Smart factory: the smart or connected factory and Industry 4.0

Within what is already called the 4th Industrial Revolution, that of automation and digitization of production, there are sectors that go much more advanced than others. Take, for example, the car factories: thanks to the application of the latest technologies in terms of productivity, robotization and constant innovation (fruit of the commercial pressure that the whole sector is subjected to) European automotive factories remain at the forefront in the world productivity ranking, and that despite the being a real logistical, productive and technological challenge in which thousands of different parts must be assembled from many different suppliers different and that they must fit with millimeter precision. This allows the European automotive industry (and the ecosystem of companies around it) to be competitive with factories in the Southeast Asian, Chinese or Latin American area, where, despite lower labour costs, the same levels of productivity are not achieved.

The vast majority of car factories are already in a very advanced state of digitization, so they can already be called “smart factories”. Traditionally, the automobile’s production innovations have since spread to other sectors (from Henry Ford-era chain production to robotization, ‘Just In Time’ logistics or Lean Manufacturing) so with smart factories there is no doubt that the same process of “technological contagion” is already being followed.

When we talk about smart factory,smart factory or connected factory we mean production plants that interact in real time in aspects such as demand identification, supply chain, reconfiguration of production, maintenance, logistics and shipping (and any other element of the value chain)  generating a flow of information in real time that is processed and analyzed for immediate decision-making or even on a character predictive.

How does it affect my sector? How do you do this?

When we talk about smart factories these questions arise in the minds of the leaders of many companies. Obviously the answer to these questions requires a thorough study since each sector and each company are different. Digitization is not a substitute technology, but additive. It’s not about replacing thinking heads with Artificial Intelligence, but about adding both to a combination that generates value. And today we are not only talking about immediate monetary value but also customer value, environmental value and corporate social responsibility value.

First, we must assume that the customer has changed the way they relate to the industry. To a greater or lesser extent, today’s customer uses mobile technologies, spends much less time in their office, and is a connected customer. On a commercial level the predominant trend is the omnichannel or multi-channel client in which we want the shopping experience to be similar by any of the channels youuse. This poses a challenge in terms of production flexibility and ability to adapt to rapidly changing demand. Going back to the example of the automobile, manufacturers must launch new models every year if they do not want to miss the innovation train, something unthinkable 20 or 30 years ago.

Therefore, the technological evolution of industrial production must adapt to these new requirements, and can only be done competitively if it incorporates technologies that take this flexibility into account. These technologies are as follows:

• Advanced sensorization. For a smart factory to work, it must have a set of sensors at every step of the production process, providing real-time information and even inspecting both the product and machinery to detect faults and correct them non-stop on production lines. We’re talking about the  Internet of  Things (IoT). A system in which the machines themselves dialogue with each other constantly while generating a flow of data that allows an advanced degree of monitoring and control. We are not only talking about traditional robots, but also  autonomous systemsconnected to the factory but with individualdecision-making capabilities.
• Interoperability and commonlanguages. Components of an IoT network in one or more factories (which may be located in different locations) must have a common communication standard that enables dialogue and data delivery efficiently. The coexistence of different standards and protocols for communication and data management tends to create “watertight compartments” within companies that are sources of inefficiency and loss of productivity.
• Cybersecurity. A smart factory necessarily has to have advanced cybersecurity and backup systems, as well as adequate risk coverage, to ensure the continuity of operations in the face of a computer attack. Let’s not forget that 80% of attacks target companies.
• Big Data and Artificial Intelligence. The large amount of data generated requires adequate processing and exploitation. Big Data technologies and the application of Artificial Intelligence algorithms allow company managers to have all the information they need at all times without having to ask for it.  Artificial Intelligence is one of the keys to the flexibilization of production,sincethe factory can adapt on its own to the productive circumstances of each moment, from the generation of orders to suppliers (or the choice between several different suppliers) to the maximum optimization of the production process and logistics control.
• 3D modeling andsimulation. Virtual Reality and Augmented Reality are necessary technologies so that all this amount of data can be viewed intuitively and in real time. For this,  the creation of a digital factory twin is a key tool, because it allows to overlay to reality the necessary data (in case of using Augmented Reality) or dive directly into a digital model (Virtual Reality) with which you can interact naturally, without having to sit on a keyboard or have great engineering knowledge. In addition, digital twins allow simulations of different scenarios using real data, which takes us from forensic analysis (things that have already happened and cannot change) to predictive analysis (things that are going to happen and that we have to adapt to). Similarly, digital twins are an invaluable tool for optimizing investments in new machinery, expansions and even new factories.

Yes, but this whole smart factory thing is the future. Or not?

Not at all. All of these technologies are already working and are operational in many factories. We are talking about present, here and now, of a train that no industry should lose. Obviously, each company will require a different degree of digitization, but the digital transformation of companies is cross-cutting across all sectors. Companies have to be digitized because the customer has already done so.  In addition, it is the only way to deal with productivity improvement (we are talking about an average of 20% of the income statement) that a large number of industries need to face already if they want to continue competing in the market.

If digitization affects all sectors of society, obviously the productive sector cannot stay out. In fact, the European countries with the highest degree of robotisation and industrial digitization (as is the case in Germany) have created the most jobs in recent years and those that endured the crisis most robustly. The figures show that it is not true that robotization destroys jobs, but transforms them and, in fact, creates net employment. The train is at the station and they have already announced their departure, it’s time to get on it.