It would be logical to start this article with some myth debunking. The smart factory conception doesn't imply that one can deploy a certain software and revamp the whole manufacturing process overnight. Instead, the concept of intelligent manufacturing means using machine learning, artificial intelligence (AI), robotics, the Internet of Things (IoT), additive manufacturing, and augmented reality technologies in conjunction.
What is a smart factory?
As of today, the three main cornerstones are shaping the innovative factory concept:
- The dominance of IoT solutions, sensors, and industrial robots;
- The intensive use of automation and data insights;
- Better regulatory compliance.
A smart factory takes root in Industry 4.0, a new chapter in the history of the Industrial Revolution. Companies such as Siemens AG, Robert Bosch GmbH, Emerson Electric Company, and Yokogawa Electric Corporation are already using smart factory strategies to improve business processes based on real-time production data.
In regard to the changing industrial landscape, manufacturers are en masse digitizing their factories. Last year, the international smart factory market hit $270.74 billion in valuation. The market is forecasted to reach $461.82 billion by 2026, registering a CAGR of 9% during five years.
Suppose you leave aside all the marketing fluff that comes with intelligent factories in the media. In that case, the main thing about a smart factory is the transparency and interconnection of working processes and systems within an industrial plant. Industry 4.0 emphasizes the use of real-time data, sensors, automation, machine learning (ML), and technologies such as PLC, SCADA, MES, HMI, etc. Robots (including collaborative ones), additive technologies (3D and 4D printing), industrial avatars controlled via neural interfaces, and other solutions are widely used in smart factories as well. Let’s dive into details.
What is the impact of a smart factory on industrial businesses?
First, a smart factory allows production lines to operate mainly autonomously, with the possibility of self-correction. Such self-correction is the hallmark of Industry 4.0 and represents its significant advantage over traditional production. Self-optimization allows you to predict and identify quality deterioration dynamics more quickly and helps find specific causes associated with the human error factor, equipment, or the environment. This level of self-optimization is attributed to the fact that today's intelligent manufacturing systems can learn and adapt in real-time, making businesses far more agile than ever before.
Second, smart factories are all about higher efficiency and productivity. The modern factory's ability to predict future results based on previously acquired and real-time data can increase uptime and prevent security issues. You can say that this concept takes the best out of both industrial devices and employees. Third, smart factories help introduce agile production processes using data collection so that manufacturers can build their decisions based on uncovered insights.
From a purely business perspective, smart factories allow:
- lowering costs;
- reducing downtime;
- minimizing waste (a vital feature concerning today’s ecological regulations).
Companies that rely on smart factory technological and management solutions aim to obtain economic benefits already at the stage of producing small batches of products or even single copies. Traditionally, this effect was achieved by reducing costs associated with mass production. The flexibility of a smart factory is about the rapid restructuring of production from one product to another and ensuring the production of various products within a given time frame and at a given production cost.
Another significant benefit is the introduction of computer modeling technologies at the stage of product design. With the concept of digital twins, it is possible to predict equipment response to operational loads with 95% accuracy and reduce the operating costs of industrial complexes by up to 10%.
At the same time, it's worth saying that not just any enterprise will benefit from full automation and digitalization. The corresponding measures require significant capital costs, which in the case of small enterprises may never pay off. This way, you need to find a balance between automation and manual labor.
A smart factory concept can also provide tangible benefits for health and safety and environmental sustainability. The operational efficiency results in less environmental waste compared to conventional production processes and generally contributes to greater environmental sustainability. The higher degree of automation of production processes reduces the likelihood of human error in various situations, including industrial accidents.
Data, data everywhere
The industrial Internet has become the most popular element of a smart factory. The conception represents an integrated system for collecting, transferring, storing, and processing the production process data gathered from sensors that control machine tools, welding installations, melting furnaces, chemical reactors, etc. This data from sensors go to an IT system for further analysis. With revealed insights at hand, manufacturers can develop timely technological and management decisions.
The problem is most manufacturing businesses find themselves at the first level of smart factory maturation. That basically means that they have already successfully digitized and automated some working processes and operations. However, they don't take any actionable insights from the data they collect. In other words, collecting data doesn’t mean using it the proper way. The second and third maturity stages take data collection to a whole different level: dashboards and visualization tools make data accessible and understandable. This way, manufacturers can have a clear vision of what's going on inside their factories and make decisions proactively.
What's ironic is that, at the same time, the abundance of data is one of the main problems in smart factory expansion. Many companies haven't yet learned how to select relevant information on their technological processes. Instead, they accumulate all of it, which is non-efficient, to say the least. What's more, the sensors are often located in incorrect places, not reaching the system’s critical points and without understanding how the data is related to the technological process. The information's completeness is nowhere to be seen, which means that data is pretty much useless.
Another serious challenge is of an economic (and somewhat human) nature. On the one hand, the transition to a smart factory comes with a tangible and beneficial economic impact. On the other hand, the whole process from A to Z is a lengthy and highly costly business. First, you have to restructure the entire production system and purchase expensive equipment for collecting, storing, and processing data. Second, it's necessary to create costly high-quality digital models (digital twins) of production.
And here’s where the problem lies. The management of a factory begins to consider the effect of digitalization and realizes that the possible savings it may bring will not be enough to recoup the costs of digitalization here and now. It might take several years to do so. What's the outcome? The purchase of expensive modern equipment seems a risky business, and many decision-makers refuse to carry on.
One more challenge is integrating new equipment with the current infrastructure and the compatibility of existing devices to the latest technology. The common situation is when the old equipment requires some protocols while new devices require some other. Machine-to-machine communication is all about a robust communication system. For instance, modern manufacturing systems need the IPv6 connectivity protocol to support several devices connected simultaneously.
Cybersecurity is vital too. As said earlier, smart manufacturing systems require reliable network connectivity. However, sharing information through the Internet is dangerous without proper end-to-end data encryption measures. To do so, manufacturers should protect all the network's nods against external interference and data mistreatment.
To Sum Up
Although the introduction of intelligent manufacturing technologies is associated with operational and financial risks, these risks can’t compete with the benefits that such technologies bring. In addition, most risks can be mitigated by implementing effective change management strategies, using measurable approaches to validating technology viability, and additional investment.
Despite the difficulties in the transition from traditional to smart production, there is no doubt that all modern players will have to change existing business models and adopt the concept of an intelligent factory. Every year, Industry 4.0 technologies will increasingly penetrate production processes and supply chains. The analysis of production's objective factors, equipment wear, and quality of raw materials make it possible to get the maximum return on equipment and ensure an increase in production volumes of up to 30%.
Do you think about making your factory smart? We invite you to transform your factory and reimagine production with Industry 4.0 technologies and Industrial Internet of Things (IIoT) consulting and development services. We build our client relations based on our long-standing experience in Industry 4.0 consulting and software development services. Contact us, and let’s start your journey towards digitalization today.
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