{"id":9697,"date":"2021-05-13T07:09:12","date_gmt":"2021-05-13T07:09:12","guid":{"rendered":"https:\/\/hightechsoftwarecluster.nl\/?p=9697"},"modified":"2021-09-28T18:25:03","modified_gmt":"2021-09-28T16:25:03","slug":"data-driven-malting-helps-holland-malt-reduce-its-ecological-footprint","status":"publish","type":"post","link":"https:\/\/hightechsoftwarecluster.nl\/en\/digitalization\/industrial-digitalisations-en\/data-driven-malting-helps-holland-malt-reduce-its-ecological-footprint\/","title":{"rendered":"Data-driven malting helps Holland Malt reduce its ecological footprint"},"content":{"rendered":"\t\t
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Home<\/a><\/span><\/span><\/p>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Data-driven malting helps Holland Malt reduce its ecological footprint<\/h1>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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\n\t\t\t\t\t\t\tBy turning down the heat in the kiln a mere 1 percent, Holland Malt can save enough electricity to power a small village for a year. Data science and modeling are aiding the malthouse in reducing its ecological footprint.\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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IN SHORT<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\tData Science supports technology experts in an objective data-driven quantification on the impacting factors on their production process.\t\t\t\t\t<\/p>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\tControl on the production process enables energy reduction, which reduces costs and also benefits the ecological footprint.\t\t\t\t\t<\/p>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\tDry runs of the model show very promising results, enabling heat change experiments to accomplish the energy reduction goal.\t\t\t\t\t<\/p>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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You can\u2019t brew beer without malt. This key ingredient is made from grain such as barley. When the grain arrives at the malthouse, it first gets cleaned to remove dust and other foreign matter. It\u2019s then covered on and off with water for a day to increase its moisture level to 40-45 percent. This so-called steeping initiates germination in the grain, causing the breakdown of cell walls and the development of enzymes that turn the starch into the sugars needed to form the alcohol. After five days, the resulting green malt is moved to a kiln, where it\u2019s dried to reduce the moisture level to under 5 percent. This effectively halts the germination and prepares the malt for brewing.<\/p>

\u201cA kiln is a very large oven,\u201d explains Martijn van Iersel, Manager Quality & Technology at the Lieshout-based malthouse Holland Malt. \u201cThe green malt is spread out over the floor and large volumes of warm, dry air are blown across by big heaters. As the air passes, it cools off, releasing heat and taking up some of the moist from the grains. For every batch, we have 20-22 hours to complete the drying process and get the malt ready in time for transport to the customer, the brewery.\u201d<\/p>

One of Holland Malt\u2019s biggest customers is its parent company, Swinkels Family Brewers, co-located in Lieshout and best known for the Bavaria brand. \u201cWhen you compare all the processes in a malthouse, kilning is the most energy consuming,\u201d says Pieter Meeuws, Business Intelligence & Reporting Analist at Swinkels. \u201cValuing our commitment to corporate social responsibility and building on our growing data science competency, we decided to see whether we could lower the electricity bill using a data-driven approach. A mere reduction of 1 percent would already save enough energy to power a small village like Lieshout for a year.\u201d<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\u201cValuing our commitment to corporate social responsibility and building on our growing data science competency, we decided to see whether we could lower the electricity bill using a data-driven approach. A mere reduction of 1 percent would already save enough energy to power a small village like Lieshout for a year.\u201d\t\t\t<\/p>\n\t\t\t\t\t\t\t

