It has been a decade since the Industry 4.0 concept was first introduced, yet only 15% of Czech and 10% of Slovak companies have implemented its principles. What is alarming is that 20% of Czech and 30% of Slovak companies have not even started to think about it, and that 5% of Czech and 8% of Slovak companies had considered these options but decided not to change anything.
The basic principles of the so-called Fourth Industrial Revolution – including digitalization and IoT – were first formulated in 2011. According to this idea, “smart factories” would emerge and utilize cyber-physical systems. Soitron, an integrator of innovative solutions and IoT technologies, conducted a survey to find out about the current stage of development among manufacturing companies in the Czech Republic and Slovakia.
The collected data shows that 58% of Czech and 51% of Slovak companies have either already implemented (or are currently implementing) elements of digitalization, IoT technology, and Industry 4.0 principles.
“In both markets, data from factories is most often collected automatically into a centralized system. Two-thirds of the surveyed companies do so. The second most common method is manual data collection whereby a technician walks around the machines and records data into a paper notebook or a computer,” explains Martin Hummel, an IoT solutions specialist and product manager at Soitron.
For more than three-quarters of companies (83% of Czech ones and 77% of Slovak ones), the main focus is on quantitative data used to manage productivity and manufacturing efficiency. Some Czech companies (32%) also use data for quality control and reject rate management, and some Slovak companies (33%) also use data for maintenance management and failure reduction.
Shortcomings in the way data is used or processed are perceived more often by Slovak companies (70%), with the Czech figure being a little more than half of all respondents (55%). Respondents in both countries most often mentioned that they saw room for improvement in terms of automation and digitalization and in having a centralized system (27% [CZ] vs 33% [SK]). Slovak respondents would also like to see more detailed and extensive data analyses and a general improvement in existing systems. Czech respondents, on the other hand, saw deficiencies in the speed of availability of outputs, i.e. the unavailability of real-time monitoring; they would also like to see better data collection and processing.
Maintenance planning in both countries (85% in the Czech Republic and 66% in Slovakia) is predominantly based on the recommendations of technology manufacturers and vendors. Then it is based on the judgment of the staff in charge (75% in the Czech Republic vs 44% in Slovakia), and only after that is it based on collecting and evaluating data from manufacturing, machines, and other sources. The future, however, lies primarily in the automated collection of data from sensors installed on manufacturing and assembly machines and equipment.
“For factories, the collected data is the most important and valuable source of information. Once processed by a data analysis or by machine learning procedures, this data can help companies predict impending failures and breakdowns. This enables operation specialists to make timely and correct decisions and to intervene as necessary and thus save significant costs,” adds Hummel.
If we look at downtime frequency, the survey shows that the Czech enterprises generally face slightly fewer unexpected downtimes (25%) than the Slovak ones (31%). The average cost of unexpected manufacturing downtime is more or less the same in both countries – it is 1.7 million Czech crowns in the Czech Republic and the equivalent of 1.5 million Czech crowns in Slovakia. It is important to realize that sometimes a malfunction causes the production line to stop and thus halt the whole production. A malfunction may take several hours to repair, which means that downtimes represent a significant financial loss to any company. The answer to this is predictive maintenance based on collected data that can provide an early warning of an impending failure.
The digitalization of production processes is still a major challenge for most Czech and Slovak industrial enterprises. “By deploying modern industrial IoT solutions, it is possible to continuously monitor and analyse operational parameters, production quality, and the manufacturing environment, and thus detect problems early and – in many cases – even predict impending failures and downtimes. Investing in IoT solutions in manufacturing clearly pays off,” says Hummel in conclusion.
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