Manufacturing 4.0 explained in detail, its key features, use cases, and real-life examples
If you step inside any factory floor today, you’re unlikely to see any similarity with the leading factory of ten or even five years ago. Today’s factories are equipped with IoT devices and integrated with emerging technologies, including cloud computing, AI, and ML.
This is how industry 4.0 is paving its way for the manufacturing industry, enabling factories to collect, analyze, and make decisions based on immense stockpiles of data. But what’s the value for business owners? Increased automation, a new level of process efficiencies, and improved quality at lower costs, to name a few.
In this post, we’re speaking about the biggest shift that hit global manufacturing since automation — the phenomenon of manufacturing 4.0, its characteristics, technologies, and effects.
What is industry 4.0 in manufacturing?
Industry 4.0, also known as manufacturing 4.0, mixes the latest manufacturing technologies with IT, such as IoT, big data and analytics, artificial intelligence (AI), and machine learning (ML), in order to improve business processes and allow for better decision-making.
Characteristics of industry 4.0 in manufacturing
The definition of industry 4.0 is rather vague, and it’s often used interchangeably with other notions, including manufacturing 4.0, smart manufacturing, and a smart factory. It’s easier for us to define its main features to be sure you understand it right.
So, industry 4.0 in manufacturing is usually characterized by:
The bridging of the physical and digital world through the use of cyber-physical systems (CPS). CPS refer to intelligent physical components, objects, and software systems with embedded computing and storage capabilities. These systems form the basis of industry 4.0 and are enabled by Industrial IoT (IIoT).
Enhanced decision-making thanks to embedded sensors and interconnected machinery. IoT and IIoT produce lots of big data, which manufacturers can then analyze to explore historical trends, identify patterns, and use in production decision-making. A company can even build a complete virtual representation of the industrial processes and create a so-called digital twin.
Interconnectivity achieved by sensors, devices, and machines fully integrated into manufacturing. A smart factory means integrated operation technology with IT and, thus, smooth cooperation between the two departments.
Real-time monitoring, enabled by the use of IoT and IIoT again. This ensures a timely response to any changes on the factory floor and minimizes the waste of resources.
Decentralized manufacturing as CPS are able to decide on their own and help to perform tasks autonomously. Manufacturing 4.0 doesn’t rely on central computers or pass the decision hierarchically. Instead, it provides more flexibility to local operators and allows them to respond to changes in place.
Improved information transparency due to collected data from sensors. This provides a better understanding of the manufacturing processes and, thus, contributes to data-driven decisions.
Product customization that meets individual customer needs, yet remains cost-effective. With advanced technologies such as 3D printing, smart factories stand aside from a one-fits-all model. Instead, they could easily create more diversified goods for customers.
What technologies are driving Industry 4.0?
Let’s also take a closer look at the most important technologies that make a difference in manufacturing 4.0. Together, the five technologies from the list form a high-tech ecosystem on the factory floor and help to increase process efficiencies.
1. IoT and IIoT
IoT/IIoT sensors are probably the most critical component of smart factories. These connect machines between themselves and to the networks and provide monitoring of equipment, its components, processes, and products.
The technology makes it possible to capture large amounts of data in real-time related to the manufacturing process. Later, this data can be analyzed to understand the behavior of the industrial environment to streamline business processes and optimize supply and demand.
2. AI and ML
Although valuable, the data received from IoT/IIoT devices is too vast for people to analyze manually. Fortunately, AI and ML algorithms are skillful enough to contextualize this info, find anomalies, and make recommendations based on this.
The most explicit example is the use of ML in predictive maintenance in manufacturing in order to detect early warning signs of equipment breakage or degradation. An ML-powered model can track and warn about temperature anomalies on the factory floor (or any other deviations). The manufacturer will then interfere timely before the real issue occurs.
3. Cloud computing
Smart manufacturing is impossible without cloud computing, which provides connectivity and integration of machines, equipment, and components. Another advantage of the cloud includes infrastructure, storage, platforms, and software applications. Cloud providers deliver them to store and manage the data received from IoT. Still, businesses don’t need to buy all this at once. They can scale their operations gradually, paying only for those resources and services they’re using.
