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The European Union is introducing the concept of the Digital Product Passport (DPP) to the manufacturing industry. The first domain areas are batteries and textiles, but regulation will soon reach all manufacturing domains. In this paper, we briefly discuss the requirements of the DPP and its contributions to the circular economy and sustainable decision making through the product lifecycle and manufacturing value chain. Some preliminary architectural viewpoints are explained, aligned with the intention to exploit the International Data Spaces (IDS) reference architecture for secure data sharing among actors. A practical way to manage the complex innovation process of how to co-create and implement the DPP via several iterative minimum viable DPP deployments is also outlined. It contains the proof-of-concept process with the build-measure-learn circles and the sprint model.

This white paper was written to gather, open and share the overflowing initiatives and concepts concerning twin transition and digital product passport (DPP) raised by European Commission. The authors hope this paper will help manufacturing industry to proceed with their sustainability goals and to develop circular economy through new R cycles. Further, the authors believe that the DPP is a concept worthwhile to study and further pilot in industrial cases.In future the DPP will be used by the European authorities monitoring product regulations in Eu-rope. The DPP can help consumers to make better (more sustainable) purchase decisions based on the available product information. The DPP shall help and guide the repair, remanufacturing and recycling activities of a product. Further, all product value chain actors can optimise their own operations based on the data shared via the DPP.

In capital intensive industries, the purchasing of IoT, predictive maintenance or other digital solutions is very complex as there already exists several separate legacy systems. Also for a single solution provider, the customer needs and expectations can be huge, and they might not have all resources or competences needed for the delivery. In our research, we examined various aspects related to joint offering development and value creation. We define the joint offering as a concept or solution that is co-created in collaboration with two or more actors that usually have complementary technological skills or value creation logics. Based on our study, there is still relatively little joint offerings deployed supporting asset performance management and execution of asset management operations. To discover the interaction between the actors able to provide a joint-solution, we further sketched value network models from the anonymised industrial challenges. Finally, the developed conceptual framework clarifies the scene of both the business opportunities and value assessment. The first part of the framework, business opportunities, considers the business models, value networks and analysis of business opportunities and risks. The later part, business value assessment, is built on capital and operating expenditure and revenues summarising the business value.

The European Institute of Innovation and Technology (EIT) is an EU body set up to strengthen Europe’s ability to innovate. Today it is Europe's largest innovation ecosystem with over 2000 partners. The EIT supports the development of dynamic, long-term thematic partnerships Knowledge and Innovation Communities (EIT KICs) among companies, research and higher education institutions, to tackle pressing global challenges. Together with their leading partners across Europe, the EIT Community offers a wide range of innovation and entrepreneurship activities across Europe. Artificial intelligence (AI) has become an area of strategic importance and a key driver of economic development. As a result, a European initiative was kicked off in Q2, 2019 called “Artificial Intelligence for Europe”. A budget allocated of around € 2.5 billion has been earmarked to increase efforts in the key areas of AI in Europe. Boost the EU’s technological and industrial capacity in AI, up taking it across public and private sectors. Empower the education system to pre-empt the socio-economic changes that will come with the rise of AI and modernize training and talent management systems that support the labour market and increase the employability of trainees. Build ethical and legal frameworks to ensure all rights of citizens are protected. VTT’s AI maturity tool was selected as the tool to be shared among several KICs, such as EIT Digital, EIT Health, EIT Manufacturing, EIT Climate KIC and EIT InnoEnergy. During 2021 VTT’s AI Maturity tool was translated to Spanish, French, Deutsch, Italian and Polish in addition to the already existing implementation in English and Finnish.

The fundamental business values and opportunities for (more) digitalized engineering report ties together different aspects related to doing business with digital twins in the pulp and paper industrial engineering and processing contexts. These practical aspects have been identified, and the understanding in them has been developed during the SEED project especially in the digital twins related use case work and in related research, and in the work done related to joint offering of digital solutions.

This report presents the both the development steps for agile cognitive industry and the dimensions of the maturity model that were developed for the implementation of ManuMaturity tool. The ManuMaturity tool was implemented to help manufacturing companies to proceed in digitalisation and to reach Industry 4.0 level or even beyond it. The maturity model has three sectors (Business, Technology and Responsibility) and seven dimensions: Customer, Business model, Processes, Data, Infrastructure, Employee, and Sustainability. With the implemented ManuMaturity self-assessment web tool, a company can discover its own maturity level in addition to strengths and weaknesses with regard to the seven dimensions. The questions and answer alternatives have been formulated to make it possible for the company representatives to complete it independently within 15-20 minutes. The web tool immediately displays the result graph based on the selections of respondent together with the average of all respondents.The ManuMaturity web tool is available at https://manumaturity.vtt.fi/ for self-assessment of companies. It is free for any non-commercial use.

Digitalisation is progressing in every domain, including the manufacturing industries. Digitising, digitalisation and digital transformation are concepts that are sometimes mixed or intentionally broaden or constricted. For us digitising is the way to provide a digital presentation (model) of an entity i.e. converting information from a physical format into a digital one. Digitalisation means the implementation of processes or services via information and communication technologies (ICT). Digital transformation is the way to digitalise your product, services or processes; i.e. how to proceed with digitalisation. In Finland, there are examples of ICT forerunners on manufacturing sector. For example, Cargotec already has over 250 implemented robot process automation applications. The first industrial 5G, edge-computing and AI-based machine-vision system can detect errors and guide workers online at ABB. However, there are some smaller forerunners, too. For example, Mantsinen has implemented intelligent maintenance service based on an Internet of Things (IoT) solution that feeds 50 different bus signals into the cloud about every second. This service is piloted with material handling machinery in a harbour in the UK. This leaflet focusses on Finnish manufacturing small- and medium-sized enterprises (SMEs) and clarifies their digitalisation status, challenges and potential technologies. Some supportive actions are proposed. VTT’s role and means to support those SMEs will be considered in more detail soon.

