What is Industry 4.0—the Industrial Internet of Things (IIoT)?
Industry 4.0 refers to a new phase in the Industrial Revolution that focuses heavily on interconnectivity, automation, machine learning, and real-time data. It includes cyber-physical systems, the Internet of things, cloud computing and cognitive computing. Industry 4.0 is commonly referred to as the fourth industrial revolution. Industry 4.0, also sometimes referred to as Industrial IoT (IIoT) or smart manufacturing, marries physical production and operations with smart digital technology, machine learning, and big data to create a more holistic and better connected ecosystem for companies that focus on manufacturing and supply chain management. While every company and organization operating today is different, they all face a common challenge—the need for connectedness and access to real-time insights across processes, partners, products, and people.
Evolution of Industry from 1.0 to 4.0
Before digging too much deeper into the what, why, and how of Industry 4.0, it’s beneficial to first understand how exactly manufacturing has evolved since the 1800s. There are four distinct industrial revolutions that the world either has experienced or continues to experience today.
The First Industrial Revolution
The first industrial revolution happened between the late 1700s and early 1800s. During this period of time, manufacturing evolved from focusing on manual labor performed by people and aided by work animals to a more optimized form of labor performed by people through the use of water and steam-powered engines and other types of machine tools.
The Second Industrial Revolution
In the early part of the 20th century, the world entered a second industrial revolution with the introduction of steel and use of electricity in factories. The introduction of electricity enabled manufacturers to increase efficiency and helped make factory machinery more mobile. It was during this phase that mass production concepts like the assembly line were introduced as a way to boost productivity.
The Third Industrial Revolution
Starting in the late 1950s, a third industrial revolution slowly began to emerge, as manufacturers began incorporating more electronic—and eventually computer—technology into their factories. During this period, manufacturers began experiencing a shift that put less emphasis on analog and mechanical technology and more on digital technology and automation software.
The Fourth Industrial Revolution, or Industry 4.0
In the past few decades, a fourth industrial revolution has emerged, known as Industry 4.0. Industry 4.0 takes the emphasis on digital technology from recent decades to a whole new level with the help of interconnectivity through the Internet of Things (IoT), access to real-time data, and the introduction of cyber-physical systems. Industry 4.0 offers a more comprehensive, interlinked, and holistic approach to manufacturing. It connects physical with digital, and allows for better collaboration and access across departments, partners, vendors, product, and people. Industry 4.0 empowers business owners to better control and understand every aspect of their operation, and allows them to leverage instant data to boost productivity, improve processes, and drive growth.
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Basic Industrial IoT Concepts and Glossary of Terms
There are hundreds of concepts and terms that relate to IIoT and Industry 4.0, but here are 12 foundational words and phrases to know before you decide whether you want to invest in Industry 4.0 solutions for your business:
- Enterprise Resource Planning (ERP): Business process management tools that can be used to manage information across an organization.
- IoT: IoT stands for Internet of Things, a concept that refers to connections between physical objects like sensors or machines and the Internet.
- Industrial IoT (IIoT): IIoT stands for the Industrial Internet of Things, a concept that refers to the connections between people, data, and machines as they relate to manufacturing.
- Big data: Big data refers to large sets of structured or unstructured data that can be compiled, stored, organized, and analyzed to reveal patterns, trends, associations, and opportunities.
- Artificial intelligence (AI): Artificial intelligence is a concept that refers to a computer’s ability to perform tasks and make decisions that would historically require some level of human intelligence.
- M2M: This stands for machine-to-machine, and refers to the communication that happens between two separate machines through wireless or wired networks.
- Digitization: Digitization refers to the process of collecting and converting different types of information into a digital format.
- Smart factory: A smart factory is one that invests in and leverages Industry 4.0 technology, solutions, and approaches.
- Machine learning: Machine learning refers to the ability that computers have to learn and improve on their own through artificial intelligence—without being explicitly told or programmed to do so.
- Cloud computing: Cloud computing refers to the practice of using interconnected remote servers hosted on the Internet to store, manage, and process information.
- Real-time data processing: Real-time data processing refers to the abilities of computer systems and machines to continuously and automatically process data and provide real-time or near-time outputs and insights.
- Ecosystem: An ecosystem, in terms of manufacturing, refers to the potential connectedness of your entire operation—inventory and planning, financials, customer relationships, supply chain management, and manufacturing execution.
- Cyber-physical systems (CPS): Cyber-physical systems, also sometimes known as cyber manufacturing, refers to an Industry 4.0-enabled manufacturing environment that offers real-time data collection, analysis, and transparency across every aspect of a manufacturing operation.
Benefits of Adopting an Industry 4.0 Model
Industry 4.0 spans the entire product life cycle and supply chain— design, sales, inventory, scheduling, quality, engineering, and customer and field service. Everyone shares informed, up-to-date, relevant views of production and business processes—and much richer and more timely analytics.
Here is a quick, non-exhaustive list of some of the benefits of adopting an Industry 4.0 model for your business:
- It makes you more competitive, especially against disruptors like Amazon. As companies like Amazon continue to optimize logistics and supply chain management, you need to be investing in technology and solutions that help you improve and optimize your own operation. To stay competitive, you have to have the systems and processes in place to allow you to provide the same level of service (or better) to your customers and clients that they could be getting from a company like Amazon.
