fbpx
emerging technology

Industry 4.0: Achieving true digital transformation in manufacturing

Chris Powers
April 14th, 2021
8 MINUTE READ

For some time, the manufacturing sector has embraced the benefits of digital transformation. Seeking to create better production outcomes and superior operational capabilities, the sector has turned to cutting-edge technology to do the heavy lifting. That commitment to continuous innovation has led to a new industrial era, commonly referred to as industry 4.0.

What is industry 4.0?

In order to understand industry 4.0 and its impact on manufacturing, we need a brief history lesson. The 17th and 18th centuries saw the onset of the first industrial revolution. This era was defined by the rise of machines powered by steam and water in the manufacturing process, allowing industries like textiles and coal to flourish. The second industrial revolution of the late 18th and early 19th centuries was characterized by assembly line manufacturing and mass production thanks to electricity (think Henry Ford and the Model T).

Modern hardware and software systems inspired the third industrial revolution, ushering in an age of automation and efficiency driven by digital technology. While transformative in its own right, the third industrial revolution has laid the groundwork for what we now refer to as industry 4.0—or the fourth industrial revolution. 

When we talk about industry 4.0, we’re talking about a new age of digital transformation in manufacturing. Building on the digital technologies introduced in the third industrial revolution, industry 4.0 is all about creating more holistic and interconnected approaches to manufacturing. Beyond just creating more efficiencies in production, industry 4.0 helps manufacturers improve processes across their businesses to help scale and drive long-term growth.

What technologies are powering industry 4.0?

If you had to use one adjective to describe the technologies powering industry 4.0, it would be “smart.” These technologies provide the interconnectivity required to achieve unified production practices and strategies. Key technologies like the internet of things (IoT), artificial intelligence (AI), machine learning, and cyber-physical systems are helping usher in the age of industry 4.0. Let’s take a deeper look at some of the practical applications of these cutting-edge technologies.

Industrial internet of things (IIoT)

The industrial internet of things (IIoT) is the concept used to describe IoT’s applications in the manufacturing space. Manufacturers implement IIoT solutions to create networks of interconnected machines and devices that can monitor manufacturing processes, collect valuable data, analyze that data, and provide targeted feedback and insights, all in real-time. The insights that IIoT solutions provide can help manufacturers create better outcomes and make superior business decisions.

IIoT networks use sensors, radio-frequency identification (RFID) technology, and various types of software to collect data on the performance of machinery in a manufacturing setting. Then, extensive communication technologies convey this feedback from machines in real time—and incorporate industrial-scale data analytics and AI capabilities, too. Thanks to timely insights, feedback, and reporting, these networks help manufacturers achieve high levels of efficiency and performance. IIoT is considered the foundational technology of industry 4.0.

Big data

IIoT networks collect massive amounts of data in factories. In order to drive productivity and make other improvements, manufacturers need to be able to take this data, analyze it, and turn it into actionable insights. That’s where big data comes in.

Big data solutions can classify data collected from all aspects of an IIoT network and then use it to draw conclusions that help manufacturers improve operational efficiency. IIoT networks connect previously isolated machines and devices to collect data. Big data solutions automate the collection, visualization, and analysis of this data, giving manufacturers an unprecedented understanding of each and every system in their manufacturing processes.

Armed with the insights gleaned from big data solutions, manufacturers can:

  • improve operational efficiency,
  • pinpoint exactly where errors or issues exist in manufacturing processes,
  • conduct quality controls,
  • improve machine performance,
  • predict machine failure and implement intelligent maintenance plans,
  • and much more.

Artificial intelligence (AI) and machine learning

AI and machine learning technologies help big data solutions provide valuable insights to manufacturers without the need for human intervention. AI and machine learning tools implement data analysis algorithms to process data and make conclusions that they were not initially programmed to do. 

AI and machine learning tools are perhaps most applicable to predictive maintenance and demand forecasting for manufacturing. Big data solutions take in massive amounts of information from large-scale IIoT networks. Therefore, AI and machine learning tools can learn a lot over short periods of time, and eventually can learn to anticipate challenges that may disrupt production, like equipment failures. They can also forecast market and demand shifts that may directly affect production.  

Benefits of industry 4.0 technologies

While implementing industry 4.0 technologies can be costly—nobody said building the factory of the future was going to be cheap—the ROI manufacturers can achieve is immense. “Smart” factories can help manufacturers drive down costs, boost revenue, and achieve significant growth. Let’s look at some of the key benefits of implementing industry 4.0 technologies.

