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Industrial Engineering - Operations Research

Industrial Engineering - Operations Research banner
Preview this course
Self-paced Beginner

Industrial Engineering - Operations Research

4(4)
1373 views
₹ 449
146 min
Anytime
English
1373 views
J Aatish Rao
J Aatish RaoMechanical Engineering Professional
  • 7-day money-back guarantee
  • Lifetime access
  • Certificate of completion
Volume pricing for groups of 5+

Why enroll

Unlock the power of data-driven decision-making with our "Industrial Engineering - Operations Research" course! This dynamic program delves into the essential techniques of operations research, including optimization, simulation, and decision analysis. You'll learn how to apply mathematical models to solve complex industrial problems, improve efficiency, and enhance productivity. With expert-led instruction and real-world case studies, you'll develop the analytical skills needed to make impactful decisions in any organization. Join us and elevate your career in industrial engineering—enroll today to start your journey toward becoming an operations research expert!.

Is this course for you?

You should take this if

  • You work in Manufacturing
  • You're a Mechanical Engineering / Production Engineering professional
  • You prefer self-paced learning you can revisit

You should skip if

  • You need a different specialisation outside Mechanical Engineering
  • You need live interaction with an instructor

Course details

The Industrial Engineering - Operations Research course introduces students to systematic methods for making optimal decisions in complex industrial and business problems. It covers optimization problems, teaching how to mathematically formulate and solve Linear Programming Problems (LPP) using graphical and simplex methods. Students learn to handle transportation and assignment problems, applying techniques like the North-West Corner rule, Vogel’s Approximation Method, and the Hungarian method. The course also explores production scheduling, including rules like SPT and EDD, and problems involving multiple machines. It provides an understanding of queuing theory, including important formulas, Kendall notation, and numerical applications. Additionally, students study project management, learning to create and analyze network diagrams, and apply CPM and PERT techniques for effective planning and control. Throughout, the course emphasizes both analytical methods and practical numerical applications, preparing students to optimize processes and improve efficiency in real-world industrial systems.

Course suitable for

Key topics covered

  • Introduction

  • What are optimization problems

  • Mathematical formulation of LPP

  • Steps for solving an LPP

  • LPP Formulation

  • Binding constraints & Special cases

  • North-West Corner rule or DENTZY's methods

  • Numerical on assignment problem

  • SPT - Shortest Processing Time

Course content

The course is readily available, allowing learners to start and complete it at their own pace.

39 lectures2 hr 26 min
  1. Introduction
    3 min
  2. What are optimization problems
    3 min
  3. Mathematical formulation of LPP
    8 min
  4. Steps for solving an LPP
    3 min
  5. LPP Formulation
    5 min
  6. How to draw graphs?
    3 min
  7. Numerical based on graphical method
    9 min
  8. Shortcut Slope method
    3 min
  9. Binding constraints & Special cases
    5 min
  10. LPP Analytical (Simplex) method
    5 min
  11. Numerical based on simplex method
    9 min
  12. What are transporation problems?
    4 min
  13. Allocation
    4 min
  14. North-West Corner rule or DENTZY's methods
    4 min
  15. Vogel's Approximation method (VAM)
    4 min
  16. Numerical on transportation problems
    5 min
  17. Understanding assignment problems
    3 min
  18. Hungarian method or Flood technique
    4 min
  19. Numerical on assignment problem
    4 min
  20. Solving maximization transportation & assignment problems
    2 min
  21. The appropriate order
    4 min
  22. SPT - Shortest Processing Time
    4 min
  23. EDD - Earliest Due Date
    3 min
  24. n jobs in 2 machines
    4 min
  25. Numerical on n jobs in 2 machines
    3 min
  26. Mathematical study of queues
    5 min
  27. Why is queuing theory important
    2 min
  28. Kendall Notation
    4 min
  29. Important formulae
    4 min
  30. Numerical on queuing theory
    2 min
  31. Project, Activity & Event
    2 min
  32. Rules for network diagram
    2 min
  33. Types of network diagram
    1 min
  34. How to make a network diagram
    2 min
  35. Network analysis
    2 min
  36. CPM - Critical Path Method
    2 min
  37. Computational approach of CPM
    3 min
  38. PERT - Program Evaluation Review Technique
    3 min
  39. Numerical on PERT analysis
    4 min

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Questions and Answers

A: That’s the most common mistake — treating utilization like a linear knob. The difference matters because queuing delay explodes as you approach saturation, even if nothing else changes, and that extra waiting time swamps any gains from reduced idle time.

A: That’s the most common mistake — smoothing away setup logic to keep the math easy. The difference matters because sequence-dependent changeovers force yes/no decisions, and continuous LP can’t express those without breaking feasibility.

A: That’s the most common mistake — collapsing different loss mechanisms into one number. The difference matters because overspeed can hide chronic downtime, and the standard forces you to see where capacity is actually leaking.

A: That’s the most common mistake — assuming more WIP always means more output. The difference matters because once you’re past critical WIP, extra inventory just sits and waits, stretching lead time without helping flow.