भौतिकी: शास्त्रीय यांत्रिकी से क्वांटम यांत्रिकी

Physics

• Classical Mechanics: Deals with the motion of macroscopic objects under the influence of forces. It includes concepts like Newton's laws of motion, energy, momentum, and rotational motion.
• Thermodynamics: Focuses on the relationship between heat, work, and temperature, and the behavior of systems at a macroscopic level. Key concepts include internal energy, enthalpy, entropy, and the laws of thermodynamics.
• Electromagnetism: Explores the interaction between electric and magnetic fields. Includes concepts of electric charge, electric fields, magnetic fields, electromagnetic waves, and the laws of electromagnetism.
• Optics: Deals with the behavior of light, including reflection, refraction, diffraction, and interference.
• Modern Physics: This branch includes relativity (special and general) and quantum mechanics. Special relativity alters our understanding of space and time. General relativity expands on gravitation. Quantum mechanics deals with the behavior of matter at a microscopic level, including concepts like quantization and probability.

Automation

• Robotics: The design, construction, operation, and application of robots, which are programmable machines capable of performing tasks automatically.
• Control Systems: Techniques for controlling and regulating dynamic systems. This involves feedback mechanisms that adjust a process to maintain a desired output. A crucial component of automation.
• Instrumentation and Sensing: Technologies to measure and acquire data from physical processes. Sensors detect changes, and instruments make measurements, often crucial for automated systems to function.
• Computer Logic & Programming: Computer science is fundamental to automating processes. Programs control robotic actions, monitor systems, and perform complex calculations for optimization. Algorithms are central to automation.
• Process Automation: The use of automated machinery and systems to perform industrial processes, including manufacturing, assembly, and material handling. Often driven by production efficiency requirements.
• Machine Learning & AI: Can be applied in automation to allow robots and systems to adapt to changing conditions or to learn from data, enhancing decision-making in dynamic scenarios. These systems often develop from pattern recognition in data input.
• System Design & Integration: The process of combining and integrating various components, like mechanical, electrical, and programming aspects, to form a fully functional automated system. This involves careful planning and interfacing considerations for all the parts to work together.
• Mechatronics: An interdisciplinary field blending mechanical engineering, electronics, and computer science, aimed at developing smarter machines and robotic systems often used in automation applications.
• Simulation & Modelling: Creating virtual representations of systems to test them and understand their behavior before deployment in the real world. Important for refining automation designs before implementation for safety and efficiency.
• Human-Robot Interaction: Focuses on the design and development of robots and interactions between humans and robotic systems. Ensuring safety and user-friendliness is important.