Improved efficiency and productivity

The real-time feedback and insights provided by industry 4.0 technologies can help manufacturers more effectively allocate resources in the factory. Predictive analytics can ensure factory managers are aware of potential equipment failures before they happen, meaning production lines experience less downtime as machine performance is properly monitored. AI and machine learning tools can automate some decision-making processes, enabling factories to run semi-autonomously. This cuts down on the amount of manual labor required for the production process, thus driving down costs.

Industry 4.0 technologies allow factories to run leaner while producing more products. Intelligent resource allocation and process automation mean significant cost savings and minimal downtime. 

Reduced costs

We touched on this a little bit above, but implementing industry 4.0 technologies can help manufacturers drive down costs and, as a result, boost revenue. While investing in industry 4.0 technologies is costly on the front end, it will ultimately drive down production costs over time. Thanks to automation, data management, intelligent systems integration, and more, manufacturers more effectively use resources, decrease production downtime, create less waste, and see a decrease in quality issues with products. All of these factors contribute to lower operating costs in the long run.

Increased collaboration and knowledge sharing

The manufacturing space has long been plagued by the siloing of its processes. Separate facilities run separate machinery, and there is little to no communication between individual elements of the manufacturing process. Production facilities could be located on different continents, with a facility lacking visibility into the status of another. As a result, there is little room for knowledge transfer.

By digitizing the entire manufacturing process and providing real-time monitoring, industry 4.0 technologies can help large-scale manufacturers share insights across their businesses. For example, if a specific machine is experiencing issues at a certain setting in one factory, this information can be shared throughout an organization, enabling other factories using the same machine to better understand how to manage it. And because “smart” factories use automated reporting, these insights can be shared automatically without the need for human intervention. In theory, data from one machine in one specific factory located anywhere in the world can help improve a large-scale manufacturer’s production process around the globe.

Examples of industry 4.0 technologies in factories

While the implementation of industry 4.0 technologies to achieve a “smart” factory may seem like a lofty goal for manufacturers, numerous organizations are already using these solutions in their manufacturing processes with some pretty amazing results. Let’s look at some examples of industry 4.0 technologies in action.

Whirlpool

A worldwide leader in home appliance manufacturing, Whirlpool has an ambitious goal of completely eliminating waste sent to landfills from its factories. In order to achieve this goal, Whirlpool implemented a robust analytics platform to monitor the amount of waste its factories are producing. Additionally, the platform can monitor how much electricity and water its factories use in the production process. 

Thanks to IIoT and this intelligent data analytics platform, Whirlpool can track how each of its factories around the world is performing in terms of its waste, and how close they are to achieving the zero-waste goal.

HP

In 2017, HP opened its first Smart Manufacturing Applications and Research Centre (Smarc) in Singapore. This state-of-the-art facility helps HP continuously innovate to improve its manufacturing processes—and aims to increase productivity by 20%. 

Smarc’s team of engineers manages 50+ supply lines around the world. Using cutting-edge technology like robotics, 3D printing, and big data analytics, the team works to develop advanced manufacturing techniques and approaches, embracing industry 4.0 practices to boost productivity for the entire company. 

HIROTEC

HIROTEC, a leading global auto parts manufacturer and supplier, needed to minimize downtime in its factories and production facilities. The company implemented IoT and augmented reality technology—combined with advanced analytics capabilities—to help improve production capabilities. Specifically, the company launched a platform to perform remote visualization of its automated exhaust system inspection line. Incorporating data from inspection robots, cameras, and even laser measurement devices, the platform offers HIROTEC real-time visibility into its operations. In turn, it helps the company look for areas to improve operational efficiency. It even uses machine learning capabilities to prevent equipment failures that would jeopardize the integrity of its inspection lines.

Wrapping up

Industry 4.0 is built on the foundation of interconnectedness. Using IIoT solutions, companies can deploy advanced manufacturing techniques and practices that harness the power of big data. Component technologies like AI and machine learning help factories run more efficiently and with less human interaction. Industry 4.0 approaches and technologies are building the factories of the future, and ushering in a new industrial revolution.
At Codal, we’re dedicated to promoting a smarter and more efficient future. As experts in digital transformation, Codal helps manufacturers grow and achieve their business objectives. Interested in learning more about our manufacturing capabilities? Reach out today.

Chris Powers
AUTHOR

Chris Powers

Chris is a Content Marketing Specialist at Codal. With a background in journalism and marketing, Chris has written about a variety of tech topics, including open source, fintech, and cybersecurity. Chris loves taking on new challenges with just a pen, paper, and his brain.

EXPLORE OTHER
ARTICLES

emerging technology

How precision agriculture technology is powering digital transformation in farming

user experience & design

A day in the life of a Codal UX designer