Smart, transparent and sustainable food supply chains

The DigiMat project aims to exploit the possibilities of ICT and modern technologies in combination with logistics competence to develop more efficient Norwegian food supply chains. By developing smart planning and control we can increase the resource utilisation and reduce food waste - thereby increasing the sustainability of the food sector. Norwegian-owned food producers to a large degree compete by offering customers high-quality, branded and safe products at reasonable prices. The Norwegian companies compete against large international actors with global and efficient high-volume supply chains. To increase their competitiveness, Norwegian actors need to improve their ability to run operations efficiently. They need to be smarter than the competitors in meeting variable demand - with minimum resource consumption through the supply chain. In the DigiMat project, Brynild (project owner), Mills, H. I. Giørtz and Leman Norway have joined forces with PA Consulting, SICK, the leading IT suppliers Relex Solutions and BI Builders - and some of Scandinavia?s leading researchers on grocery, food supply chains and ICT at NTNU, Østfold University College and Aalborg University (Denmark). Together we are leveraging our expertise in ICT, emerging technologies, and logistics to create a smart, transparent and sustainable food supply chain in Norway. The project activities focus on three main topics. 1) Smart demand planning and production control With Industry 4.0 new technologies are emerging for collecting and sharing data from both production and supply chain operations. In the project we investigate how food processors can exploit this data for smart planning and control - by using machine learning and other advanced methods for analysis, simulation and visual decision support. By 'smart' we mean planning and control that is more dynamic, integrated and (near) real-time - where data is converted to information for decision support. In the project, we are therefore investigating how producers can use point-of-sales (POS) data from grocery stores to improve forecasts and production plans, particularly for product launches and campaigns. In addition, we are investigating how external data can be combined with internal data to dynamically adjust e.g., daily and weekly production plans and batch sizes. 2) Smart logistics in production and warehousing Despite the high degree of automation in food processing, there are still a lot of manual processes involved in handling and moving materials and goods. Mobile robots for automating picking in warehouses are emerging (see e.g., https://bit.ly/3Dfgon7). In DigiMat we therefore used machine learning to develop models for determining which product should be picked by robots and which should be picked by humans. The aim is to minimize the weight lifted by humans (and thereby avoid strain injuries) and simultaneously maximize the similarity of product categories picked in each zone to enable efficient warehouse picking and in-store stocking of shelves. We have also looked at how to dynamically assign storage locations to products to increase efficiency in warehouse operations, as well as how information from the supply chain can be used to make planning and control of all warehouse operations more dynamic and efficient. 3) Visual analytics for decision support To support decision making in the supply chain, data must be captured, shared and analysed. Using visual analytics, relevant information can be customised and presented to various types of decision makers in such a manner that it supports monitoring, diagnosis and decision making. As a starting point for this activity, we have identified relevant techniques and tactics for visual analytics and investigated how these can be used to support relevant logistics processes in supply chains. The consortium continuously disseminates news and results from the project. We have close collaboration with DLF - the association of Norwegian Grocery Suppliers, where results are communicated to DLF's more than 100 member companies through seminars, webinars and visits to NTNU?s Logistics 4.0 laboratory. Since the start of the project, we have organised four seminars/webinars and given 16 presentations at international, national and company workshops, seminars, and conferences. In 2021, three webinars each reached an average of 40 people in the project target group of producers and suppliers in the Norwegian fast moving consumer goods sector. In addition, since the start, the project has published nine scientific journal articles, one book chapter, one PhD thesis (not project funded), 19 master theses, and 14 other reports.

-

Brynild Gruppen, Mills and other Norwegian-owned food producers to a large degree compete by offering customers high-quality and safe brands at reasonable prices. Within the sugar confectionary and snacks segment, we in Brynild with our turnover of 706 mill. NOK (2017) compete against large international actors with global and efficient high-volume supply chains. To increase our competitiveness, we need to improve our ability to operate our supply chain effectively. We need to be smarter than our competitors in how we meet dynamic demand with minimum resource consumption. In this project, we have joined forces with our supply chain partners Mills and Leman Norway. In addition, we collaborate with PA Consulting, SICK and the leading ICT systems providers Relex Solutions, BI Builders, and DRIW, as well as some of Scandinavia’s leading researchers in retail and food supply chains at NTNU, Østfold University College and Aalborg University. Together we will exploit our capabilities in ICT, emerging technologies, and logistics competence to create a smart, transparent and sustainable food supply chain. The most critical R&D challenges are: - Integrating big data visual analytics in a food supply chain perspective. We will investigate applicable methods and forms of cooperation to exploit the potential in data sharing between supply chain partners, how to apply big data analytics, and how to tailor visual analytics to the supply chain actors. - To create smart demand planning synchronised with warehouse and production control. The main challenge is to integrate machine learning and artificial intelligence systems in real time. - To increase knowledge on how to design, plan and control smart intralogistics systems based on mobile robots (MOBOTs) for flexible and responsive food supply chains. - To sustain food production in Norway. A major project focus is efficient resource utilisation and reduction of food waste.