Work Order Tracking System for Managers and Employees

Preliminary Website
SMS System in Action

Mark, Gedeon, Shayar, Agna

Inspiration

Since we are all college students, we all agreed that creating an organized schedule for a complex system of actions/events would be a big strength for all of us. Additionally, the chevron challenge seemed perfect because it had a set goal that we needed to achieve giving us a clear finish line but it was also open ended in how we were to achieve that goal or letting us choose our path to reach the finish line.

What it does

Our project helps the workers of chevron work in an organized and disciplined manner making the entire work process easier and hence more efficient. Our website reads all the given work-orders in a particular day, and forms the most optimum schedule for the workers to complete al the work orders the next day keeping in mind all the restrictions that have to be maintained. This is done by our algorithm sorting out the work orders based on priority and then assigning each work-order to the most suited worker for that work-order through a bunch of factors like location and necessary equipment as optimizing factors.

How we built it

The work order, employee, facility, and equipment data was obtained in the form of an excel file. We imported this data to Python, where we develop a comprehensive back-end tracking and scheduling system to decide which employee would be assigned to each work order. Once we had finished developing this system, we developed a front-end messaging system using the Twilio API and Streamlit library.

Challenges we ran into

There were a large number of variables (>20) contained in our input data. These variables represented factors such as the worker order submission time, required equipment, the availability of the employees and the equipment, of the physical locations of the employees and equipment. Deciding which of these factors to prioritize and how much to value each of these factors was very challenging. The number of variables and the complexity of the data lead to a number of unforeseen edge cases that needed to be debugged.

Accomplishments that we're proud of

We are immensely proud of all our work together as a team but somethings we’re particularly proud of is that no one of us knew anything about front-end development at the beginning of this hackathon and in less than two days, we taught ourselves how to do that and successfully built a website at the end of this project. We are also immensely proud of the optimization algorithm we came up with along with all the testing and debugging that came with it.

What we learned

In technical aspects, we learned a lot about Web development, in terms of HTML, CSS and ReachJS., then we also learned a lot about API’s and their use cases, and lastly we all learned about working with high dimensional optimization problems with a lot of noisy data. In non-technical terms, since we were all very inexperienced in hackathons, we learned essential skills like working on projects together through collaboration and also how to work quickly since we were time bound while working on a big and potentially time consuming long problem.

What's next for HackRiceChevron

There are several goals we have for the project going forward. Going forward we plan to make our back-end system more dynamic and our front-end systems more interactive. Additionally, we plan to add more code that accounts for less significant decision factors, such as the probability of individual equipment failing.