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INNO-NAERING-INNO-NAERING

Smart, transparent and sustainable food supply chains

Alternative title: Smarte, transparente og bærekraftige verdikjeder for mat

Awarded: NOK 9.6 mill.

Project Manager:

Project Number:

296686

Project Period:

2019 - 2025

Funding received from:

Organisation:

Location:

Partner countries:

The DigiMat research project was conducted in collaboration between companies and research institutions to develop smarter, more sustainable, and automated solutions for food supply chains, with a particular focus on production, inventory management, and logistics. The collaboration resulted in both theoretical insights and practical solutions capable of transforming the supply chain and contributing to more efficient and environmentally friendly processes. The food sector faces challenges in production, inventory management, and logistics, where vast amounts of data are generated but not optimally utilized. The DigiMat project was initiated to explore how modern technologies such as Artificial Intelligence (AI), Machine Learning (ML), and automation could create more flexible, efficient, and sustainable food supply chains through three key innovations: 1. Smart planning and control of production and inventory 2. Smart logistics using mobile autonomous robots (MOBOTs) 3. Real-time information sharing and visualization for improved decision-making Through these innovations, the project aimed to enable more transparent and sustainable operations in the food supply chain while generating both scientific knowledge and practical utility. The project spanned 4.5 years and involved partnerships among Norwegian grocery sector actors (Brynild AS, Mills AS, H. I. Giørtz Sønner AS, and Leman Norway AS) and providers of software, technology, and consultancy services (SICK AS, BI Builders AS, SOLWR AS, Relex Solutions AS, and PA Consulting Group AS). Research participants were NTNU, Østfold University College, and Aalborg University (Denmark). Together, the consortium explored new opportunities for innovation and value creation, combining practical industry experience with academic insights. The project activities resulted in key findings that supported the overarching goals and sub-innovations. Using empirical data, theoretical insights, and practical applications, DigiMat made significant contributions to theory and practice, delivering solutions for smart supply chains in food production and inventory management. A central focus was on creating demonstrators realized in collaboration with participating companies. The research on smart planning and control explored technologies such as internet of things, big data analytics, and machine learning. A methodology for designing smart planning systems was developed and tested at a case company, examining flexibility, scalability, and dynamic production planning. Case studies mapped the potential of digitalization in production and inventory operations, resulting in a framework for assessing the need for smart planning and control. Additionally, a conceptual model was developed to integrate production data into tactical planning, enabling more accurate and reliable production schedules. One of the outcomes within smart logistics was the development of a cloud-based concept for material handling, enabling seamless integration between logistics and production processes. An analytical model demonstrated how MOBOTs improve productivity and flexibility, while an ML model optimized warehouse layouts for robots and operators, enhancing ergonomics and efficiency. The project advanced visual analytics (VA) for supply chain analytics. A comprehensive framework integrated VA into decision-making processes, and a VA tool for automatic dashboard generation made advanced analytics accessible to non-technical users. Additionally, the project demonstrated how ML could improve demand forecasting by identifying patterns in sales data that traditional methods might overlook. This innovation can reduce demand uncertainty for product launches and minimize risks of overproduction early in the product lifecycle. Dynamic allocation of storage locations also proved more effective than traditional inventory management methods. The results were disseminated through five seminars and webinars, 25 presentations, three media articles, two doctoral theses, 13 articles in international scientific journals, two book chapters, and 51 student projects. These efforts facilitated broad knowledge sharing with academia, industry, and the public. The DigiMat project was a successful collaboration between research communities and companies, delivering tangible solutions to develop smarter, more efficient, and sustainable food supply chains. The technological innovations generated significant benefits for both industry and society and established a foundation for further research and development in production, logistics, and sustainability.

Virkninger for involverte bedrifter: Bedriftene i prosjektet har startet implementering av prosjektløsninger. Brynild AS tar i bruk et produksjonsplanleggingssystem for optimalisering av scheduling og vurderer ytterligere investeringer i MOBOT-er for materialflyt. SICK AS samarbeider med Brynild og Future Then om visjonssystemer og visualiseringsløsninger for produksjonsstyring. Mills AS fokuserer på smart styring gjennom manufacturing execution-systemer (MES) og økt bruk av visjonsteknologi. Leman Norway AS tilrettelegger for smartere lokasjonsstyring, mens SOLWR AS integrerer ML-baserte lageroptimaliseringsløsninger. Relex Solutions vil bruke prosjektinnsikten for videreutvikling av løsninger innen forsyningskjedeplanlegging. Gjennom deltakelse i prosjektet har bedriftene lagt grunnlag for kompetanseheving, strategiutvikling og fremtidige investeringer. For næringsmiddelprodusentene ligger nytteverdien i bedre bruk av verdikjededata for beslutningsstøtte innen produksjon, salg og lager, som gir forbedrede prognoser, bedre planlegging og reduserte lagernivåer. Kostnadsbesparelser kan også oppnås gjennom automatisering av både fysiske og administrative prosesser. Lager- og distribusjonsaktørene ser fordeler i bruk av MOBOT-er og KI/ML-løsninger for effektivisering av plukk- og pakkprosesser, samt beslutningsstøtte og nye kundeverdier. For teknologi- og tjenesteleverandørene har prosjektet gitt økt forståelse for fremtidens teknologier og utfordringer i den norske matverdikjeden. Dette gjør dem bedre rustet til å tilby relevante og tilpassede løsninger til flere bransjer hvor digitalisering og automatisering er i vekst. Prosjektet bidro også til etableringen av teknologibedriften Future Then AS, spesialisert på dataanalyse, KI, ML og maskinsyn. Deres løsninger for kvalitetskontroll, salgsprognoser og digitalisering brukes allerede i en rekke industrier. Bredere effekter: Prosjektresultatene har lagt grunnlag for videre samarbeid mellom bedriftspartnerne og forskningsmiljøer. Den nye kunnskapen vil brukes i fremtidig forskning, både innen matverdikjeden og andre sektorer. Prosjektet legger også til rette for tverrfaglig samarbeid ved å integrere teknologier som KI, ML og automatisering på nye områder. Resultatene kan bidra til mer bærekraftige, effektive og fleksible produksjonsprosesser og er relevante for fremtidig forskning innen smart logistikk, verdikjedeoptimalisering og digitalisering. Dette styrker innovasjonsevnen og forskningsmiljøenes kapasitet til å møte utfordringer i norsk næringsliv. Resultatene har også indirekte samfunnsverdi gjennom utdanning og kompetanseutvikling. De vil bli integrert i utdanningsaktiviteter som doktorgrads-, master- og bachelorprosjekter og i etter- og videreutdanningskurs, samt som casemateriale i emner på bachelor- og masternivå. Slik sikrer prosjektet kontinuerlig kunnskapsoverføring til nye generasjoner av ingeniører, ledere og teknologer, og bidrar til å ruste norsk industri for fremtidige utfordringer.

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.

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Funding scheme:

INNO-NAERING-INNO-NAERING