“YOU NEVER CHANGE THINGS BY FIGHTING THE EXISTING REALITY. TO CHANGE SOMETHING, BUILD A NEW MODEL THAT MAKES THE EXISTING MODEL OBSOLETE.”
R. BUCKMINSTER FULLER
JANUARY 3RD 2009, THE BITCOIN PROTOCOL WAS UNLEASHED TO THE WORLD.
A FOUNDATIONAL TECHNOLOGY REDEFINING ORGANIZATIONS TRADITIONAL BOUNDARIES AND CHALLENGING THEIR BUSINESS MODELS.
THE PILLARS FOR A NEW ECONOMIC SYSTEM
An Introduction to Blockchain Technology
Blockchain technology’s core component is a technological protocol that enables data to be exchanged among multiple parties within a network. It does so without the need for intermediaries, as network participants interact with encrypted identities (anonymously) and directly with each other using peer-to-peer communication. Each transaction is then added to an immutable transaction chain and distributed to all network nodes.
Blockchain technology; a decentralized, distributed ledger that provides a way for information to be recorded, shared and maintained by a community.
Blockchain Core Components
- Blocks can be written and read by certain participants and entries are permanent, transparent, and searchable
- Transactions are recorded in chronological order on a continuously growing database
- A system of computers, connected via the internet, in which users at any computer can receive or send value to another computer
- Data is replicated and stored across the system over a peer-to-peer network
- It facilitates peer-to-peer transfer of value without a central intermediary, e.g. a bank
- Digital signatures and cryptography are used to secure the transfer
“Unlike the internet alone, blockchains are distributed, not centralized; open, not hidden; inclusive, not exclusive; immutable, not alterable; and secure. Blockchain gives us unprecedented capabilities to create and trade value in society.”
World Economic Forum (2017)
Digital Twins – Definition & Application Areas along Industries and Functions
Currently, a great deal of movement from different industries towards digital twins can be observed. While there appears to be a general consensus as to the importance and potential of digital twins, there currently is no universal standard or generally adopted definition of what exactly a digital twin is.
One definition of digital twins:
Digital twins are virtual replicas of physical objects or systems; a pre-existing necessity in the Internet of Things.
Mapping real assets to their digital twins typically requires a combination of the following four key characteristics:
1. IT components that transmit a status or data package
2. Connectivity in form of bandwidth
3. Defined data structures that handle basic analytics
4. User interfaces to visualize relevant data
Similar to the internet and its users, the IoT ecosystem’s beneficial character increases with a growing digital twin population.
While so far mostly High Value Assets, such as airplane turbines or windmills, have been subject to this development, with increasing digitization more generally available objects and machines will populate digital twin solutions.
Whether consumer business, manufacturing or automotive: Many sectors in Industry 4.0 scenarios have the potential to greatly benefit from digital twins and related business and product modelling.
Drilling further down from broad industry examples, specific opportunities and use cases can be identified:
Industry examples of digital twins
Digital twins of windmills enable e.g. predictive maintenance. Sensor data from wind parks and power plants enable continuous surveillance.
IT components generate comprehensive amounts of data, real-time geo-information delivers location or status- specific alerts via digital twins.
Patients, health data, develop- ment of new drugs, forecasting demand for treatment could strongly benefit from digital twins.
Smart homes and smart cities, along with consumer-oriented services like virtual assistance, are strongly growing fields.
Digital twins simulate, visualize and optimize supply chain movements through real-time monitoring to increase efficiency.
Real-time monitoring of sensitive components like turbine engines provide the optimal data foundation for predictive maintenance.