Real world adoption of the Tangle technology is happening at an increasing speed as IOTA works its way into industrial and academic circles. The Industrial IOTA Lab Aachen (IILA) at the Laboratory for Machine Tools and Product Engineering (WZL) of the RWTH Aachen University happens to connect both of them. Therefore, it’s a great example worth exploring in more depth.
As an open laboratory, IILA invites students, lecturers, hobbyists, and industry experts to collaborate on IOTA’s real industrial use-cases. The focus is put onto machine-to-machine (m2m) interactions through the creation of proof-of-concepts (PoCs) for the emerging Industry 4.0. The vision is to enable “Smart Factories”, which are huge decentralized systems of independent machines that cooperate with each other in a “Manufacturing Economy”.
Such a decentralized system requires an underlying data and value transfer protocol that is decentralized itself. Therefore, IOTA – as a light-weight, fee-less, permission-less, distributed, and scalable protocol for the IoT – fits perfectly into the entire picture. It is capable of secured data acquisition and real-time leasing of machine services in the Internet of Production (IoP). Further layers on top of the Tangle come in handy for exactly these purposes:
- MAM – Masked Authenticated Messaging: a method that allows publishing of data on the Tangle in an encrypted fashion
- Flash Channels: nearly instant micro-payment flows for real-time payments like pay-per-second
- Data Marketplace: a decentralized marketplace that allows machines to buy and sell data How MAM, Flash Channels and the Data Marketplace make IoP Applications feasible. PoC: Digital Twins in Production
PoC: Digital Twins in Production
Products of industrial processes are usually not identical. Instead, they show slightly different properties due to production uncertainties and fluctuations in the material. With its first PoC, the IILA stores the individual properties (the digital twin) of each component on the Tangle. A web GUI can access the data for further inspection. Most importantly, this enables other machines involved in the supply chain to utilize this data, plan ahead for future production steps, and ultimately become more efficient.