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Big Data Analytics for Predictive Maintenance Strategies

Big Data Analytics for Predictive Maintenance leverages advanced data processing to predict equipment failures, optimize maintenance schedules, and reduce downtime, enhancing operational efficiency.

Duration

5 Days

Lectures

5

Projects

1

Course Overview

Big Data Analytics enables predictive maintenance by analyzing vast datasets to identify patterns, predict equipment failures, and optimize maintenance schedules, reducing downtime and costs.

Course Curriculum

1 live class

  • Overview of big data analytics principles
  • Importance of predictive maintenance in modern industries
  • Introduction to key concepts: Big Data, IoT, and AI
  • Understanding ISO 55000 for asset management
  • Fundamentals of API RP 580 and API RP 581 for risk-based inspection
  • Basics of ISO 14224 for reliability data collection
  • Introduction to predictive maintenance frameworks

1 live class

  • Techniques for effective data collection from sensors and IoT devices
  • Data integration methods for disparate sources
  • Understanding data quality, accuracy, and integrity
  • Use of cloud computing for data storage and processing
  • Big data technologies: Hadoop, Spark, and NoSQL databases
  • Real-time data streaming and processing
  • Data privacy and security considerations
  • Reviewing relevant standards and guidelines

1 live class

  • Introduction to machine learning algorithms for predictive maintenance
  • Supervised vs. unsupervised learning techniques
  • Feature engineering and selection for maintenance data
  • Model training, validation, and testing
  • Use of deep learning and neural networks
  • Predictive maintenance tools and software platforms
  • Data visualization techniques for predictive insights

1 live class

  • Developing and deploying predictive maintenance models
  • Condition-based maintenance (CBM) and real-time monitoring
  • Integrating predictive maintenance with existing systems
  • Risk assessment and management in predictive maintenance
  • Cost-benefit analysis of predictive maintenance implementation
  • Change management and training for maintenance teams
  • Evaluating the performance of predictive maintenance strategies
  • Best practices for continuous improvement

1 live class

  • Emerging trends in big data and predictive maintenance
  • Integration of AI and machine learning advancements
  • The role of digital twins in maintenance strategies
  • Overcoming challenges in big data analytics implementation
  • Future directions and innovations in predictive maintenance

Admission Is Going On

Enroll now to any of our Offline (On- Campus) or Online (Live Class) courses as per your suitable time.

Course Fee Offline

BDT 785,400.00

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Course Fee Online

BDT 0.00

Call This Number: 01958025050

BDT 785,400.00

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