4. Edge computing
Some issues, such as those related to safety or quality, need to be resolved immediately. So, data analysis should take place at the “edge” — where the data is created. This is possible with the use of edge computing which aims to bring computation and storage closer to the source of data.
While edge computing minimizes security risks, the manufacturer also saves itself from too much dependence on a reliable network.
5. Digital twin
Digital transformation provided by manufacturing 4.0 also gives way to digital twins — digital replicas of processes, production lines, or even the entire plant. This technology helps to improve performance and workflows on the factory floor, yet also test changes in a cost-effective manner. For instance, a manufacturer can test a new product design without actual investment in production.
What effect will industry 4.0 have on manufacturing?
Industry 4.0 can deliver irresistible returns to manufacturers if implemented and maintained properly. Connected, smart manufacturing, enhanced by a fully automated production process, is a major return on investment.
Still, not every manufacturer is ready to venture into the upfront investment needed for launching a pilot smart factory project. If you need a couple of more reasons why a smart factory is worth investing in, here are the meaningful returns:
1. Increase in productivity
Enhanced productivity is the primary advantage of industry 4.0 in manufacturing. It’s also the major goal of smart factory projects. Manufacturers want to get rid of repetitive and tiresome tasks and use smart machines for this type of work. Meanwhile, human operators spend their time monitoring and maintaining systems only.
Altogether, this means faster, more efficient production around the clock and an increase in the production rate.
2. Quality improvements
While performance is the first and most important for manufacturers, product quality comes second. Fortunately, the 4.0 era has all chances to help you deliver better quality products. Processes get more automated while less human engagement means fewer errors. Besides, real-time monitoring, smart sensors, and AI/ML algorithms allow manufacturers to detect any quality issues and react to them quickly.
3. Enhanced customer experience
The improvements in product quality logically lead to a better customer experience. Moreover, the use of smart machines and automation technologies means that the manufacturer can produce goods faster and in more quantity. This increases the satisfaction level of customers, as they no longer face issues when the product is unavailable in the market.
Finally, manufacturing 4.0 contributes to products becoming more customized. Thanks to innovative technologies, a smart factory can mass-produce lines of personalized products. It can experiment with more designs and test them via digital twins, shorten routes between production and delivery, co-create, etc.
Another benefit of industry 4.0 that we can’t ignore is its cost-efficiency. Manufacturers should expect lower expenses with automated tasks and fewer production errors. Labor costs also decrease since manufacturers need fewer workers for everyday, repetitive tasks.
And one more thing to mention here. A more efficient production process, especially if a manufacturer enables predictive maintenance, means lower downtime and maintenance costs.
5. Better business continuity
When the equipment or its component breaks down, manufacturers need time and costs to replace or fix it. Now imagine this is a piece of very critical machinery that is experiencing issues — some industrial equipment that your plant cannot work without. So, add here the effects of downtime costs and damaged reputation as orders are canceled or delayed.
With industry 4.0, your business continuity won’t be affected this much. Industrial assets are connected and monitored in real time. So, any equipment issues are addressed immediately or, better, prevented. Advanced maintenance and monitoring capabilities can also help businesses notice patterns and insights in production, which you can then use to optimize the processes further.
6. Flexibility and agility
Big data, automation, AI, and machine learning also bring lots of flexibility to production. Now manufacturers can easily scale their production up or down depending on the seasonal demand and market fluctuations. They can also predict those chances and include or exclude new product lines, avoiding wasted resources in the future.
7. Higher competitiveness
Manufacturing 4.0 also brings more opportunities for companies to stay competitive in the market. By implementing a smart factory, a company can increase its production rates while also minimizing the wastage of materials and valuable resources. Earlier, outsourcing to cheaper regions was the only way for manufacturers to remain competitive. Now businesses can compensate for this with investments in technology.
Applications of industry 4.0 in manufacturing
As you can see, industry 4.0 is already transforming the manufacturing sector, especially when it comes to:
1. Asset tracking and optimization
With industry 4.0, manufacturers can locate and monitor equipment, its components, different machines, and work in process. IoT and IIoT devices at place help to increase visibility on the factory floor and keep track of every single stage of production. Based on the data collected, the factory can optimize its operations and improve productivity in the long run.
