Net zero for the dairy industry – GEA and OmegaLambdaTec are adopting new approaches

Thomas Jackson: Data science solutions, particularly AI algorithms, have two major advantages compared to a purely human approach: firstly, vast amounts of data can be processed quickly and efficiently and, secondly, such approaches can also be used to easily determine relations and patterns and use them profitably. These would barely be recognisable using visual or classic methods. This not only offers us familiar and obvious suggestions for improved resource efficiency on an industrial scale, but also enables us to identify possible, entirely new approaches and methods for saving resources.

Thomas Jackson: Climate change and the related need to live and work sustainably and with zero CO2 emissions are becoming an increasingly important issue for our society. Many customers – including myself – are increasingly paying attention to the ecological footprint of products when making purchases. Use of the latest AI technologies is now offering the food industry great potential for taking a further, significant step forwards in continuing to reduce this footprint. Specifically evaluating large volumes of data with accordingly trained algorithms enables better or even optimum decisions to be made in order to make production more sustainable. Since the requirements and framework conditions of every farm, every dairy and every production site differ, an AI solution has to be very flexible and scalable at the same time – and that is precisely what we are working on.

Christian Becker: With regard to specific resources, using water economically poses a major challenge in milk processing and is closely interlinked with operational processes. Water is indispensable throughout production, particularly for cleaning, but also for cooling machines. This dependence inevitably leads to high volumes of waste water that are contaminated with organic and inorganic substances and chemical residues. The challenge is to minimise fresh water consumption and the volumes of waste water as far as possible without compromising productivity, product safety or system availability.

Thomas Jackson: Our data science team has already implemented over 200 smart data solutions and that is exactly what we are building on, although the food industry is more of a new application area for us. Our algorithm portfolio offers a high number of the necessary solution components that we have developed with and for other partners and customers in the past. They are pretty much ready to be implemented. These include, for instance, the detailed modelling and simulation of drinking water cycles, long-term simulations of ecological footprint scenarios, optimisation procedures for calculating optimum resource efficiency, data-driven real-time monitoring of production systems and the identification of cost-optimised expansion scenarios.

Christian Becker: GEA’s portfolio has actually included resource-efficient solutions for the dairy industry for a number of years, because our company’s mission statement has long since been ‘Engineering for a better world’. However, the current societal and political focus is lending our quest to achieve more sustainable solutions additional impetus. Sustainability is part of our growth strategy, which is why both our technology portfolio and our innovation pipeline are bursting with practicable and sustainable solutions.

For instance, we have established the Add Better label; it calls attention to GEA solutions that are significantly better than their predecessors when it comes to efficiency and environmental impact. This not only involves energy efficiency, but also fewer emissions and lower water and raw material consumption. In each case, the eco-label is awarded on the basis of data, determined according to a proven ISO calculation method and validated by TÜV Rheinland. Add Better is an important element in GEA’s efforts to reduce our greenhouse gas emissions along the entire value chain to net zero by 2040.

Georg Munde: The dairy industry needs to prioritise strategic water management that meets immediate operational requirements and incorporates long-term sustainability considerations at the same time. The will to implement such a fundamental procedure is noticeably increasing, both because water and waste water costs are increasing and because sustainable practices for dairies are shifting into focus – safeguarding their future viability, so to speak.

Transparency regarding highly-complex dairy operations is immensely important in order to methodically save water and keep process water in circulation, and we still have a great deal to do in this respect. This is also the objective of our challenge for the start-ups: we want to think beyond conventional technical methods (such as reverse osmosis systems and saving water in separators, etc.) and provide a comprehensive overview of the water footprint of a dairy. The objective is to equip companies with the knowledge that they need in order to make decisions. This is not only concerned with saving water, but with fostering sustainable water management per se. This is why we are working on a dynamic ‘water stress map’ that continuously monitors the production process and optimises water consumption. To do this, we have to define KPIs (key performance indicators) and compare them against the system’s current data. These are used to generate decision-making knowledge, action recommendations and, depending on the maturity of the AI, also self-optimisations.

Sensors are able to supply the majority of data for an overview of the system. This is already technically feasible for dairies today. Of course, it’s an investment decision if sensors need to be retrofitted. The willingness to make this data available for processing is a clear factor for success in sustainable optimisation. Digitalisation is a common task for operators and manufacturers.

