Spring 2025

CH-240-B             Basics of Manufacturing Technology (B.Sc.) Introduction

1. 

Engineering Drawing

Isometric Drawing

Orthographic or Multiview Drawings

Dimensioning

Sectioning

Drawing Tools

Assembly Drawings

Where to Put Dimensions

Drawing Template 1, 2

Session EngDrwing, EXCE

Session Sectioning, EXCE

  2.

BOM, OPC, P&ID

Raw materials

Sub-assemblies

Intermediate assemblies

Sub-components, Parts

Value-adding activities

Piping and process equipment

Session BOM/OPC


3. 

Production Technologies

Casting, Welding

Machining, Grinding

Spark

3D Printing

Session Production technologies

 

  4.

Facility Planning & Layout

Job shop

Cellular manufacturing/Group Technology

Production Line

AS/RS

Session Facility Planning & Layout


  5.

Time & Motion Study

MTM

Basic Most

Humman-Machine Chart

Stop watch

Session Time & Motion Study



CA-IEM-802     Advanced Product Design (B.Sc.) Introduction

  1.

Axiomatic Design

Product and Manufacturing System Complexity management

**First Axiom

**Second Axiom

Session PLM

Session Axiomatic Design -intro

Session Axiomatic Design -First Axiom

Session Axiomatic Design -ZigZag

Session Axiomatic Design-2nd Axiom

  2.

Product Requirement Management

QFD

Session QFD

FMEA 

Session FMEA

  3.

Advanced CAD

CAD Geometric Models

**Geometry Interpretation

**B-rep, CSG, Voxel, ….

**Feature Recognition

Session Advanced CAD


  4.

DFx

Design for maintenance

Design for assembly and disassembly

Design for people: ergonomics, reparability, safety, and product liability

Session DFx Session


 

CA-IEM-801-A          Industry 4.0 Technologies (B.Sc.) Introduction

  1.

Digital Transformation

Introduction to industry 4.0

Session DTM

  2.

Digital Twins

Apply social media analytics techniques for consumer expectation insights. 

Use NLP methods to build a “consumer digital twin”

Session 

  3.

Internet of Things (IoT)

Implement machine learning models for operational parameter predictions. 

Integrate IoT devices for data collection and operational planning

Session 

  4.

Machine learning and Big Data 

Employ condition-based monitoring strategies and failure prediction models.

Use Python to implement predictive maintenance algorithms

Session 

5.

Real-time traceability and tracking

Understand the concept of digital product passports. 

Implement basic blockchain solutions for traceability and product life cycle management.

Session 

6.

Machine learning and digital marketing 

Explain extended producer responsibility (EPR) and circularity concepts. 

Integrate consumer engagement analytics (social media, influencer marketing) via ML.

Session