After a big data lecture by Professor Dr. Bayu Jayawardhana of the University of Groningen, the managers experience a high-tech safari to YP Your Partner and BD Kiestra.
How do we handle data? And what can our data do for our customers? Host Klaas Jan Hutten, Director of Industry at ING, succinctly gives his disconcerting answers. ,,We can predict how his business is doing before the entrepreneur does. And we can tell from our customers’ surfing behavior, for example, that they are tense about the development of their investment portfolio.’’ Algorithms appear to be the magic word. According to Hutten, business models and the development of cost prices are going to change drastically. ’’We are living in a fantastic period,’’ he jubilates, ’'but the supply of raw materials and the influx of personnel are pinching in more and more places. This is a signal that economic growth will slow down.'' That's why Hutten advises the industry to get your business ready for the future right now. ''This period of cash is ideally suited to go through the transition.''
Flintstone
According to Professor Jayawardhana, this transition can only be made if communication between industry and knowledge institutions is optimal. ’’Without further knowledge of the possibilities of interpreting and using data, the industry misses the connection with the latest developments. Then China will have caught up with us in no time.'' This sounds a little threatening from the professor's mouth, and perhaps it is meant that way a little. If we don't innovate, we will miss the boat. As an example of this intertwining of knowledge institution and industry, he shows the project Ocean Grazer, of which he is the co-founder. ’’With this project, we answer the growing demand for renewable energy and show how you can make big data work for you.’’ Using Fred Flinstone as an example, the professor shows how in prehistory and later big data, the information present in the environment was already interpreted. ‘’Starry skies allowed people to navigate and weather forecasts could be made from nature.’’ We now have this kind of "prior knowledge" thanks to our data streams. ''It is important that we learn to interpret the data properly and then link it to our production processes, for example, in combination with smart software, sensors and cameras. The result is predictive maintenance and thus the extension of machine life.''
machine learning
That is exactly what Theun Prins, owner of YP Your Partner, does. He extracts data from processes and machines and visualizes it so that users can draw conclusions from it with their knowledge and experience. ,,If you see 24 degrees you don't know anything yet. But if you see it in the hospital on a display next to a patient's bed and it's about body temperature, you know this is not good. You can't do anything with just the data, you need the environment and knowledge to interpret it correctly to be able to use it.’’ Prins develops remote process and machine control for customers. He calls it remote monitoring. ‘’Not only do we increase the uptime of machines and installations with our systems, but thanks to ’machine learning’ our customers now know, for example, exactly when parts need replacing so they don't have to perform maintenance any sooner than necessary.’’ Prins knows the value of context information, but notes that most companies are not yet using it to make their machines smarter. ''That's why people are still necessary to interpret information.'' According to Prins, it won't be long before machines interpret context themselves.
Smart collaboration
Everyone knows that product life cycles are getting shorter, market demands are increasing and margins are shrinking. The ‘time to market’ is more important than ever. ,,We currently already connect more than 50 thousand systems and installations with our C.A.R.S. software objects and convert the data into valuable information. This is how we create value from data that leads to action, such as energy savings, predictive maintenance or knowing everything about your processes.’’ The path to success with data, according to Prins, is sensoring, connectivity, collection, analysis and action. Again, another resounding example, the banana ripening machine from high tech partner VDH Products from Roden. Within two years, this product has been sold in 25 countries. The key to success? Open communication about job requirements and opportunities. ,,That is crucial, trust in each other, working together and recognizing that there are more smart people working outside your company than inside your company. So, data in the cloud complemented by knowledge is the success ‘to make or save money.’
Bacteria
BD Kiestra is using big data very differently. They use data combined with knowledge and environmental factors to save lives. ’’With our system, doctors can determine within 24 hours what bacteria made someone sick and what antibiotic should be given.’’ Jan Lucas, manager of R&D at BD Kiestra, says that less than a decade ago this process took more than five days. ’’What we do is important work. We have drastically reduced the examination time and doctors can also give the right antibiotic with certainty, this way unnecessary resistance is also prevented.’’ Lucas explains that worldwide the number of trained microbiologists is insufficient to staff all laboratories. ’’The demand for automation is strongly increasing because of this.’’ Laboratories, he says, spend half their time ruling out disease. ’'With our system, we add value by not only ruling out, but also by naming what is there. This allows us to determine which antibiotic is needed and really helps doctors in their work.'' The lab machines do this by taking images in a time series in different light waves and colors. An algorithm uses different aspects to then determine which bacteria are growing. ''In addition, we use big data to optimize the clinical outcome.'' This is exactly what BD Kiestra's founder had in mind when he entered the hospital in the 1990s. There, he remained uncertain about his diagnosis for a long time because all the research was done manually. So the ultimate dream of BD Kiestra, according to Lucas, is to bring together all the images and results of all customers worldwide. ''From this, our algorithms learn and we can not only quickly determine which bacteria are growing, but also whether a new bacteria is growing.''
Industry top
The High Tech Safari Industry Northern Netherlands is organized annually by ING, FME and Innovatiecluster Drachten. The goal is to raise awareness among Northern businesses about the very rapid development of industry toward smart factories and the determining influence of digitization in production, operations and sales.