The data gathered through interviews, sectorial documents, and reports revealed essential insights about the scenario for Industry 4.0 in the Brazilian sugarcane sector.
Initially discussed, the need for technology and interconnectedness in the sugarcane sector causes numerous losses and efficiency reduction. The production variables are centralised in the controllers, with the objective of operational control. However, they are not interconnected. For example, when there is a load reduction in the grind, the ground power continues at its maximum level, reducing energy efficiency. If a truck has problems during transportation, humidity gets higher, and there is a direct impact on the production process of cogeneration. When there is contamination in the production process, the chemical results from the laboratory can take a long to be ready, reducing the production efficiency and promoting losses and high CO2 emissions.
For instance, meteorological data influences the field and grind, and if in real-time, can promote a better decision about harvest and production. The connection between suppliers, the actual time consumption and the operation, can guarantee efficient process analysis and production with no loss. With the field interconnected with the plant, the industry can have all the supply chain information, internal to the industry and external - from suppliers, government, climate, and market, allowing intelligent decision-making. One of the interviewees pointed out that the production process can be simulated using market and consumption information, allowing the industry to produce efficiently.
For the specialists, the digital transformation in the sugarcane production system promotes cost and energy reduction, safety improvement, despair reduction, errors and risk reduction, business transparency, improvement in quality and scale personalisation. All these will guarantee a more agile process of decision-making, the reduction of operational processes, events anticipation, and optimisation. The interviewees also mentioned the importance of asset management for maintenance, using asset prognosis and intelligent optimisation with all the related equipment.
Digitising the production process demands understanding the whole system (Fig. 1). One of the interviewees related the importance of understanding the concept of Industry 4.0 to start a transition process of implementing it. The first step, they affirm, is the convergence between automation and information technology.
The sugarcane industry has a complex production system that generates various wastes and by-products whilst producing ethanol, sugar, and electricity. Many innovations and technologies are arising to digitise the sugarcane industry, such as IoT, Internet of Things, Cybersecurity, Cloud Computing, and Big Data, besides the enabling technologies that accelerate the process of digitisation, such as Drones, Cobos, Machine Learning, 3D Printing, Augmented Reality, Virtual Reality, Digital Twins, among others, remembering that these technologies are dynamic, and they are constantly evolving and changing. In this new scenario, data is a valuable product and an essential foundation for the farm and agro-industrial industry (Hernandes et al. 2021).
One of these technologies is Process Analytical Technology (PAT) (FDA 2004). The technology is considered a standard and systemic solution, so much so that it came from the pharmaceutical industry and is widely accepted in the sugarcane sector. PAT consists of applying a continuous real-time analysis of manufacturing processes using mathematical modelling to monitor critical chemical and physical quality attributes (FDA 2004). In the first phase, PAT provides a framework for designing, analysing and controlling manufacturing in real-time through raw material analysis and critical process steps to ensure the desired quality of the final product. It can be applied in chemical, regulatory, and production. PAT has grown in the last few decades, driven by the need to improve manufacturing productivity across all industries (Wiley 2010).
This knowledge-based approach allows a better understanding of the manufacturing process, new technologies, data analysis, and real-time monitoring, ensuring that each process is sufficiently known to enable its improvement by identifying sources of variability.
The real-time optimisation process, the creation of a data history, pre-programmed actions in the process equipment, and validated actions through models that predict the impact of each parameter on the quality of the product or by-product result in a cycle of the PAT system (FDA 2004) running seamlessly with the industry's intelligent manufacturing model 4.0.
Digital transformation has proved to be a positive reality for the sugarcane-energy industry sector development. However, significant challenges must be addressed, such as cybersecurity, legislation adaptation, the dependence on capital and government, and the need for more professionals to operate in a new paradigm.
It was possible to understand that specialists see the implementation of Industry 4.0 in the sugarcane industry as a convergence of automation and information technology. It is an interconnection between the value chain (information, people, and equipment). According to one of the interviewees, “[…] it is a glance at the future. The industry will no longer respond to "What is happening?" or "Why is it happening?". It will also respond, "What will happen?". Today, industrial plants are reactive, responding to events after they happen. In the 4.0 industry, they will respond in advance in a structured and analysed form.” The sugarcane industry 4.0 is a process of understanding using IoT and measurement for learning behaviours through artificial intelligence and big data and predicting by anticipating events.
