Instrumentation and Control Engineering Certification Training Course

Why Select this Training Course?

Instrumentation and control engineering is the cornerstone that determines the performance and efficiency of modern industrial operations. Undertaking this comprehensive certification course positions you at the forefront of this dynamic field, empowering you to drive innovation and maximise productivity within your organisation.

Why are Instrumentation and Control Essential?

Grasping the current complexities of instrumentation and the subtleties of robust control systems allows engineers to fine-tune processes to unprecedented levels of precision. In this course, participants learn to formulate solutions that optimise performance and ensure safety, drawing on their knowledge of the latest technologies in the industry.

• Instrumentation Engineers
• Control Systems Engineers
• Process Engineers
• Electrical Engineers
• Maintenance and Reliability Engineers
• Project Managers in Automation and Process Control
• Technical Staff Involved in Instrumentation and Control Equipment

What are the Course Objectives?

Upon completion of the course, attendees can expect to:

• Understand complex instrumentation systems and their applications.
• Develop expertise in the design and implementation of control strategies.
• Learn to troubleshoot and maintain advanced control systems. -Embrace industry trends and new technologies for better systems integration.

How will this course be presented?

The course material will be served through:

• Hands-on laboratory sessions using real-world equipment and simulations.
• Detailed theoretical sessions to underpin practical understanding.
• Group projects and case studies for collaborative learning experiences.
• Seminars and webinars hosted by industry experts.
• Direct coaching and feedback from certified professionals.

What are the Topics Covered in this Course?

Module 1: Advanced Instrumentation Techniques

• Smart sensors and intelligent transmitters
• Calibration and maintenance strategies for high precision.
• Wireless instrumentation networks.
• Analytical instruments and their industrial applications.
• Flow, pressure, and temperature measurement technologies.
• Level measurement and control tactics.
• Signal conditioning and conversion.
• SIL rating for instrumentation and safety implications.

Module 2: Modern Control Systems Design

• Distributed Control System (DCS) architecture.
• Advanced Programmable Logic Controller (PLC) functionalities.
• Human Machine Interface (HMI) considerations in system design.
• Ensuring system robustness through redundancy and fail-safes.
• Applying modular design principles for systems scalability.
• Selection and application of control valves.

Module 3: Process Control and Optimization

• Control loop tuning methodologies.
• Artificial intelligence and machine learning in process control.
• Multivariable control strategies.
• Predictive control and model-based strategies.
• Batch process control using Sequential Function Charts (SFC).
• Optimal startups and shutdowns of process systems.
• Process simulation using digital twins.
• Alarm management system design.
• Applying Six Sigma methodologies for performance improvement.

Module 4: Industrial Communication and Networking

• Fieldbus, HART, and other industrial network protocols.
• Ethernet/IP and other TCP/IP based industrial networks.
• Network security and cybersecurity measures.
• Integration of wireless communication in industrial settings.
• Data highways and interlinking between control systems.
• SCADA system communication architectures.
• Industrial Internet of Things (IIoT) implementation.
• Remote operation and monitoring solutions.

Module 5: Safety Systems and Risk Management

• Understanding IEC 61511 and IEC 61508 for Functional Safety.
• Safety Instrumented System (SIS) design principles.
• Risk assessment and layer of protection analysis (LOPA).
• Safety system lifecycle management.
• Auditing and ensuring regulatory compliance.

Module 6: Reliability Engineering and Asset Management

• Predictive and preventive maintenance practices.
• Renewal and redundancy strategies for critical instrumentation.
• Asset management tools and software applications.
• Techniques for root cause failure analysis (RCFA).

Module 7: Project Engineering and Management

• Project lifecycle for instrumentation and control projects.
• Scope definition, budgeting, and resource planning.
• Quality assurance and control best practices.
• Procurement management and vendor communication.
• Managing multidisciplinary teams and contractors.
• Commissioning, handover, and documentation.
• Performance tracking and KPI definition.
• Leveraging project management software tools.

Module 8: Environmental Monitoring and Compliance

• Instrumentation for emission and pollution control.
• Water quality monitoring technologies.
• Adhering to environmental regulations and standards.
• Implementation of green technology in control engineering.
• Remote environmental monitoring systems.
• Noise and vibration measurement.
• Energy auditing and sustainability in process control.

Module 9: Advanced Data Analysis for Control Engineering

• Implementation of Big Data analytics in control systems.
• Real-time data processing and decision-making algorithms.
• Statistical process control and quality data analysis.
• Cloud computing in industrial data management.
• Edge computing for decentralised control and data acquisition.
• Integration of Enterprise Resource Planning (ERP) with control systems.
• Data visualisation tools for performance monitoring.
• Advanced process modelling and simulation techniques.
• Machine-to-Machine (M2M) data strategies.
• Fault detection, isolation, and recovery (FDIR) strategies.
• Systematic data logging and retrieval for audit trails.
• Implementing ISO 50001 for energy management and analysis.
• Utilising Augmented and Virtual Reality (AR/VR) for system diagnostics.

Module 10: The Future of Instrumentation and Control

• Nanotechnology in measurement and control.
• Quantum computing’s anticipated role in process optimisation.
• Biomimicry in control system design.

Module 11: Integration of Renewable Energy Systems

• Designing control systems for renewable energy applications.
• Grid integration and smart grid technologies.
• Energy storage and load balancing in control engineering.
• Monitoring and efficiency optimisation for solar and wind farms.
• Instrumentation in bioenergy and geothermal energy systems.
• Challenges and future trends in renewable energy.

Module 12: Robotics and Automation in Industry

• Collaborative robots (Cobots) integration in manufacturing processes.
• Industrial robotics and the role of control engineering.
• Automated Guided Vehicles (AGVs) in logistics and warehousing.
• Robot Operating Systems (ROS) for industrial applications.
• Vision systems for automated quality control.
• Safety standards and regulations for robotic systems.

Module 13: Compliance with International Standards and Best Practices

• Navigating ISO 9001 for quality management systems in control engineering.
• Compliance with the European Machinery Directive for safety.
• Understanding ANSI/ISA standards in automation.
• Implementation of Total Quality Management (TQM) in instrumentation.
• Compliance with environmental standards like the Clean Air Act.
• Cybersecurity standards such as IEC 62443 for industrial networks.

Module 14: Human Factors and Ergonomic Design in Control Systems

• The role of human factor engineering in control systems design.
• Ergonomic considerations for control room and panel design.
• Cognitive ergonomics for improved operator decision-making.
• Alarm management and interface design for error reduction.
• Stress and workload assessment in control operations.
• User experience (UX) design principles for HMI.

Module 15: Advanced Process Control (APC) Techniques

• Model Predictive Control (MPC) in real-world applications.
• Advanced PID control strategies (cascade, feedforward, ratio).
• Fuzzy logic and neural networks for non-linear control.
• Implementing adaptive and robust control techniques.
• Optimisation algorithms for real-time process control.
• Economic and advanced regulatory control methods.