You’re probably thinking this is another blog post about two relatively new technologies tossed around as the new hot topic in today’s “manufacturing landscape”. And you’re not completely wrong!
The thing is, Industry 4.0 isn’t exactly a technology, it’s more akin to a concept.
Industry 4.0, or the fourth industrial revolution, is the integration of digital technologies into manufacturing and industrial processes to create smart systems. One of these digital technologies includes IIoT (Industrial Internet of Things) networks.
Initially, Industry 4.0 and IIoT originated from different perspectives. However, the trend of pairing them up has been getting traction as both terms evolved and began to share common goals.In this article featuring Industry 4.0 and IIoT, you’ll learn:
- The evolution of Industry 1.0 to 4.0
- Industry 4.0 vs. IIoT: what are the differences and similarities between these two?
- How Industry 4.0 and IIoT fit together
- One use case of Industrial 4.0 and IIoT for industrial automation
Without further ado, let’s begin.
Evolution of Industry 1.0 to 4.0
So, how did we get to Industry 4.0?
It’s almost like we’re experiencing the industrial equivalent of software updates, isn’t it?
The evolution of Industry 4.0 represents a significant shift in industrial processes. Before the pre-industrial era, we primarily relied on manual labor. But today, digital technologies and automation have revolutionized the way we produce goods.
Here are the key components of the evolution of Industry 1.0 to 4.0:
Industry 1.0
- Inception: 18th century.
- Key discovery: Steam power for industrial processes.
- Main benefits: Higher productivity and the ability to mass-produce goods.
- Advancement over predecessors: Before Industry 1.0, manufacturing relied heavily on manual labor, which meant production was inconsistent and often slow. However, with the introduction of steam power to drive engines, a period of mechanization emerged. Mass production of goods and their fast transportation were possible thanks to steam engines and steam-powered locomotives.
Fun fact: Industry 1.0 saw the rise of the textile industry, with inventions like the spinning jenny and the power loom which changed textile manufacturing forever.
Industry 2.0
- Inception: Late 19th century to early 20th century.
- Key discovery: Assembly lines powered by electricity.
- Main benefits: Production in a standardized assembly line increased productivity and reduced costs.
- Advancement over predecessors: Prior to Industry 2.0, goods were assembled (from start to finish) in a single station. This resulted in variations in quality, slow production rates, and high costs. With Industry 2.0, standardized production processes and assembly lines became common, which led to more efficient production and reduced costs as tasks were divided among multiple stations along the assembly line. This also meant goods were more affordable and accessible to customers.
Fun fact: Henry Ford’s introduction of the moving assembly line in 1913 revolutionized automobile manufacturing. It reduced the time to build a car from over 12 hours to just 93 minutes.
Industry 3.0
- Inception: The 1970s or late 20th century
- Key discovery: Automation of manufacturing processes, robotics, and programmable logic controllers (PLCs).
- Main benefits: Production processes without human assistance and the ability to mass-produce more complex goods.
- Advancement over predecessors: Manufacturing processes were either semi-automated or manually operated and data silos were common as there was limited integration between machines, equipment, and systems. Industry 3.0 marked the integration of digital technologies in manufacturing using computerization. This meant it was possible to automate entire production processes (without human intervention), improving efficiency and flexibility.
Fun fact: The introduction of the first industrial robot, the Unimate, in 1961 by George Devol and Joseph Engelberger marked the beginning of robotic automation in manufacturing.
Industry 4.0
- Inception: 2011 or 21st century.
- Key discovery: Internet of Things (IoT), cloud computing, and Artificial Intelligence (AI) in manufacturing.
- Main benefits: Data-driven decision-making, predictive maintenance, and overall more connectivity between digital technologies and physical processes.
- Advancement over predecessors: Before Industry 4.0, manufacturing faced challenges regarding the limited connectivity between industrial systems. This made it difficult for manufacturers to access real-time data and make informed decisions. Also, traditional manufacturing systems were designed for mass production, making changes based on customer demand and specifications more challenging. And with the rise of awareness about global warming, sustainability and environmental impact became crucial for companies. Industry 4.0 facilitated the connection of industrial systems, machines, and processes through IoT allowing real-time data exchange and collaboration. Technologies such as digital twins enabled customizable production processes for companies to adapt to customer demand. Thanks to data-driven decisions, it was easier to optimize resources such as energy, waste, and water which minimized environmental impact.
