Handover shifts tracker app

Log in page (wireframe)
Tasks page (wireframe)
In progress / pending tasks (wireframe)
Chat function (wireframe)

Inspiration

The inspiration behind the app comes from the inefficiencies and miscommunications in the shift handover process in microchip manufacturing. This project aims to bridge the communication gap between morning and night shift machine operators.

What it does

The app is a comprehensive mobile platform designed to facilitate seamless task handover between morning and night shift operators. It consists of the function to log in before and after their shift, access logs from the previous shift, and also communicate directly with the chat function that was built into the app.

How I built it

The app was developed using the product development life cycle:

Brainstorm - identify and understand the existing problem and gather insights from stakeholders (mentor)
Define - identify sources needed to develop the solution
Design - create a wireframe on Figma and built a simple app in Flutter by including functionalities such as viewing logs, a list of ongoing issues, and a log-in system.
Test - getting feedback from stakeholders (mentor) and improving the solution based on user needs and preferences
Launch - providing links to the Flutter app for the public to try out

Challenges I ran into

Developing the app using software development is quite challenging for me as I don't have enough programming skill level to build it. Besides that, finding an adequate amount of people to test the wireframe is another hurdle.

Accomplishments that I'm proud of

I'm proud to have successfully created a mockup app using the skills I learned from the Google Coursera courses - UX design and turning to Youtube for Flutter app development.

What I learned

Throughout this project, I learned more about the challenges faced by the manufacturing industry. I am also able to leverage my skills in user-centered design and collaborate with my mentor to build practical solutions.

What's next for the Handover shifts tracker app

This app has great potential for expansion such as upscaling into real software and incorporating IoT and machine learning algorithms to identify recurring patterns in defective machines.