Creating intelligent manufacturing systems

Additive Manufacturing (AM) is one of the game changers in the 4th industrial revolution. Current research themes within AM include process modelling and optimization, development of AM processes for new materials, development of AM processes for multi-material applications (metal/plastic, metal/ceramic), development of AM processes for very large parts, new AM based models for product design and AM process and product certification.

Integrated sensors and control play a crucial role towards zero defect manufacturing. Sensors provide a huge amount of data, which has to be mined, processed and translated to control and advance the manufacturing process. Variation in, e.g., material and process conditions can be measured in-line and directly corrected based on advanced nonlinear process models. Research in this area focuses on nonlinear process (chain) modelling, robust optimization and model-based control.  

In Industry 4.0 scenarios, smart robots will take on a range of production tasks (production, inspection, transportation) and will behave as smart production entities based on local intelligence that react to data from sensor-rich production environments. Current research focuses on decentralized and mixed control strategies that will enable maximal flexibility and extensibility of systems of cooperating production robots.

Maintenance is vital in ensuring the availability, reliability and cost effectiveness of technical systems. The research field ranges from physics of failure (failure modelling, life prediction) and structural health and condition monitoring to data analysis, maintenance process optimization and logistic challenges in resource planning. The key challenge is to transfer fixed time interval maintenance to on-demand, remote operated maintenance strategies.

Digital Twinning means that each physical device and process will have its cyber part as a digital representation of the real world for the whole life cycle of a product or process. The ‘digital household’ consists of a ‘digital parent’ that captures the nominal type definition of the cyber-physical system, and digital twins that represent one or more instantiated products.

Process and product development are organized in cycles. The structuring, management and the accuracy, applicability and reliability of information is of crucial importance for the efficiency and effectiveness of these development cycles. The development cycles of products and processes, combined with the different stakeholders/perspectives that are involved at different levels of aggregation are so complex, that virtual models are required to provide the essential understanding for optimal product and process development. Research on all levels is carried out to allow for building full-blown Digital Twins.

The relevant topics for research related to modelling, analysis, design and internet-based ICT for smart industries are sensor design, with (wireless) sensor networks to monitor production processes and products; Internet-enabled decentralized monitoring and control algorithms that improve product and production-process performance; machine-learning algorithms and (big) data analytics for industrial processes; effective, reliable, and secure data collection and sharing; proactive maintenance strategies using local and global information; improved supply-chain management techniques, utilizing data acquired locally and globally; self-optimizing (industrial) systems; autonomic systems; cloud-based generic services that enable the transfer to smart industries; dependability, security, and privacy issues of the internet-of-things; ICT’s impact for smart industries on industry structures and value chains; and application-specific research, including (but not limited to) smart grids, production, transportation systems, and infrastructure. 

A cyber-physical system (CPS) is a system featuring a tight combination of, and coordination between, the system’s computational and physical elements, and the system’s environment. The CPS research focuses on the design and implementation of communicating computational elements (both hardware and software for both communication and computation), taking into account the foreseen interaction with a physical environment, and driven by application constraints. To integrate networking, computation and physical processes, wireless networked systems for sensing and control are of key importance. Research ranges from radio transmission systems, and wireless network systems to sensing and control, always in close connection with the (extremely demanding) applications. 

Cyber Security and Public Safety aims to make physical and cyber space safer by combining the forces of ICT and social sciences, in particular psychology, sociology, and philosophy, in order to design high-tech solutions tuned to human behaviour and needs. ICT will provide the technology to detect risks and abuse and protect against these. Social sciences will help to understand the behaviour of users and (potential) offenders in order to design technology that is effective, efficient and proportional.

Global supply chains and business networks will be continuously redesigned driven by ICT innovations. Sensor networks start to deliver a wealth of (near) real-time data from distributed sources. No longer dependent on rough estimates, industry can start to use big datasets to analyze current performance and future alternatives. Businesses that do not have the agility to transform their ICT architecture, processes, products and services quickly lose their competitive edge.

Disturbances in supply chain have to be tackled at the three production levels, i.e., production network, plant and shop-floor levels, thus covering the strategic, tactical and operational decision-making levels. As disturbances propagate from one level to another, proper coordination mechanisms are required to manage the supply chains robustness. Methods and computer tools are developed for quickly setting up new supply chain configurations. These tools will determine and implement new production schedules as soon as changes in supply chain configurations are occurring. This will increase the level of coordination among suppliers and producers by information sharing protocols and contracts, and changing planning directly as system disturbances appear. Driven by the concept of equipment re-use, reconfigurable and co-evolving production cells can be implemented.

