What is Industry 4.0?
Klaus Schwab, founder of the World Economic Forum, coined the term "Fourth Industrial Revolution" to describe the progress in automation in traditional manufacturing and industrial practices, namely the use of machine-to-machine communication and the Internet of Things (IoT) surrounding self-monitoring.
We are now experiencing an unprecedented pace of development, to the point that our brains are no longer capable of perceiving or analyzing our environment in the same way. To remain competitive, companies will have to rely on machines and artificial intelligence to handle some of the most demanding tasks. Those that remain stagnant and refuse to adopt these new tools will face significant competitive challenges.
However, the need for greater analytical capabilities is not the only reason for this current adoption. Certain technological changes have created unprecedented opportunities.
These three technological shifts make Industry 4.0 possible.
1. The integration of different disciplines in the past
Industrial technology is developing at an exponential rate, partly due to the convergence of previously unconnected scientific and technological disciplines such as machine-to-machine communication, robotics, artificial intelligence, nanotechnology, and synthetic biology.
2. The granularity of data insights has increased significantly.
Humans need data to iterate and innovate. When using the same datasets for extended periods, we can only drive insights and innovation. However, with a significant increase in granularity—similar to examining old data under a microscope for the first time—we have new datasets to analyze. We are now able to:
▲View and analyze high-frequency data.
▲Sampling and streaming at unprecedented speeds.
▲Analysis using neural networks.
▲Execute the algorithm at the edge.
Using this new data, we can understand complex activities in real time and make data-driven decisions. This enhanced understanding leads to additional insights and even new areas of science.
3. Reliable basic technology
These significant technological advancements have formed the necessary pillars to support Industry 4.0:
▲Bandwidth
▲Digitalization
▲Interoperability
▲Data Transparency
For example, network bandwidth has developed to the point where high-definition video calls can be made globally, and IoT devices can easily communicate via cellular networks.
We are also beginning to see truly exciting levels of interconnectivity. This enhanced interconnectivity is unlocking new innovations as we overcome the challenges of using different protocols, languages, and data in different formats.
Another key factor is increased data transparency – which allows us to extract data that was not easily accessible before and to create new insights.
Without these foundations, Industry 4.0 and the Industrial Internet of Things (IIoT) would be impossible. So, if you're ready, where do you begin?
The Road to Change
It's important to remember that not all IoT is created equal. Capabilities have a natural evolutionary process, and while your organization might want to quickly transition to a highly mature IoT deployment, this is largely impossible if you haven't experienced the early stages of IoT development.
Using our IoT maturity model as a framework, you can lay the foundation for long-term sustainable success and profitability.
Phase 1: Embedded Devices
The code runs independently on a single device and does not interact with other devices.
Phase 2: Cloud Computing
Computing services obtained through the Internet, such as servers, storage, database networks, software, analytics, and intelligence.
Phase 3: Internet of Things
This combines embedded devices with cloud computing. The code connects machines over a network and facilitates communication.
Phase 4: Predictive Maintenance and Analysis
Use machine learning to gather predictive business insights from data collected from IoT devices.
Phase 5: Normative Analysis
Use advanced machine learning to gather prescriptive insights from IoT device data, such as recommending additional products/services to customers based on their behavior.
Phase 6: Ubiquitous Computing
Computing power is available throughout the physical environment, inside and outside the enterprise, but is largely invisible to the user.
These stages point to the path to maturity and income, but there are also some pitfalls to avoid along the way.
Avoid these pitfalls on the road to IoT maturity
Avoid decision paralysis. We often see companies with vast IoT opportunities struggle to launch projects because they can't reach a consensus or develop a compelling ROI model—often because they try to deploy too much at once. Don't try to boil the ocean; start small and adjust continuously.
Avoid large, high-risk investments. Don't make huge investments without proper market validation. Instead, start small and use a readily achievable project to demonstrate your investment returns. If this readily achievable project fails, it's a good sign that your initial assumptions are invalid and you can reconsider further investments.
Avoid reinventing the wheel. Several proven models already exist. From a workflow perspective, these include agile and lean methodologies. When it comes to AI and you're considering building versus buying, remember—just because you can't find what you're looking for doesn't mean the solution has to be completely custom-designed. Some models require minimal engineering work to plug in. Minimize risk by consulting industry IoT experts familiar with these established frameworks and solutions.
Avoid compromising operational security. Maintaining a security-first mindset is crucial when working with the Internet of Things (IoT). Remember that you may be opening up new attack vectors through IoT, and don't let pressure to launch a minimum viable product (MVP) cause you to neglect security.
Industry 4.0 is here.
With IoT deployments failing, it is crucial to follow in the footsteps of those who have succeeded.