Thomas Jackson: Compared to other industries, there is still a lack of data and its long-term storage, not only in small dairies with numerous manual processes, but also in large dairies with automated machines. The management of water, electricity and other resources is still controlled either by hand or with less intelligent classic software. Particularly where large companies are concerned, this is no longer efficient and, above all, it does not exploit the potential offered by good data. At present, however, the data is often not consistent, the evaluation methods (if there are any) are slow and optimum data-based decisions are therefore rare and only possible with a time lag. In order to achieve more ambitious goals by means of informed decisions, such as GEA’s drinking water saving goals, for instance, we urgently need new, innovative solutions, which we will now be implementing together.

Christian Becker: Digitalisation and AI are indeed powerful catalysts for productivity, efficiency and sustainability in industry. At GEA, we are using these technologies to design our machines and systems more intelligently. At present, artificial intelligence is enabling our customers to use their machines optimally and to meet challenges such as the lack of skilled workers, intensive competition and more stringent climate and environmental regulations.

In the future, we anticipate that data connectivity will increase, causal relationships will increasingly be revealed and production facilities will adapt themselves ever more intelligently. The extent to which a dairy can operate autonomously will depend more on the corporate and industry culture than on the technological possibilities. However, dairy experts will continue to make decisions based on their experience. AI is already having an enormous influence on the pace and quality of innovations. We therefore consider it advisable to use successful examples from other industries for orientation.

Georg Munde: The combination of technical expertise, an innovative approach and a convincing presentation helped OmegaLambdaTec to secure their win. We were convinced by the method of visualising a water stress map that enables complex data to be presented in a visually appealing and accessible manner. The jury was bowled over by how the complex data volumes are analysed and handled. The scalability of the technology was an additional factor. OmegaLambdaTec demonstrated that their solution also has the potential to tackle broader challenges in fresh water management. The idea of predicting the influence of various water saving measures in the form of scenarios on the water stress map almost certainly offers particular opportunities.

OmegaLambdaTec can now continue to expand their solution, firstly in a practical environment with extensive market potential, and secondly with GEA, an extraordinarily diverse and experienced company that is a world leader in dairy equipment. This practical link is very important for digital solutions and is often underestimated. We are now working closely together to produce a real water stress map. A pilot project will help us to test and find out under real conditions what can be done even better. Our cooperation is intended to be long-term, and we believe there is a good likelihood of its leading to even more projects and enabling OmegaLambdaTec to continue growing on the market.

Thomas Jackson:The first main objective in tandem with GEA is to simulate possible approaches to achieving net zero drinking water consumption for dairy production systems, to identify critical process components, to show potential improvements in the simulation and to determine the most efficient, cost-optimised ways of achieving net zero consumption by means of large-scale optimisation processes. A similar approach can also be used to significantly reduce energy consumption, particularly electricity costs, by exploiting flexibilities, buffering inexpensive electricity in batteries and capping load peaks, for instance.

The carbon footprint and the long-term shift towards climate neutrality can also be mapped, simulated and optimised using data. Many of these applications involve the concept of digital twins of production systems, processes and even entire companies. This enables any number of future scenarios to be computed and, for instance, long-term investment decisions to be optimised long before any money has been spent on new hardware. With these approaches, dairies can achieve their climate goals either as quickly or as cost-efficiently as possible.

AQUARiUS, our GEA solution, is intended for the simulation and long-term, optimised planning of systems. By implementing digital twins of entire dairies, the future could also see real-time process control optimisation and the holistic maximisation of production quality and resource efficiency. As I have already mentioned, however, this is still something of a pipe dream. What can be implemented significantly faster is the use of long-term AQUARiUS scenario simulations in order to significantly improve planning and decision-making bases. This then enables GEA to quickly and actively support customers in making their production systems more sustainable and resource-efficient.

Thomas Jackson: 10 years in the AI environment are around five complete innovation cycles, in which a vast number of new possibilities and solutions will be launched onto the market. On the other hand, 10 years is not a long period of time for major system investments, which means that the discrepancies between the most modern dairies, average systems and innovation stragglers will continue to increase. Dairies that use these innovation potentials correctly and invest intelligently may possibly succeed in securing enormous competitive advantages. On the other hand, those that wait too long and continue to produce pretty much as they did in the last century will face massive business problems as of a certain point during this period of time – at the latest when consumers across the board demand sustainable and climate-neutral production.

OmegaLambdaTec GmbH
Manuela Pehle, Marketing Manager
manuela.pehle@olt-dss.com
T +49 151 292 662 66
https://omegalambdatec.com

GEA Group Aktiengesellschaft
Fanny Förster, Media Relations
pr@gea.com
gea.com