics, and compliance in AI-powered manufacturing environments.

Why Mazenet?


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    Expert Faculty

    Our Faculty comprises of 300+ SMEs with many years of experience. All our trainers possess a minimum of 8+ years of experience.

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    Proven Track Record

    We have served over 200+ global corporate clients, consistently maintaining a 99% success rate in meeting training objectives for 300+ technologies with quick turnaround time.

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    Blended Learning

    We provide course content over any platform that our clients prefer. You can choose an exclusive platform or a combination of ILT, VILT, and DLP.

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    Learning Paths

    The learning paths are very defined with clear benchmarks. Quantitative assessments at regular intervals measure the success of the learning program.

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    Case Study

    We have amassed over 10,000 case studies to support training delivery. Candidates will be trained to work on any real-time business vertical immediately after the training.

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    24*7 Global Availability

    We are equipped to conduct training on any day, date or time. We have delivered training pan India, Singapore, North America, Hong Kong, Egypt and Australia.

Delivery Highlights

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    Customized Training Modules

    Training programs are highly flexible with module customizations to suit the requirements of the business units.

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    Certification

    The training can be supplemented with appropriate certifications that are recognized across the industry.

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    Multi-language Support

    Course content can be delivered in English, Spanish, Japanese, Korean or any other language upon request.

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    Personalized Training Reports

    Candidates are assessed individually at regular intervals and are provided unique learning suggestions to suit their learning calibre.

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    Industry-Oriented Training

    Industry-oriented training, completing which, candidates can be immediately deployed for billable projects.

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    Diverse Training Platforms

    Choose from Instructor-Led Training, Virtual Instructor-Led Training, Digital Learning Platform and Blended Training platforms

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Course Preview

  • Explore Industry 4.0 and AI’s role in connected intelligent systems.
  • Learn common AI use cases in discrete and process manufacturing.
  • Understand the technology stack including Edge AI, Cloud AI, and Data Lakes.
  • Detect equipment failures using sensor data and ML algorithms.
  • Apply time-series forecasting and anomaly detection techniques.
  • Tools: Prophet, Scikit-learn, Azure IoT, AWS Lookout for Equipment.
  • Hands-on: train failure prediction models on sensor data.
  • Forecast demand using historical and external data.
  • Optimize inventory with reinforcement learning.
  • Model supplier risk and lead-time variability.
  • Tools: Facebook Prophet, NeuralProphet, SAP IBP AI modules.
  • Hands-on: build SKU-level demand forecasting models.
  • Use computer vision for defect detection in assembly lines.
  • Apply deep learning models like CNNs for image-based inspections.
  • Tools: OpenCV, YOLO, TensorFlow/Keras.
  • Hands-on: detect product defects from camera images.
  • Integrate AI with SCADA, MES, and ERP systems.
  • Deploy AI at the edge for real-time inference.
  • Use dashboards for monitoring AI operations.
  • Manage model lifecycle including retraining.
  • Follow AI safety protocols for factories.
  • Address ethical data use and transparency.
  • Build business cases and measure ROI.