FarmSted
Farmsted (name is representational) is an European farming equipment manufacturer with a fleet of machines, including feedseed machines. Feedseed machines collect data that Farmsted uses to improve their products. Farmsted wanted to convert their feedseed machines into digital twins and use the real-time data to improve their operations.
Farmsted want to create an application that will allow them to view data from their feedseed machines in real time. This will help them to take faster action on errors and defects, improve customer experience, and ensure that there are no delays in seeding. It will also give them insights into how their machines are being used, so that they can allocate and utilize them more effectively.
With a platform integrated with digital twins, Farmsted can even configure new machines by adding sensors and modules, and see how they might perform before they are manufactured. This will help them to ensure that their new machines are designed and built to meet their specific needs.
PS: I have kept these use-cases out of this case study as I am currently working on creating it as a white label solution for any IoT enabled digital twin fleet of machines.
Challenges
Digital twins of big machines are difficult to grasp, but the IoT team helped me understand the technology.
Grouping sensor data into a structure that users could easily navigate and find their required information was key to this project, and was a challenge.
My Role
As the only designer on the project, I worked with industry experts and the client to understand digital twin technology. I designed a dashboard with real-time data to give users an overview of the fleet's status. I worked with the client and IoT professionals to define the user journey.
Date & Duration:
/ Feb'2022 / 5weeks
Project Tags
/ Digital Twin
/ Operations Dashboard
/ Product Design
Solution
The Dashboard
/ The map view provided a high-level overview of all the feedseed machines in operation. The icons indicated if there were any alarms on the machines.
/ The most frequent errors that occur in that region were also included on this page. This allowed users to look for patterns and address the root cause of alarms in a region.
Asset List
/ The asset list showed the primary details of each machine in the area, including the number of alarms.
/ The machine with the highest number of alarms was at the top of the list, so that users could quickly identify and address problems
Vehicle Details
/ The information was segregated based on the user needs, with alarms, jobs, and operations data being most relevant to field technicians.
PS: As mentioned earlier the details of the Explore, Build use-cases have been omitted from this case study as I am developing those as a white label solution.
Outcomes
FarmSted Used Digital Twin to Improve Operations with Real-time data making sure the farming never gets delayed and its customers are happy.
Machine comparison and continuous improvement helped FarmSted to design better products and optimize operations.
Helped allocate machines more efficiently and optimize operations.
Helped identify problems early on and take action quickly. This reduced the time it took to fix machines after breakdowns.
Gave valuable insights into how to design better products for their customers.