The fourth Industrial Revolution is taking place right now and it will transform both the paradigm of the global economy, as well as the mechanisms by which the creation of economic value is determined. Like the 3 previous industrial revolutions, it will be based on the rapid adoption of new transformation technologies that will challenge everything we assume and change everything we think about each manufacturing process.
Today, manufacturing is evolving from the model and mindset that guided the previous three industrial revolutions, which focused on centralization and mass production to achieve economies of scale, to one based on mass customization and flexibility. with the real production of goods located near the centers where the demand is located.
Rather than creating and managing inventory, manufacturers are looking to build fully integrated supply chains that dynamically adapt to real-time requirements and demand from suppliers and upstream consumers. This includes the ability to anticipate and take corrective action in terms of real-time production adjustments. What makes this transformation revolutionary, is that manufacturers are looking to achieve all of this with minimal or ideally no human intervention in the entire end-to-end production process.
This manufacturing model is based on automation and the exchange of data between manufacturing technologies, and includes the integration of cybernetic systems, Internet of Things (IoT), cloud computing and Big Data.
Decentralization and automation with smart factories
The Industry 4.0 model essentially seeks to transform the factory into a computer or what is called “Smart Factory”, modular manufacturing processes can be developed by means of physical-computer systems, fused with computer technology to the machines themselves, not simply to control and monitor remotely.
These smart modular factories will be able to autonomously enable decentralization and automation of production decisions, as well as being able to communicate and cooperate via the Internet of Things (IoT) with human operators and other smart factories to complete a supply change. vertical or full horizontal.
Industry 4.0 Principles:
1. Interoperability: The ability of machines, devices, sensors, and people to connect and communicate with each other through IoT or the Internet of People (IoP).
2. Information transparency: Ability of information systems to create a virtual copy of the physical world by enriching digital plant models with sensor data. Requiring aggregation of raw sensor data to higher value context information.
3. Technical assistance: First, the ability of assistance systems to support human beings by aggregating and displaying information in an understandable way to make informed decisions and solve urgent problems at short notice. Second, the ability of cybernetic physical systems to physically support human beings carrying out a series of tasks that are unpleasant, too exhausting, or unsafe for their human collaborators.
4. Decentralized decisions: The ability of physical cybernetic systems to make decisions for themselves and perform their tasks in the most autonomous way possible. Only in the case of exceptions, interferences or conflicting objectives are tasks delegated to a higher level.
Industry 4.0 technical challenges
Revolutions, however, can be challenging and messy, and this one will be no different. Beyond the cultural and political challenges inherent in any change related to economic productivity, there are several technological challenges that must be overcome to enable the adoption of the Industry 4.0 model.
1. Data security problems are greatly increased by integrating new systems and greater access to those systems. Additionally, proprietary production knowledge becomes an IT security issue.
2. A high degree of reliability and stability is needed for successful cyber communication, but it can be difficult to achieve and maintain.
3. Maintaining the integrity of the production process with less human supervision could become a barrier.
4. Avoiding technical problems that could cause costly production outages is always a concern.
In a world where organizations struggle to ensure both the availability and security of resident technology in their data centers, the idea of building cyber applications that involve not only software, but also industrial machinery and the added responsibility of securing a factory where each machine.
Application performance, in particular, in an Industry 4.0 world will be exponentially more complex than it is today. When a traditional software application is down now or worse yet is slow, it is quite difficult to figure out what is causing the problem.
Most organizations have deployed a number of tools to help monitor and diagnose these problems and avoid last minute conference calls where the application team blames the network and the network team goes through an endless log to demonstrate that it is the database causing the problem.