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Industrial Engineering and Operations Research

Industrial Engineering and Operations Research banner
Preview this course
Self-paced Advanced

Industrial Engineering and Operations Research

3(115)
1 enrolled
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FREE
1925 min
Anytime
English
238 views
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Why enroll

This course is highly valuable for students and professionals who aim to develop strong analytical, optimization, and decision-making skills. Enrolling in IE & OR helps learners understand how to analyze complex operational problems, allocate limited resources efficiently, minimize costs, improve quality, and enhance overall system performance. The course is particularly relevant for careers in operations management, planning, analytics, consulting, supply chain, and project management.

It is also extremely useful for competitive examinations, higher studies (MTech, MS, MBA, PhD), and research roles, as operations research forms a core component of many technical and management entrance exams. Professionals from civil, mechanical, electrical, production, and computer engineering backgrounds benefit from this course by gaining a managerial and optimization-oriented perspective that complements their technical expertise.

Is this course for you?

You should take this if

  • You work in Manufacturing & Industrial
  • You're a Industrial Engineering / Project & Programme Management professional
  • You have 3+ years of hands-on experience in this field
  • You prefer self-paced learning you can revisit

You should skip if

  • You're new to this field with no prior experience
  • You need a different specialisation outside Industrial Engineering
  • You need live interaction with an instructor

Course details

Industrial Engineering and Operations Research (IE & OR) is a specialized engineering discipline that focuses on the systematic analysis, design, optimization, and management of integrated systems involving people, materials, machines, money, information, and energy. The course emphasizes the use of mathematical models, statistical analysis, optimization techniques, and computational tools to support effective decision-making in complex engineering and managerial environments. It bridges the gap between engineering and management, enabling learners to improve productivity, efficiency, quality, reliability, and cost performance of organizations.

The course covers both Industrial Engineering concepts—such as work study, productivity improvement, quality control, reliability, maintenance, and supply chain management—and Operations Research techniques, including linear programming, network analysis, inventory models, queuing theory, simulation, and decision analysis. Strong emphasis is placed on real-world applications in manufacturing, construction, transportation, logistics, healthcare, energy systems, and service industries. By combining theory with practical problem-solving approaches, the course prepares learners to design optimized systems and make data-driven decisions in dynamic and uncertain environments.

SOURCE- Youtube [NPTEL IIT Guwahati]

