The shift didn’t happen overnight, and by now it is irreversible. Hungary’s market-leading milling company, GoodMills, processes around 320,000 tons of grain each year. The control centre of a modern milling plant – and often its individual sites – can look more like a software company than an industrial hall. The difference is that here, system downtime doesn’t just mean a frozen computer; it can halt a production line and turn tons of flour into waste. The reliability of digital systems and uninterrupted connectivity are therefore critical to a mill’s operation.
The story of a digitized mill: GoodMills (click for video)
The network has become the new infrastructure
In long-established industries like milling, one of the most critical – though less visible – elements of digitization is the data network. Mills typically operate outside busy city centres, and thick concrete walls, steel structures, and geographic location can all reduce the effectiveness of solutions that rely on traditional Wi-Fi connectivity. That’s why industrial operators are turning to so-called SD-WAN-based solutions, which can manage multiple network connections simultaneously and automatically switch to the more stable option in the event of an outage – without disrupting production.
For such solutions to be effective, however, the mobile network must be fast and reliable – especially in the areas where the plants are located. According to publicly available data collected by the measurement vehicles of the National Media and Infocommunications Authority (NMHH) and published on szelessav.net, Yettel currently provides the highest average download speeds among Hungary’s mobile networks. Its network ensures nationwide connectivity for GoodMills’ sites in Baja, Komárom, and Tiszapalkonya, as well as at the company’s headquarters in Budaörs.
Data as the new raw material for the milling industry
The business rationale behind digitalization in industry is the same as elsewhere: the sooner a company can access the data generated during production, the sooner it can analyse it, act on it, and make decisions to operate more efficiently.
In a mill, for example, if the quality control system signals in real time that the moisture content of a shipment exceeds a specific limit, intervention must also occur in real time. The same applies to predictive maintenance: machine sensors send alerts when the system detects an anomaly, allowing operators to react before a malfunction brings production to a halt. For this to work, data must not only be generated but must also reach the right place – quickly, securely, and without interruption.
Grain still forms the basis of flour, but keeping the process efficient, safe, and competitive now depends on the network on which the entire system relies.