Sustainable Supply Chain Innovation (SSI) focuses at the design and implementation of sustainable innovation of global supply chains. SSI is achieved by enhancing and implementing ICT, operations and coordination methods for planning and control, and organizational theories in complex multi-actor settings. Methods include algorithm design, large-scale simulations, serious games, architecture modelling and distributed systems engineering.

Smart Industry challenges the validity of established business models. Increasing customer/market orientation and the resulting problems of varying diversity and product complexity correlates to the complexity of business processes in manufacturing companies. The speed of corporate reactions towards changes to obtain or maintain a stable process situation depends on the product and process transparency. The management of complexity in product and processes as well as the decentralization in case of smart factories is a real future challenge. To successfully combine the use of new production technology, digitization and a network approach, firms are challenged to adapt the four interlocking elements of their business model, i.e., customer value proposition, profit formula, key processes and key resources.

The establishment of a network-centric production system that spreads throughout the entire asset life cycle may cause the emergence of new forms of collaborations that are characterized by a co-creation approach to value creation. Among the collaboration partners, customers play a predominating role. They become an integral part of the smart industry by providing information on their individual needs – a critical input for optimizing existing and creating new network centric production systems. Some key research lines are the design and implementation of new business models that allow the active integration of customers, to evolve business models into efficient and effective mechanisms based on co-creation competences, customer intimacy within an information-based business approach and the contribution of co-creation approach to the creation of customer intimacy.

Smart Industry is on the agenda of many countries, hence, managing inter-company relationships in coopetitive settings, i.e., contexts in which competition and cooperation merge together, has to be advanced. Since competition and cooperation might not be considered as secluded spheres, the development and adoption of new technologies required for smart industry solutions (e.g., automation, digitization, flexibilisation, etc.) might benefit from a network approach to innovation among various competitive firms. Therefore, key questions to be asked are: How to promote the establishment of coopetitive settings to foster the development of a smart industry? How can coopetitive competences help business models to evolve into efficient and effective mechanisms of value creation within a smart industry? How do coopetitive settings impact the technological advancement and adoption of technological standards within a smart industry? How can firms benefit from the pursuit of coopetition strategies?

The renowned Fraunhofer Institute brings two things together: fundamental scientific research and ready-made solutions for current and highly complex industrial challenges. With 69 centres worldwide, all linked to a university and a neighbouring industrial region, the centre is Europe's leading institution for applied scientific research.

‘We create a golden circle of science, industrial application and socio-economic progress,’ says Biba Visnjicki, director of Business Development at the Twente branch, the Fraunhofer Project Center in Enschede. ‘We only have one main activity: finding new ways to translate relevant scientific knowledge into industrial solutions that benefit the economy and society as a whole.’ 

In the Netherlands the institute only works with one university: the University of Twente (UT). ‘A logical choice,’ says Visnjicki. ‘The UT is the only university in the Netherlands with a strong focus on, and a leading role in, the field of production and the manufacturing industry. With research in areas ranging from non-conventional production techniques, data science and cyber security to psychology, management and organization, the UT has all the areas of expertise needed to shape the industry of tomorrow. In addition, the Twente region, home to many first- and second-tier manufacturing companies, is definitely the strongest Dutch region in advanced manufacturing. There is a lot of potential for further growth and an urgent need for what we offer.’

According to Visnjicki, the most pressing question in the manufacturing industry at the moment is: How can the industry use all the data it is now collecting with the help of sensor technology – on products, processes, chains and markets – to produce more intelligently? Visnjicki: ‘A university like the UT has in-depth knowledge that is essential to finding answers to this question. But the industry is in a hurry. Our job is not to rush scientists, or to turn them into solution sales people. Neither is it to tell industries to be patient. What we do and want to do is build creative bridges between the two. Based on a specific customer request, together with our colleagues from Fraunhofer IPT, we set up extra resources and people – for example, Master's students, post-doctoral researchers or project teams – to scour the scientific field for relevant knowledge and to convert what they find into working solutions, in collaboration with industry. It works both ways, because the industrial applicability of knowledge gives direction to new scientific research and stimulates scientists and students to think about the questions of tomorrow and the day after. It’s a golden circle.’