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1. Machine Learning Model Deployment in Mechanical Materials
Robinson P, Mahesh Kumar
School of Mech. Engg., REVA University, Bengaluru, Karnataka, India
Dept. of Mech. Engg., PES College of Engineering Mandya, Karnataka, India
Corresponding Author, Email: robinson.p@reva.edu.in
Abstract
In the era of technology, it has become increasingly vital to adapt newer and novel approaches
in mechanical and materials engineering, for predicting different material behaviour, properties
and in condition monitoring of mechanisms at different hierarchal levels. Deployment of
Artificial Intelligence Techniques like machine learning (ML) and deep learning (DL)
algorithms are popular approach. The machine learning model performance relies on the data
collected or generated using the domain knowledge of material science. Then, we discuss the
importance of data collection, generation and pre-processing. The applications in mechanical
property prediction, materials design and computational methods using ML-based approaches
are summarized, followed by perspectives on opportunities and open challenges in this
emerging and exciting field. In this review, we first present a brief introduction of state-of-the-
art ML models, algorithms and structures, also will focus on the generalized models used and
its approaches in mechanism and material design and modelling
Keywords: Machine learning, Deep Learning, Pre-processing.
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2. Mechanical
Materials Design
Mechanical System
Modelling
Additive
Manufacturing
After successful completion of the course, the students will be able to
· Understand the elements of microprocessor based controller systems
· Understand the working sensors and transducers
· Understand the different types of actuation systems
· Understand the basics, architecture and programming of microprocessor and
microcontrollers
Unit-1
Introduction: Measurement and control systems their elements and functions,
Microprocessor based controllers, examples of mechatronic systems 6hrs

3. Transducers and Sensors: Static and dynamic characteristics of sensor,
Potentiometers-LVDT-Capacitance sensor-Strain gauges-Eddy current sensor-Hall
effect sensor-Temperature sensors-Light sensors. 7hrs
Unit-2
Actuation System: Electrical systems, Mechanical switches, solid-stat switches,
solenoids, DC & AC motors, Stepper motors. 6hrs
Elements of mechanical actuation system. Introduction to programmable logic
controllers. 5hrs
Unit-3
Introduction to microprocessors: Evolution of microprocessor, organization of
microprocessor, basic concepts of programming of microprocessors. Boolean
algebra, Logic gates & gate networks, Binary & Decimal number systems, memory
representation of positive and negative integers, maximum and minimum integers.
Conversion of real numbers, floating point notation, representation of floating
point numbers, accuracy and range in floating point representation, overflow and
underflow, addition of floating point numbers, character representation. 7 hrs
Logic functions: Data word representation, basic elements of control system,
8085A processor architecture, terminology-CPU, ALU, data registers, assembler,
fetch cycle, bus, interrupts. Micro controllers and its classification, difference
between microprocessors and microcontrollers. 6 hrs
Unit-4
Organization and programming of Microprocessors: Introduction of INTEL 8085-
Data and Address buses, Instruction set of 8085, programming the 8085, assembly
language programming. 6 hrs
Central Processing Unit of Microprocessors: Introduction, timing and control unit
basic concepts, Instruction and data flow, system timing, examples of INTEL 8085
and INTEL 4004 register organization 5 hrs
Text Books:
1. Mechatronics, W.Bolton fourth edition, Pearson Publications, 2008. 2.
Microprocessor Architecture, Programming and applications with 8085/8086A,
R.S Ganokar, Wiley Eastern.
Reference Books:

4. 1. Mechatronics System Design, Devdas shetty and Richard A. Kolk. 2.
Microprocessors and Microcontrollers, Krishna Kant, Prentice Hall of India, 2007.