What makes the factory really smart

If we are to conform to the canonical definition, the smart factory or smart factory is a factory in which production processes are combined with digital technology. Using technologies and solutions such as Big Data, machine learning and predictive analytics, a more reliable, efficient and flexible ecosystem can be created. This is particularly true for the manufacturing sector, where the ability to combine the concreteness of production lines with the benefits of the most advanced digital has only been a reality for a few years.

The smart factory is one of the building blocks of Industry 4.0, since in a supply chain with a high rate of interoperability, machinery and production lines also need to be able to operate based on an increasingly timely and elaborate flow of data.

This definition, however, often generates an error of method when thinking about the smart factory in particular and the Industry 4.0 supply chain in general. That is, thinking that technological implementation is  sufficient as well as necessary condition. Instead, the technological transition to the smart factory often requires rethinking various strategic aspects of the business, especially in terms of production line management strategies, but not only.

• Connected data: at this stage, all machinery provides the necessary data and this data is collected in one source. Having all the data in one location is the first and critical step in enabling smoother analysis and more immediate troubleshooting.
• Predictive analytics: in the “second level,” the data collected begin to be used for proactive troubleshooting both at the production line level (predictive maintenance) and at the strategy level.
• Prescriptive analysis: having reached this point, the focus shifts more and more to the analytically based forecasting. Instead of predicting when breakdowns, production line problems or raw material shortages might occur, machine learning suggests optimized settings, based even on contingent data, to ensure maximum efficiency, the ideal production level and the best life cycle for machinery. An interesting aspect of this level is that, again according to Forbes, it is possible to distill into algorithms even  the experience of veteran staff for the benefit of future generations.
• Artificial intelligence-based automation: at the fourth and final level, artificial intelligence is used to make the entire decision-making line automated. For example, artificial intelligence algorithms can identify a production line optimization, generate the necessary settings and transmit them in real time to the machinery where they are applied. This is still a futuristic technology, and Forbes itself points out that in the current state of things, human supervision is recommended, but the benefits of this technology are indeed considerable, especially considering that they allow for  Devolve the most safety-hazardous operations entirely to machines.

People make a difference

Now that it is clear how smart factories change and will change the industry technologically, it is necessary to focus on what the real paradigm shift is. To simplify to the extreme, we could say that what makes a factory truly smart is the  level of trust in the data, which must be complementary to the technological solutions adopted.

Therefore, it is imperative that progress in terms of implementation be accompanied by a process of training and education on the use and importance of data. The ability to make data-driven decisions should be accepted and grasped by all levels of decision-making as an opportunity. In many cases this means creating friction with a range of customs, particularly in an ecosystem like Italy where there is considerable concentration of decision-making power on a limited number of business figures.

But just as it is necessary in production departments to convey the positive spillover effects on operations of data collection and management, it is necessary for the change of mindset to involve the entire company, following what is the basic principle of digital transformation: data and analysis tools are meant to Simplify people’s work, improve the quality of their engagement and take on the tasks that absorb the most time and effort without real added value. In short, to truly transform our manufacturing reality into a smart factory requires a change in mindset first.

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