2. Quality management
Another important use case of industry 4.0 in manufacturing includes quality control and management. With the help of AI and ML, you can identify the parameters relevant to product quality and then monitor deviations, if any. For example, in the case study, we tell how we helped to keep track of quality issues for an appliance manufacturer and resolved repeated equipment failures.
3. Predictive maintenance
Partly mentioned, predictive maintenance allows manufacturers to predict and prevent potential equipment problems. Manufacturers do their best to maximize production efficiency. And it’s not really efficient if you perform maintenance at scheduled intervals. The equipment might not need any intervention at this stage. Still, it’s also a poor strategy to wait until the equipment fully degrades and breaks down, and a manufacturer has to spend a fortune for its replacement or repair.
From this perspective, predictive maintenance seems an optimized solution, with systems being able to know about the business problem arising before it occurs. So, you could fix it early, avoid unplanned downtime, and improve equipment uptime.
Learn more about predictive maintenance in manufacturing by reading our White Paper “Turn Predictive Maintenance into a Success Story for Your Manufacturing Company”.
Real-world examples of manufacturing 4.0
Now let’s learn about industry 4.0 examples in today’s business environment and how manufacturers are reaping advantages from this.
A truly great example of today’s smart factory is Audi. The company is combining modular assembly (producing pre-assembled modules rather than individual components) with industry 4.0 in its car production. The factory relies a lot on big data, trying to make its production as data-driven and flexible as possible. It’s also implementing many other manufacturing 4.0 projects, from the application of virtual reality to AI/ML to 3D printing.
The car manufacturer is transitioning to the production of the future. Just check its fascinating use of technology in the video:
The appliance manufacturer, Whirpool, introduced a powerful analytics system a couple of years ago. The company was planning to eliminate waste that was sent to landfills. In this case, ML technology has helped the company to monitor the amount of wastage produced by its factories, as well as the usage of resources like electricity or water.
Whirpool’s smart factory is also a vivid example of how to connect plants distributed across the globe. IoT technology and analytics help the manufacturer monitor its sustainability performance in every plant, aiming at some unity in its zero-wastage policy.
In 2018, Siemens received the industry 4.0 award for its manufacturing 4.0 solutions implemented in Elektronikwerk in Amberg (EWA), the smart factory in Germany. Equipped with AI/ML technology, lightweight robots, digital twins for production and quality control, and 3D printing, the electronics plant has people, machines, and equipment working side by side as a single mechanism.
The smart factory uses dashboards to track machine performance and product quality in real-time, so the workers could react quickly to any deviations. Overall, different industry 4.0 components help the company increase productivity, achieve a higher degree of flexibility, and reliability.
A large manufacturing company (under NDA) that we cooperated with has contacted us to solve the problem of repeated malfunctioning of the specific components of its hydraulic system. Of course, the industry 4.0 approach fitted best here.
The Intelliarts team has built an ML-based solution to predict the equipment failure of the components of the hydraulic system, prevent it from happening, and provide the proper maintenance to the facility. The customer was totally satisfied with the outcomes, with the ML models being almost 100% accurate in their results and predicting the failure right. Read the full case study on predictive maintenance to get to know how the solution was built.
Why does industry 4.0 define the future of manufacturing?
Although some manufacturers are still hesitating to adopt innovative technologies, it’s obvious industry 4.0 and smart factories are the new normal in manufacturing. And those who transfer to manufacturing 4.0 earlier have a high chance to be ahead of the competition, let alone leveraging multiple benefits that industry 4.0 brings to manufacturing:
Improved product quality
Increased resource utilization
If you want to give it a try, but still don’t know where to start, our advice is to start small by equipping your factory with IoT devices and introducing basic automation. In case you already have some IoT in place and would like to use it to your full advantage, we’d recommend scaling up with data analytics and AI/ML technology. Reach us to our Intelliarts team to discover how to move to data-driven decision-making in the most effective way.