Artificial intelligence (AI) is both revolutionising the ways in which societies functions and opening up new business opportunities. AI is expected to increase automation and boost productivity. It, therefore, is essential for all organisations to understand their readiness to take advantage of AI.The AI maturity self-assessment web tool helps organisations gain a holistic view on their maturity level when planning, applying and developing new solutions based on AI. The tool was developed based on work by Finland’s Artificial Intelligence Accelerator published in the Finnish Digibarometer 2018. The contents were reworked in close cooperation by the VTT Technical Research Centre of Finland Ltd. (VTT) and the University of Oulu, and in early 2019, VTT launched the tool as a free web tool for any organisation to assess its current AI maturity. It enables maturity comparison with other respondents of the tool and creating national and international AI maturity overview in the long run.

Beyond IoT Business reflects our view on digital transformation within manufacturing sectors. It aims to provide new insights into emerging possibilities and future development paths. This report is based on the experts workshop jointly organised at VTT in Espoo, Oulu and Tampere at the end of 2018. The workshop results are complemented by other materials, such as blogposts, research reports and project presentations. Today, digitalisation has created an explosion of data, and the manufacturing sector is one of the sectors that generate remarkable amounts of data within its smart connected factories. Nevertheless, the utilisation of this sector’s data are one of the lowest, as it is typically saved to closed enterprise data management systems. Unlocking the value of these data sources requires collaboration between the existing value networks of the manufacturing industry and network actors operating within data flows. There are a number of ways to use the data to build businesses, including data management, analysis and delivery. Services are the core of business based on IoT solutions and the outcome economy, where suppliers contribute directly to operational efficiency and key value co-creation processes. We emphasise that a real impact can be gained by changing how goods are made and distributed, how products are serviced and refined, as well as how resources are shared and circulated. Furthermore, the transformation requires investment in new capabilities and skills, i.e., learning and re-learning. This is especially true for organisations that have enjoyed great success, as the disruption means that some of their current capabilities and skills become outdated. We wish to thank everybody who participated in the workshop and person-to-person brainstorming discussion. It has been crucial to gain different views on a future beyond IoT business.

Cloud-enabled tools developed in the Cloud Collaborative Manufacturing Networks (C2NET) project address the needs of small and medium enterprises with respect to information exchange and visibility across the collaboration partners in the supply network, coupled with automated and collaborative production planning and supply management. This paper analyses a case of an oil lubrication and hydraulic systems manufacturer and describes a pilot application of C2NET where the production schedule is optimized according to the priorities of the pilot company. In this case the goal is a highly adaptive just-in-time manufacturing schedule with guaranteed on time delivery. acceptedVersion

Here we define foresight as a view forward or exploring alternatives for the future. The current global business environment is ever-changing, and new technologies, innovations, threats and opportunities emerge continuously. Early identification of discontinuities can prevent companies from losing ground in this competitive environment. Thus, many companies have already started to prepare better for the future by initiating foresight practices. Foresight requires futureoriented awareness and planning that enable businesses to respond quickly to future threats and opportunities in the market. Foresight is a necessity for companies aiming to survive as the world around them is changing. Foresight is an activity that guides a company to: I. actively scan the environment, identifying trends in consumer and customer behaviour, industrial trends, disruptions, emerging technologies, competitors, clients' needs, wild cards and weak signals. II. interpret the identified signals and find opportunities and threats. III. prospect the opportunities and threats and evaluate options for decision-making. These options may be incremental innovations around an existing product or service or radical innovations with a new product, service or even customer.

Corporate foresight is a value-creation tool that helps companies survive in a competitive, ever-changing business environment. Foresight can be perceived as a company's capability to commit to continuous environmental scanning and to respond quickly to the discovered market threats and opportunities. Currently, there is scarce literature about foresight application procedures in organizations. This paper presents a single-case study, with a foresight process that was experimented in a real industrial setting. Based solely on a workshop series, this simple and straightforward process used the participants' tacit knowledge and insights as the main data sources. The participants presented different roles and departments of the case company. As a result, two new application areas, My Data and eHealth, were found, and a message to the company's top management was formulated. The future will show how the results will be implemented in the company and what will be their business impact.

This paper outlines the main outcomes of the work performed for Industrial Scenarios and Requirements Analysis, under the project C2NET Cloud Collaborative Manufacturing Networks. To ensure a successful management of a collaborative network for the manufacturing industry, different collaboration planning problems and needs between supply chain stakeholders (suppliers, manufacturers, distributors, retailers, managers, etc.) along the entire supply chain are addressed. Four industrial pilots representing relevant sectors such as Automotive, Dermo-cosmetics, Metalworking SMEs networks and Original Equipment Manufacturing (OEM) of Hydraulic/Lubrication systems are described, and the main functionalities identified for the C2NET Cloud platform are highlighted. Additionally, acceptance criteria and corresponding metrics settled to validate the results of the project are explained.