Overview:

• This case study presents a summary of Digital Twin Genie and its implementation in the automobile manufacturing industry.

•  The software solution was successfully implemented and utilized for our client and the results were double the initial expectations that were established.

The Challenges of Meeting Our Client’s Needs – Digital Twin Case Study Introduction

The main challenges that Challenge Advisory was presented with was to meet the criteria of improving annual profit margins by 15-20%, reduce the average time it takes to manufacture a car model down to 12-13 hours and create a context where the client has all the visibility they need, that is directly related to how their customers are interacting with the manufactured products.

The Implementation of Digital Twin Technology – Talking About The Strategy Described In This Case Study

The approach that was taken by our Digital Twin experts in order to successfully implement Digital Twin Genie was divided into 5 steps. Those five steps included the delivery of the development kit that comes directly with the actual software, the installation of the solution in the internal computing systems of our client, bespoke sensor development, data collection & aggregation, and continuous guidance to deliver the expected results. The key challenges that were solved during this process included:

• Motion and key movement tracking of the machinery
• Accurate data collection and usage in order to provide valid workflow optimization
• Establishing key monitoring systems that would serve as a foundation for machine learning
• Installing additional sensors directly into the engines of all manufactured models

The Execution of Our Strategy:

The plan of action that was executed during the 14 day period:

1. The Digital Twin Genie development kit was successfully delivered and installed
2. The software was directly built into the machinery responsible for manufacturing car parts
3. Internal sensors were added into the engine of the cars in order to track “customer to product” interaction
4. After a 1 week period of data acquisition, development work has been done to the manufacturing machinery itself

Results and outcomes:

During the 2 week period that was dedicated to data collection and the implementation of Digital Twin Genie into the internal manufacturing processes, the results greatly exceeded our client’s expected outcomes. Here are the key achievements we managed to obtain via Digital Twin Genie:

• Their upgraded automobile manufacturing process increased their profit margins by an average of 41-54%
• The overall time it takes them to manufacture a car model was reduced down to 9-10h
• New digital twin based monitoring features were achieved, such as gas consumption, daily mileage, and engine performance monitoring

The overall timespan than was needed to implement Digital Twin Genie took 14 days, the first 7 days being the most intensive time period due to data accumulation.