Instructor

Avinash Bhardwaj, Makarand Kulkarni

Section

S1

Semester

Spring ‘20

Course Difficulty

The course runs in two parts. For me, OR (Avinash Bhardwaj) was pre-midsem and IE (Makarand Kulkarni) was post-midsem.
OR: Can be quite challenging without prior aptitude or exposure towards rigorous math
IE: Reasonably easy to follow based on lecture videos, however certain concepts were quite vaguely explained

Time Commitment Required

OR: Heavy, at least 3 hours a week in addition to regular classes
IE: Not more than an hour a week

Grading Policy and Statistics

Very strict grading.
2 AAs, 3 ABs, 17 BBs out of 167 students.
A vast majority of the students received a BC or a CC.
15 students were awarded FF grade.

Attendance Policy

None

Pre-requisites

None officially, although some exposure to an optimization course or a rigorous linear algebra course (not MA106) could do you some good in the OR part.

Evaluation Scheme

OR: 20% Quizzes, 30% Midsem
IE: 20% Quizzes, 30% Endsem

Topics Covered in the Course

OR: Convex analysis, Mathematical programming formulations, Linear programming (Geometry, Forms), Farkas’ Lemma, Linear programming duality, Simplex algorithm and initial basic feasible solutions
IE: Quality Control Mechanisms, Production Control Mechanisms, Inventory Control Mechanisms, Failure Control Mechanisms

Teaching Style

OR: Lecture videos (from an older offering of another course that the professor takes) would be uploaded periodically and the lecture slot would be used for conducting quizzes and discussing doubts
IE: The professor started with taking live lectures, but as the attendance dropped to single digits, he started uploading recorded lectures instead of live classes

Tutorials/Assignments/Projects

None

Feedback on Exams

OR: Quizzes would contain far too many questions and would become near impossible to completely attempt. They would also be governed by a horrendous marking scheme, which eventually meant that the class average for some quizzes would be negative. The midsem was a 24-hour take-home exam. The professor was very strict about the use of internet and any answers even remotely appearing to resemble something found online would be awarded zero. Again, this resulted in an abysmal class average for the midsem.
IE: Quizzes were numerical answer type on SAFE, with marks being allotted only in case the final numerical answer was exactly correct. No marks were awarded for steps. Time was often insufficient, but not as much as the OR quizzes.
The endsem was a regular pen-paper exam with only theoretical questions, picked up from the slides.

Course Importance

The OR part would be the equivalent of the first half of most optimization courses in the institute, so that certainly means that it opens avenues for a lot of computational sciences. However, you would be better off doing a proper optimization course since the OR part of ME308 only scratches the surface.
The IE part would be relevant for those students pursuing a dual degree specializing in CIM. Consequently, a lot of courses in Manufacturing Automation, Lean Manufacturing and Production Management open up for you.

Going Forward

If you liked the OR part, do a proper optimization course, you can find these in CSE, EE, SC, IE as well as ME itself.
As for follow-ups to the IE part, see the section on Course Importance.

References Used

OR: Introduction to Linear Optimization (Bertsimas and Tsitsiklis)
IE: Dell Case Study uploaded by the professor, Fundamentals of Quality Control and Improvement (Amitava Mitra), Productions and Operations Management (Martinich)

ME 308 Review By: Aditya Iyengar