Fun fact: The term “Industry 4.0” was coined in Germany as part of a government initiative aimed at promoting the digitalization of manufacturing.
Industry 4.0 vs. IIoT
Industry 4.0 and IIoT are closely related and are often used interchangeably as they share common goals. However, they have a different focus and scope.
Here’s a breakdown of their differences and similarities:
Differences Between Industry 4.0 and IIoT
Scope and focus:
- Industry 4.0 is a broader concept that represents the transformation of industrial processes using digital technologies.
- IIoT is a specific technology that refers to the integration of IoT in industrial settings.
Integration:
- Industry 4.0 integrates multiple technologies such as IoT, IIoT, cloud computing, and AI.
- IIoT could be called a subset of Industry 4.0 as it focuses on connecting industrial equipment and devices to collect and exchange data for posterior analysis.
Similarities Between Industry 4.0 and IIoT
- Decision-making based on insights: Both concepts stress the importance of using data to identify patterns, trends, and opportunities for improvement to optimize industrial operations.
- Predictive maintenance: Both, Industry 4.0 and IIoT, facilitate predictive maintenance. IIoT uses information from sensors and other data sources to monitor the condition of your industrial equipment which helps prevent unplanned downtime, reduces maintenance costs, and extends the life cycle of assets. And Industry 4.0 uses IIoT sensors to achieve the same.
- Integration between different industrial systems: Both terms promote integration and interoperability between the different components of an industrial environment.
How Industry 4.0 and IIoT Fit Together
In simple terms, Industry 4.0 is a broader concept that engulfs IIoT.
When it comes to connectivity, IIoT can be considered the technology that allows Industry 4.0 to link industrial devices, sensors, and machinery to the internet—and each other. IIoT empowers Industry 4.0 to exchange data and the creation of an interconnected system.
However, Industry 4.0 is a concept that encompasses more digital technologies creating a smart system and interconnected system.
IIoT and Industry 4.0 Use Case: Siemens AG
Siemens, a German technology company and leader in industrial automation, implemented Industry 4.0 and IIoT solutions at their Electronics Works Amberg (EWA) facility to optimize manufacturing processes, increase efficiency, and enhance productivity.
Here’s a summary of how IIoT and Industry 4.0 were used:
Connectivity and Data Collection (IIoT)
IIoT sensors were integrated into the production line to gather real-time data on machine performance, production rates, and quality metrics. This data was then transmitted to a central data platform using IoT connectivity technologies, facilitating seamless data collection and exchange.
Edge Computing and AI (Industry 4.0)
Siemens implemented edge computing to process data locally (either at the plant or machine), which helped a lot when there was a need for real-time data analysis and decision-making.
Additionally, AI algorithms were trained using process parameters and sensor data to predict equipment failures and optimize production processes. These AI-controlled models were instrumental in predicting the likelihood of defects in polychlorinated biphenyls (PCBs), enabling early detection and prevention of production issues.
Digital Twins (Industry 4.0)
Digital twin simulations were used to optimize production processes and achieve target cycle times for manufacturing components. The simulation results were pivotal in identifying and replacing inefficient machine modules, thereby improving production efficiency.
In summary, the integration of IIoT and Industry 4.0 technologies at Siemens EWA enabled seamless connectivity, real-time data analysis, predictive maintenance, process optimization, and cybersecurity. As a bonus, this resulted in improved efficiency, productivity, and reliability in manufacturing operations.
Final Thoughts
As we learn more about Industry 4.0 and IIoT, we can’t help but wonder what the future holds. There are rumors of Industry 5.0 coming.
(Yes, just a little over a decade since Industry 4.0)
Industry 5.0 is rumored to be the era of human-machine collaboration, and it promises to take automation and connectivity to unprecedented heights.
Wondering what happens next is probably a sentiment that echoes throughout history. From the anticipation of steam power in the 18th century to the dawn of AI-driven manufacturing in the 21st, each era brought a sense of wonder and excitement.
Today, at the cusp of Industry 4.0, with technologies for every vulnerability and need, we are impatient and willing to learn whatever comes.
Industry 4.0 & IIoT
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