Page 8 - PPO Diaries

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PPO Diaries

❖ A brief overview of the project

Topic – Design of Critical Spare parts inventory model –
Machine breakdowns can occur sporadically at any time of a
machine’s life. Subsequently spare parts must be available to
repair it and make it up and running as soon as possible to
reduce downtime and improve productivity. Hence there was
a need of a model to forecast the expected demand of spare
parts of equipment, determine the reorder quantity, re-order
interval and safety stock requirement and subsequently
automate it so that it can be run over the years for inventory
planning.

Study of possible losses in blending and filling operations –
ABHIJNAN LAHIRI Identify the different points in the entire blending and filling

operations of lubricants where losses were occurring and
CASTROL
finding out possible solutions for them.
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GENERAL INFORMATION ❖ How is a normal day at the Internship?

Batch: PGDIE 48 My working hours per day was from 9am-5pm on a typical day
but depending upon the daily work and as my project
BTech: National Power progressed, I had to extend my time at office till 8-9pm. I was

mostly involved in interactions/conversations with the
Training Institute (E.R) employees and technicians to gather data and insights

regarding the issues needed for the project in the initial days.
Stream: Power Engineering
After gathering data, I spent my days in my “dedicated” office
Work Ex: Tata power company cabin beside my mentor to work on the model and come up
with results.

Having made quite a lot of acquaintances at the office in different departments, it was quite fun to work and

spend time at the office. Being a young student, all employees used to be fond of me and acknowledged my
company with them. Time used to fly by smoothly between project work and chitchat with the people there.

❖ What are the challenges faced during Internship?

The most frustrating challenge faced during the project was data collection. I believe this is the biggest challenge

faced by any intern in any company. As it looks simple in textbooks to come up with solutions to problems faced
efforts to gather reliable and useful data for any real-life
on the given data, it becomes extremely arduous
problem. There were incomplete data, missing data, irrelevant data, erroneous data and in many cases even no

history of data for certain portions of the project. In such situations, either you got to retrieve the data somehow

or take mindful assumptions to maintain validity of your project as well.

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