An IoT Approach to Solving Inventory Tracking Problems For Rolls-Royce Aviation 

We helped save about  $40k monthly in facility operation costs using a  user-centered approach to identify critical problems and solve them by proposing an end-to-end IoT solution powered by a mobile-web app platform.

MY ROLE

I took charge of defining the product concept, articulating information architecture & designing high-fidelity prototypes. I also collaborated closely with the researcher to analyze the findings.

DURATION

8 weeks - Sept 2021 to Oct 2021

TEAM

Aditya, Akash, Gauri & Kevin

ABOUT THE CLIENT

Rolls-Royce Corporation is located in Indianapolis, IN, United States and is part of the Aerospace Product and Parts Manufacturing Industry.

INTRODUCTION

Context

The proposed solution will help track helicopter engine parts within the facility. There is no established way of tracking them currently.

Logistically, they arrive in the facility in bins of different sizes and are placed on shelves by facility workers. 

Problem

Currently, the task of tracking these parts depends entirely on manual effort and in-person coordination which is  time-consuming and a cause of  significant stress for all stakeholders involved.

Objective

Creating value through IoT automation. To find the best way to automate the existing tracking process easing the burden on the stakeholders. To use the sponsored Particle.io Argon IoT sensor kit and weight sensors.

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KEY FEATURES

The InvenTrack Mobile App and Web App bundle help you manage your stock inventory in real-time while allowing you to customize shelves according to your requirements. It also provides actionable insights derived from your usage patterns over time.

Mobile App Features

Real-time View of Shelf Capacity

View the real-time capacities of shelves at the departments and at the docks, and know the current inventory levels of each shelf.

Real-Time Bin Tracking

Get real-time information on the quantity of each bin on the shelf. The weight of each bin is measured and calculated using the physical prototype powered by the IoT Argon kit. For each bin, the user can decide to update its status to Active, Inactive or Calibrate.

Customizable Updates

Receive updates in the form of notifications regarding the position of shelves and bins from one point to another within the facility.

Managing Purchase Orders

Manage and track purchase orders from the app when you start noticing inventory levels go down.

Web App Features

Universal Bin Tracking

View real-time statistics of the facility and a graphical view of the status of all bins in the facility.

Predictive Analytics

Optimize the facility with prediction based on existing data by knowing anomalies in processes like order turnover times, shelf empty times and bin commute times within the facility.

Customize Shelves

Get the flexibility to customize shelves according to your needs and requirements.

Manage the Facility

Effectively manage users, shelves and purchase orders from one single dashboard.

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RESEARCH

Design Process

Data Gathering

Desk Research - We conducted initial desk research to understand the facility's working. Specifically,  remote observations by studying documentaries and videos online helped us have a model in our minds before preparing an  interview script for the facility visit. We also conducted an informal competitive analysis of existing software solutions for inventory tracking.

​Facility Visit & Interview - We conducted a  facility tour and an interview with key management staff.

We sketched out a lifecycle diagram to understand workers' schedules a the journey of a bin. In the process, we uncovered several insights about users and their interdependecies.  

Understanding Workflow & Users

Based on the interview, we identified four key users that play critical roles in managing the facility & their relationship with each other. We learned more about them by creating personas and empathy maps. 

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BRAINSTORMING

Value Proposition Canvas

We used the Value Proposition Canvas to guide our brainstorming process which has been represented below.

Solution Workflow

This workflow explains the journey of bins. The weight sensors are used to track the weight of specific slots on shelves, generating data that can be tracked using the mobile app and web dashboard.

Information Architecture

Key User Flows

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PROTOTPYING

IoT Prototype Concepts

Low Fidelity Wireframes

Design Inspiration

The visual design of this app was inspired by the recent re-branding of Rolls-Royce Aviation by the design agency Pentagram. 

Version 1 Prototypes

These were two of our initial high-fidelity prototypes. We conducted a basic heuristic analysis on these and got feedback from our stakeholders. Some drawbacks of these prototypes were that they:

• Did not reflect the new Rolls-Royce branding
• Had confusing navigation
  
• Displayed poor user experience - for example, it was tough for users to reach the top dropdown with their thumb. They would have to use two hands in this scenario.
  

Based on this feedback, we improved the next version of the prototypes.

Final Prototypes

The proof-of-concept IoT prototype built using Argon IoT kit

Reflections

This project was covered in a short span of over 6 weeks. If we had more time, we would:

• Dive deeper into each aspect of the prototype 
• Conduct more testing with stakeholders
• Design better data visualizations after gathering inputs from users
• Optimize prototypes to adhere to WCAG accessibility guideline

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LETS CONNECT!

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