\n\t\t\t\t\t\t\t\t\t\t\tPieter Meeuws, business intelligence & reporting-analist bij Swinkels<\/cite>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/blockquote>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Turn the dials<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Carrying forward their standing relationship, Swinkels turned to the data science consultants from Bright Cape for assistance. \u201cWe did a project with them in Ethiopia,\u201d gives Meeuws an example of their earlier collaboration. \u201cAfter we set up a greenfield brewery there, they helped us run a successful data-driven marketing campaign to best promote our new beer. When we contacted them on behalf of Holland Malt, they supported us again with their data science expertise.\u201d For Bright Cape, located in Amsterdam and Eindhoven, the Holland Malt project aligns nicely with its focal areas. \u201cWe develop advanced data science solutions, going from exploration to user experience,\u201d elaborates senior data scientist Daphne van Leeuwen. \u201cWe\u2019re mainly active in finance, logistics and manufacturing, with an increasing focus on sustainability.\u201d The project also resonates with the efficiency and sustainability objectives of the High Tech Software Cluster, which brings together Bright Cape and other software specialists to combine, promote and apply Dutch software excellence on a worldwide stage.<\/p>

Collaborators\u2019 goal was to kiln a batch of malt within the required timeframe of 20-22 hours, delivering the same high quality while using as little energy as possible. \u201cHaving varying grain sizes and shapes, different types of barley have different inherent moisture levels and therefore take different times to dry. The conditions outside the oven also play an important role. When the humidity is low, in winter for instance, some batches may already be ready in 15 hours,\u201d describes Van Iersel. \u201cUntil recently, we set the heaters to full power, irrespective of the conditions. However, if we were to turn down the heat a little so that the same batch would take 20 hours to dry, we would still be within the set boundaries and we would have used less energy.\u201d<\/p>

\u201cHolland Malt already had a lot of impact variables readily available, such as the humidity and the temperature in the kiln, the shape and size of the barley and the layer thickness of the green malt,\u201d continues Van Leeuwen. \u201cWe processed that data, combined it with external factors like the outdoor humidity and temperature and put everything in a model that, given a set of preconditions, predicts as accurately as possible the time it takes to complete a batch. Holland Malt can use this prediction to turn the oven dials, giving them new data with which they can improve the model and get an even better prediction.\u201d<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\u201cWe\u2019re seeing some very promising results, confirming that the model can indeed correctly predict the kilning time. We\u2019re nearing the point where, under the right circumstances, we could turn the heat down a notch and actually start saving energy. Currently, we\u2019re still tweaking manually. Ultimately, of course, we\u2019re gunning for a self-correcting model.\u201d\t\t\t<\/p>\n\t\t\t\t\t<\/blockquote>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Dry runs<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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The project started in February of last year and finished this January. Holland Malt is now doing extensive dry runs. Van Iersel: \u201cWe\u2019re seeing some very promising results, confirming that the model can indeed correctly predict the kilning time. We\u2019re nearing the point where, under the right circumstances, we could turn the heat down a notch and actually start saving energy. Currently, we\u2019re still tweaking manually. Ultimately, of course, we\u2019re gunning for a self-correcting model.\u201d<\/p>

\u201cWe\u2019re also looking to see if we can optimize multiple kilns at the same time,\u201d adds Meeuws. \u201cHolland Malt has four and we\u2019re exploring if we can cascade them in such a way that we can reuse their residual heat more efficiently. It\u2019s all about how to make the best use of the model, how to benefit best from having a better grip on the process.\u201d<\/p>

The project has opened Van Iersel\u2019s eyes to the opportunities of data science and modeling: \u201cIt\u2019s really remarkable what you can achieve.\u201d For Meeuws, it was a confirmation that you can never have enough data: \u201cHolland Malt already recorded a lot, but the project showed us that we still had some blind spots. So, even if you don\u2019t yet know what you\u2019re going to need it for, collect as much process data as you can.\u201d<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\tA successful implementation of data science stands or falls with business adoption, therefore, involving technologists and decision-makers from start to end is key.\t\t\t\t\t<\/p>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\tStart small, deliver well \u2013 it is important to carefully scope your use case at the start and align extensively with the experts to understand their needs.\t\t\t\t\t<\/p>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Bright Cape makes data accessible for everyone. Not just insight, but a practical solution that immediately adds value. Bright Cape provides the insight and the solution. We always do this together with our client as one team.<\/p>\n\t\t\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\tSee Company\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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