The complete digital transformation will enable the dissemination of large amounts of information about consumer demands; the market value for sugar, ethanol, and energy; climate data; interconnected laboratories for analysis and control; connected instruments, maintenance, and intelligent optimisation; online characteristics of industrial inputs and agriculture information related to the industry. The interconnectivity of Industry 4.0 in the sugarcane production system relies on a service-oriented architecture, all connected in the plant, with external and internal stored data in an extensive database. Big Data analytics use the information within a cognitive system that learns from AI to make the best decisions for the market, simulated by virtualisation.
Moreover, one of the specialists summarises, “The main challenge is to identify which technologies will allow the sector to obtain fast returns in terms of interoperability between several different IT working simultaneously. The internet connection and network infrastructure are still barriers to overcome with new business models. When integrating the field with the industry, tracking and monitoring systems for the agricultural and transport fleets can generate good operational and logistical gains, but everything depends on connectivity”.
Taking as a whole, one of the aspects that reflects the technology gap Brazil suffers is based on the quality of the educational systems and the difficult access of most of the population to high levels of education, especially in technology-based sciences.
Another aspect is the economic and political instability of the country. International currencies are free for variation, causing severe price oscillations in the sector. Also, Brazil has been through political crises. Brazilian public banks can finance production investments, but these financial lines are separate from innovation agencies such as Funding Authority for Studies and Projects (Finep). The Brazilian Agricultural Research Corporation is an excellent example of an effective service for providing new technology for the sector. However, it has an agricultural approach and needs to address the industrial production process. Fiscal incentives are above what the industry requires and are geographically concentrated in state policy more than federal policy.
When asked about the current technology status in the sector, specialists affirm that, in general terms, the sector could be ahead. They explain that the sector comprises big and small companies competing at different levels of supply chain maturity. Big companies of multinational groups are investing in specific solutions, whereas small businesses are still fulfilling the law of the mechanised harvest. This phenomenon begins from environmental issues to technology challenges.
Raízen, one major player in this sector, developed an innovation hub connecting startups that can test their prototypes inside the company. Some pilot projects are already employed in the mills of the company. The production engineer emphasises that one innovation from this hub created different forms of artificial intelligence to improve the boiler control and readjust the best operating point in cogeneration, which allowed to optimise the entire process. Another example is São Martinho, which elaborated its 4G network connecting all fields and mills' geographical points. This connection provided real-time access to harvesters in the field, increasing productivity through prompt control in the mill and allows preventing maintenance of any electronic component. Before that, they had to wait for the harvester to return to the industry where a pen drive was used.
Some companies are using AI combined with satellite data to provide new forms of soil evaluation and correction of fertilising formulas with high precision. Even to prevent fire, AI can be used. A company is developing an algorithm that detects smoke and alarms the closest fire station. However, despite using AI in many processes, agriculture equipment must still be connected to the industry. This is an essential step for the implementation of Industry 4.0.
Besides many sugarcane industries using technological advances towards intelligent manufacturing, there is a significant disparity in the sector, with companies ahead in implementing Industry 4.0 investing in specific solutions and companies far away from innovations and technology investments still fulfilling the mechanised harvest law. Using artificial intelligence for decision-making may promote cost and energy reduction, safety improvement, despair reduction, errors and risk reduction, business transparency, improvement in quality and scale personalisation. However, significant challenges need to be addressed, such as cybersecurity, legislation adaptation, the dependence on capital and government, and the need for more professionals to operate in this new paradigm.
The sector combines doubts about the effectiveness of new technologies and the need for more qualifications for their technology development and solutions, implicating an explicit constraint.
The concept "Usina 4.0" turns into the possibility of the creation of an industrial environment where the plant will be connected in a dynamic information environment, with data that maintains the entire production process connected, from the farm to the industry, exchanging information during the entire process, allowing an outlet of decisions about cutting and production by analysing the process and eliminating all order of waste.
The interconnectivity of Industry 4.0 in the sugarcane production system relies on a service-oriented architecture, all connected in the plant, with external and internal stored data within a cognitive system that learns from AI to make the best decisions for the market through Big Data. In brief, digital transformation will enable the dissemination of large amounts of information about consumer demands, the market value for sugar, ethanol, and energy; climate data, interconnected laboratories for analysis and control, connected instruments, maintenance, and intelligent optimisation; online characteristics of industrial inputs and agriculture information related to the industry.