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How Industry 4.0 Is the Next Revolution in Manufacturing

Manufacturing has evolved significantly since the Industrial Revolution that began in the 1760s. Today, the manufacturing industry is experiencing another revolution. Big Data, interconnectivity, and smart automation are fueling a new phase in manufacturing termed “Industry 4.0.” As this modern revolution takes hold, manufacturers that embrace a technology-driven approach position themselves for growth in an increasingly competitive and uncertain business landscape.

What Is Industry 4.0?

Industry 4.0 manufacturing represents the Fourth Industrial Revolution. It takes the power of data collected from sensor networks and smart machines as well as automation technologies and filters it through artificial intelligence (AI) and machine learning (ML) to improve profitability and efficiency. 

Historical context

Manufacturing has undergone four distinct phases of growth, each one characterized by a new source of power. The first harnessed water and steam energy, replacing the manual labor of man and beast. During the 19th century, a second revolution took place as manufacturers transitioned to oil, gas, and electricity to power assembly lines. The 1950s ushered in a third wave of innovation as computers, advanced telecommunications, and the advent of early data analysis technologies drove growth forward. We’re now amid a fourth, this time powered by smart machines, Industrial Internet of Things (IIoT) sensors, and advanced data analysis capabilities. 

Technologies driving Industry 4.0

Just as prior industrial revolutions were each initiated by disruptive technology, Industry 4.0 is transforming manufacturing operations with the latest technologies. 


IIoT sensors are at the vanguard of Industry 4.0 manufacturing practices. These internet-connected sensors can be installed on factory equipment to monitor metrics such as heat, pressure, and location. The data collected from a network of IIoT devices can be used to improve the efficiency of production lines, predict when machinery will need to be serviced, and monitor the stressors faced by humans on the production floor, ensuring workers stay safe while on the job. 

AI and machine learning

Manufacturing data can be fed into AI and ML algorithms to improve yields, analyze root causes of performance degradation, improve safety and fault detection, enhance virtual metrology, and improve energy management practices, among many other benefits. 

Cloud computing

Cloud computing technology offers a more economical way to store and process the vast reservoirs of data fueling Industry 4.0. Cloud computing has democratized the power of data, offering even small and medium-sized manufacturers the ability to collect and analyze data at scale.


With vast networks of IIoT devices and smart machinery deployed, manufacturers are increasingly vulnerable to cyberattacks seeking to steal proprietary data or cripple manufacturing operations. This elevated risk has driven developments in cybersecurity technologies.

Benefits of Adopting Industry 4.0

Manufacturers benefit in various ways by implementing the technologies that define the Industry 4.0 revolution. Let’s take a look at three of the most meaningful.

Enhanced strategic decision-making 

Decision-making teams continually optimize production levels, react to supply chain disruptions, predict future demand, and engage in other strategic initiatives. In an increasingly competitive global market, missteps are costly. By uniting data from manufacturing operations, supply chain, sales, warehousing, and human resources, advanced data analytics offers manufacturers a comprehensive view of their business. Using data to inform decisions results in better decision-making. 

Greater supply chain efficiency 

The past few years have highlighted the fragility of many manufacturers’ supply chains. As sources of potential disruption continue to grow, manufacturers who leverage the power of data are better positioned to create flexible supply chains that result in quality products delivered to customers on time. Advanced data analytics is capable of flagging potential disruptors before they manifest by analyzing massive data sets drawn from diverse sources including historical demand trends, changing patterns of consumption, supplier reliability metrics, and transportation contractors. This capability enables decision-makers to achieve more-effective contingency planning and learn precisely when to deploy those plans. 

Enhanced customer service

Satisfied customers are the lifeblood of any manufacturing operation. Delivering the right products on time, every time, is only possible when manufacturers have flexible manufacturing capabilities, a resilient supply chain, and the ability to accurately forecast future demand. Industry 4.0 manufacturing practices put this objective within reach. 

Industry 4.0 Manufacturing Use Cases

Powered by data, the Industry 4.0 manufacturing revolution is upending how manufacturers source raw materials and develop, build, and transport their products. Those investing in technology are already seeing substantial benefits. Here are just a few manufacturing use cases to highlight what’s possible with Industry 4.0.

More-accurate demand forecasting using internal and third-party data sources

Accurately forecasting future demand is essential for maintaining profitability, preventing in-demand items from being back-ordered, and ensuring less popular products don’t languish on shelves. Before Industry 4.0, producers relied on a handful of incomplete data sources, including historical sales numbers and purchase orders to project future demand. Fast-forward to today. AI and ML algorithms can process numerous data sets from various sources, including supplier data, customer data, weather data, demographic data, and economic indicators. This diversity of data sources results in much more accurate demand forecasting.

Quality assurance using IIoT sensors

IIoT sensors can be deployed across the factory floor to assess a range of quality assurance parameters. This network of sensors can detect production issues as they happen, alerting operators as quality assurance failures occur. This information allows production line teams to react quickly, identifying and correcting defects before products are shipped to customers.

Productivity gains using digital twins

Digital twins are virtual clones of manufacturing lines, supply chains, and distribution networks. These replications allow decision-makers to adjust different parameters, modeling how significant changes in operations may result in improved outcomes without changing anything in reality. This capability enables zero-consequence testing of potential adjustments that may result in substantial efficiency gains.

Supply chain visibility 

A diversity of suppliers, strained global transportation networks, and just-in-time manufacturing practices leave little room for error when it comes to maintaining a reliable supply chain capable of keeping production running at capacity. Using predictive analytics tools, a manufacturer can gain insights into how factors such as severe weather, labor shortages, the insolvency of a key supplier, or impending port congestion are likely to impact deliveries of raw materials, allowing them to make the adjustments needed to maintain normal operations.

Snowflake and Industry 4.0 for Manufacturing 

The Snowflake platform delivers the performance, scalability, and data sharing capabilities needed for Industry 4.0 technologies, including IIoT, machine learning, and advanced data analytics. Snowflake is powering supply chain optimization, production quality and efficiency, manufacturing automation, and robotics and IIoT initiatives for manufacturers across the globe.

Gain a global real-time view of your supply chain while also leveraging local data to meet complex information requirements. Break down data silos across SCM systems, ERP platforms, order fulfillment systems, and IIoT devices to gain complete visibility of your manufacturing processes. Power ML and AI with comprehensive, up-to-the-second data to improve product quality. Snowflake serves as a data hub, data lake, and foundation for data applications, among many other use cases for manufacturers who want to capitalize on Industry 4.0 opportunities. 

See Snowflake’s capabilities for yourself. To give it a test drive, sign up for a free trial