Miller Magazine Issue: 123 March 2020

57 COVER STORY MILLER / MARCH 2020 able, and every teenager can take a MOOC course from a top foreign university without having to wait for their local technical college, these technologies of the Fourth Industrial Revolution are spreading. All these innovations have the same common goal: to achieve strong customization under the conditions of mass production. It will be done using: self-optimization, self-configuration, self-diagnosis, cognition and intelligent support of workers. The design principles that guide Industry 4.0 are: • Interconnection: Machine to machine, people to peo- ple, and machine to people. • Transparency: Huge volumes of information (collect- ed from the system) are readily available across the whole system. • Technical assistance: The systems are designed to as- sist human beings in boring or dangerous tasks, but it is also devised so the human operator becomes a “consul- tant” of the system, providing orientation to the artificial intelligence. • Decentralization: The systems make decisions on their own. This also means a paradigm shift, because you can’t (from a practical point of view) provide independence to machines and at the same time micro-manage people. Or- ganizations will become flatter and more flexible. The keys of the future mill are the high adaptability and rapid design changes. The customization of small batches of flours according to grain quality and consumer demands is only possible with a highly automated mill. A digital twin (software simulation that replicates a real process), fed with real-world variables, allows predicting the results of the real-world process. Most modern mills use a SCADA system to control what the factory is doing, to self-adjust the individual machines according to variations in the product (be it raw material, in process, or finished), and also to manually adjust parameters according to reci- pes. However, digital twins of process industries go one step ahead by creating what would be a fake SCADA that, after entering the parameters of the real world (even automat- ically) will tell you what happens at each stage of the pro- cess, to each variable, and the final results achieved. This isn’t something to be bought as a package, as it requires extensive programming to teach the twin how his brother behaves in every circumstance, but they are more accessible that you could imagine. Even though the machines used in milling are fairly sim- ple, if you consider the whole mill as a machine, with the different flows possible considered as robot operations, then the topic of robotics is applicable. It means that if one machine breaks down, the system can divert flows, change capacities, etc., in order to continue operation. This reactive capacity that usually required human intervention now is natural for any computerized system. It is even possible to program an Artificial Intelligence that learns from what happens in the mill and from our reactions to it. This is called Machine Learning . It means using patterns and in- ference (like a human would do) instead of specific instruc- tions. This technology has been able to achieve incredible things, like develop a new language from scratch. If you use Google Translate, for example, it is based on machine learn- ing. The AI behind it has developed a new language of its own as a bridge between all the languages it translates, just because it “felt easier”. The main focus of machine learning is optimization, according to the goals the user wishes. It is also closely related to Data Mining , which is the use of al- gorithms to discover patterns in the information provided to the computer. This could be used, for example, to discover the reasons behind quality fluctuations in the products or the causes of machinery failure. Another breakthrough, that is tied to customization, is using blockchain technology to trace every processing op- eration, from farm to table. A blockchain is created by the farmer, using certificates provided by reliable authorities, declaring that the grain comes from a specific part of his land and was grown under some specific conditions. For example, it could say the grain is GMO, drought-resistant wheat, grown in parcel 114 of his land, or coordinates such and such, and has certain qualities (weight, density, humidity, etc.). This information is passed to the elevator, which segregates or mixes batches according to qualities and demands, and generates another blockchain, contain- ing the information of the farmers involved, the processing involved for each batch (if it was dried, fumigated, stored for how long, etc.). Lastly, the miller does something simi- lar when manufacturing the flour, generating a blockchain with all the information of his process. In this way, the final consumer could read the blockchain in his 1 kg bag of flour and know all the process it went through, from farm to su- permarket. What blockchain will mean, essentially, is that a housewife will be able to scan a code in the package of flour at the supermarket and know its exact history. This will also require more segregation of grains and flours but will provide us with more information that we ever thought possible. A whole book could be written ex- plaining how blockchain works and how it currently applies and could apply to agriculture and milling. Workplace inefficiencies could be virtually eliminated by smart manufacturing, by allowing the continuous recording of all processes and machines, and implementing automatic actuators that regulate the variables of the processes. For example, grain mixtures can be adjusted, roll pressure in- creased, sifting time increased, etc. A network of sensors gives you real-time data, as much as you want, as long as each variable can be defined by a numerical variable. With the advancement of this technology, manual adjustments will have to disappear, being replaced by actuators that can control every aspect of the operation of the machines. For- get about the old supervisor that knows the machine by the sound it makes, but be prepared to pay big bucks to your supplier’s field service technician.