- It makes you more attractive to the younger workforce. Companies that invest in modern, innovative Industry 4.0 technologies are better positioned to attract and retain new workers.
- It makes your team stronger and more collaborative. Companies that invest in Industry 4.0 solutions can increase efficiency, boost collaboration between departments, enable predictive and prescriptive analytics, and allow people including operators, managers, and executives to more fully leverage real-time data and intelligence to make better decisions while managing their day-to-day responsibilities.
- It allows you to address potential issues before they become big problems. Predictive analytics, real-time data, internet-connected machinery, and automation can all help you be more proactive when it comes to addressing and solving potential maintenance and supply chain management issues.
- It allows you to trim costs, boost profits, and fuel growth. Industry 4.0 technology helps you manage and optimize all aspects of your manufacturing processes and supply chain. It gives you access to the real-time data and insights you need to make smarter, faster decisions about your business, which can ultimately boost the efficiency and profitability of your entire operation.
Industrial IoT (IIoT) Use Cases
1. Machine Monitoring
Sensors and other intelligence can be added to new or existing plants in order to monitor exterior parameters—like AC current consumption and vibration levels—through a retrofit process to look for pumps that need maintenance or are approaching failure. For example, if you need to know when the air pressure is low in your conveyer belt system, battery-powered sensors can collect that data and wirelessly transmit it back to a central source to tell you if any kind of malfunction has occurred or will occur soon. Until recently, getting third party data out of a plant was very difficult.
Swiss company ABB, a global leader in industrial technology, uses smart sensor-based connectivity technology to monitor the performance of its low voltage induction motors. Each motor is fitted with a smart sensor that provides data about the motor’s condition and performance. When an impending problem is identified, the factory can plan a timely repair or order a replacement if necessary. With downtime costs usually in the neighborhood of a few hundred dollars an hour, this type of preventive monitoring translates to significant savings.
2. Monitoring For Toxic Gases and Indoor Air Quality
Whether a facility is monitoring its air quality for compliance or health reasons, enhancing those efforts with the IIoT helps ensure that goods and people are safe—without an expensive integration cost.
3. Monitoring Environmental Conditions In An Industrial Space
Hortilux, a provider of light solutions for greenhouse growers, developed an application that uses smart sensors to provide insight into greenhouse performance. The sensors collect data on greenhouse temperatures and CO2 levels to enable growers to optimize their growth strategies. Customers also use the data to minimize energy consumption, letting them switch off lighting when it’s not needed without sacrificing plant yields.
4. Indoor Asset Location
Finding out where inventory and supplies are located in a defined area has myriad benefits to many industries. For example, in an airport, it can be prohibitively expensive to pay a cellular carrier to monitor buses, vehicles, luggage carts, and fuel—but through defined area IoT asset tracking, you can improve your vehicle services and cut down on employee costs, all without a big M2M cellular bill.
5. Connecting Into Existing Modbus & Profibus Networks
Industrial IoT monitoring allows for data acquisition in older plants without disturbing existing industrial control networks. Factories that have been operating for more than 30 years often use legacy industrial wireline protocols to gather data and monitor a number of machines. While the systems aren’t modern, they are functional—and breaking the connections to replace them with a new IoT monitoring system can be difficult and expensive. Instead, factories can simply “listen in” on the legacy wireline connections and report out through another channel.
6. Inventory Monitoring & Management
Knowing where people and assets are located throughout a defined space can be critical in certain industries. Patient tracking, capital equipment tracking, behavioral monitoring, and health outcomes are all important IoT use cases in a health care setting.
Components Of An Industrial IoT System
1. Front-end Edge Devices
Sensor data is most of the IIoT, therefore the hardware used to gather and collect it is a critical component of the system. Front-end devices like sensors and control devices are responsible for collecting the continuous streams of data and acting on them.
2. Connectivity Technology
Once you’ve collected the data, you need a way to transmit it to the cloud and your IoT system also needs a way to receive commands from the cloud. That’s where connectivity comes in. Many industrial IoT solutions rely on wireless technology. There are a number of wireless options available, including: Wi-Fi, Bluetooth, Mesh networks, Cellular networks, LPWAN technology.
3. Industrial IoT Platforms For Data Analytics
This is most important. Today many IoT platform available for enterprise. An
Challenges in implementation of Industry 4.0:
- IT security issues, which are greatly aggravated by the inherent need to open up those previously closed production shops
- Reliability and stability needed for critical machine-to-machine communication (M2M), including very short and stable latency times
- Need to maintain the integrity of production processes
- Need to avoid any IT snags, as those would cause expensive production outages
- Need to protect industrial know how (contained also in the control files for the industrial automation gear)
- Lack of adequate skill-sets to expedite the march towards fourth industrial revolution
- Threat of redundancy of the corporate IT department
- General reluctance to change by stakeholders
- Loss of many jobs to automatic processes and IT-controlled processes, especially for lower educated parts of society
- Low top management commitment
- Unclear legal issues and data security
- Unclear economic benefits/ Excessive investment
- Lack of regulation, standard and forms of certifications
- Insufficient qualification of employees
Reference – https://en.wikipedia.org/wiki/Industry_4.0
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