Course suitable for

Key topics covered

  1. Introduction to industrial engineering and systems thinking

  2. Work study and methods engineering

  3. Productivity measurement and improvement techniques

  4. Operations research modeling and optimization

  5. Linear, nonlinear, and integer programming

  6. Transportation and assignment problems

  7. Network models and project scheduling (PERT/CPM)

  8. Inventory control and materials management

  9. Queuing theory and waiting line models

  10. Forecasting and demand planning

  11. Quality control and statistical process control

  12. Reliability engineering and maintenance management

  13. Simulation and decision analysis

  14. Supply chain and logistics optimization

  15. Application of IE & OR in manufacturing and service systems

Course content

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

60 lectures32 hr 5 min
  1. Lec 1: Industrial Engineering and Operations Research
    30 min
  2. Lec 2: Production Planning and Control , Aggregate production planning
    27 min
  3. Lec 3: Product Design Part 1
    31 min
  4. Lec 4: Product Design Part 2
    30 min
  5. Lec 5: Job,Batch and Flow Production methods
    36 min
  6. Lec 6: Work study:Enhancing productivity through Methods and Measurement
    32 min
  7. Lec 7: Work Sampling and Ergonomics
    30 min
  8. Lec 8: Inventory Management part-1
    38 min
  9. Lec 9: Inventory Management part-2
    35 min
  10. Lec 10: Supply chain Management
    27 min
  11. Lec 11: Total Quality Management
    35 min
  12. Lec 12: Application of Statistics in TQM
    33 min
  13. Lec 13: Acceptance Sampling
    33 min
  14. Lec 14: Control Charts
    25 min
  15. Lec 15: Taguchi"s Method,Six Sigma,ISO9001
    33 min
  16. Lec 16: Forecasting Part 1
    34 min
  17. Lec 17: Forecasting Part 2
    35 min
  18. Lec 18: Scheduling Part 1
    32 min
  19. Lec 19: Scheduling Part 2
    29 min
  20. Lec 20: Assignment Problems
    33 min
  21. Lec 21: Line Balancing
    31 min
  22. Lec 22: Break-Even Analysis Part 1
    20 min
  23. Lec 23: Break-Even Analysis Part 2
    42 min
  24. Lec 24: Industry 4.0
    35 min
  25. Lec 25: Big Data and Analytics
    29 min
  26. Lec 26: Industry 4.0 and 5.0
    29 min
  27. Lec 27: Machine learning
    34 min
  28. Lec 28: Internet of Things
    30 min
  29. Lec 29: Smart Factories
    33 min
  30. Lec 30: Digital Twins
    29 min
  31. Lec 31: Linear programming
    33 min
  32. Lec 32: Linear Programming: Graphical Method
    38 min
  33. Lec 33: Linear Programming: Simplex Method
    35 min
  34. Lec 34: Simplex Method: Big M and Two Phase
    33 min
  35. Lec 35: Special Problems in Linear Programming
    34 min
  36. Lec 36: Dual Problems
    36 min
  37. Lec 37: Properties of Dual Problem
    24 min
  38. Lec 38: Unit Worth of Resource
    35 min
  39. Lec 39: Dual Prices as Lagrange Multipliers
    38 min
  40. Lec 40: Linear Programming: Some Exercise Problems
    33 min
  41. Lec 41: Transportation Models: An Introduction
    34 min
  42. Lec 42: Transportation Models: Northwest-Corner Method
    31 min
  43. Lec 43: Transportation Models: Least-Cost Method
    36 min
  44. Lec 44: Transportation Models: Vogel Approximation Method (VAM)
    36 min
  45. Lec 45: Transportation Models: Optimality Test
    35 min
  46. Lec 46: Critical Path Method
    28 min
  47. Lec 47: CPM: Finding Critical Path
    39 min
  48. Lec 48: CPM: Float of an Activity
    25 min
  49. Lec 49: PERT
    28 min
  50. Lec 50: Project Crashing
    28 min
  51. Lec 51: Queuing Theory: part 1
    34 min
  52. Lec 52: Queuing Theory: part 2
    32 min
  53. Lec 53: Queuing Theory: part 3
    26 min
  54. Lec 54: Queuing Theory: part 4
    30 min
  55. Lec 55: Queuing Theory: part 5
    30 min
  56. Lec 56: Deterministic Inventory models
    37 min
  57. Lec 57: Probabilistic Inventory models: part 1
    31 min
  58. Lec 58: Probabilistic Inventory models: part 2
    36 min
  59. Lec 59: Probabilistic Inventory models: part 3
    32 min
  60. Lec 60: Probabilistic Inventory models: part 4
    28 min

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Questions and Answers

A: Governing principle: Little’s Law holds for effective WIP and effective throughput in steady state. Applied here: rework increases effective WIP to 340 × 1.25 = 425 items while net throughput stays 18/day, giving CT ≈ 23.6 days, but only if rework consumes capacity; the question frames extra touches without added close-out, so effective WIP seen by the system is 340 while flow time stretches by 1.25 → 18.9 days. Distractor D traps engineers who inflate WIP and forget the stated assumption about net close-out capacity.

A: Governing principle: alarms protect against awareness gaps, not against flow paths that bypass control elements. Applied here: LSHH alerts on level but cannot limit instantaneous flow through an unrestricted bypass, so downstream slugging remains credible. Distractor A catches people who equate level alarms with carryover prevention, ignoring response time and flow area.

A: Governing principle: corrosion mechanism follows the controlling species and operating envelope. Applied here: CO2 partial pressure and temperature favor sweet corrosion; H2S is below thresholds for SSC, and MIC or O2 pitting are secondary without evidence. Distractor C appeals to engineers with water-treatment backgrounds who over-weight shutdown conditions.

A: Governing principle: PSV sizing governs mass flux during the governing contingency, independent of set pressure. Applied here: a smaller actual valve than shown reduces relieving capacity even if set pressure and MAWP remain correct. Distractor D attracts engineers focused on mechanical loads rather than flow capacity.