Fraunhofer Institute for Industrial Engineering

With the introduction of the Internet of Things (IoT) and cyber-physical system (CPS) concepts in industrial application scenarios, industrial automation is undergoing a tremendous change. This is made possible in part by recent advances in technology that allow interconnection on a wider and more fine-grained scale. The purpose of this article is to review technological trends and the impact they may have on industrial communication. We will review the impact of IoT and CPSs on industrial automation from an industry 4.0 perspective, give a survey of the current state of work on Ethernet time-sensitive networking (TSN), and shed light on the role of fifth-generation (5G) telecom networks in automation. Moreover, we will point out the need for harmonization beyond networking.

Many people spend an increasing amount of time in front of computer screens equipped with light-emitting diodes (LED) with a short wavelength (blue range). Thus we investigated the repercussions on melatonin (a marker of the circadian clock), alertness, and cognitive performance levels in 13 young male volunteers under controlled laboratory conditions in a balanced crossover design. A 5-h evening exposure to a white LED-backlit screen with more than twice as much 464 nm light emission {irradiance of 0,241 Watt/(steradian × m(2)) [W/(sr × m(2))], 2.1 × 10(13) photons/(cm(2) × s), in the wavelength range of 454 and 474 nm} than a white non-LED-backlit screen [irradiance of 0,099 W/(sr × m(2)), 0.7 × 10(13) photons/(cm(2) × s), in the wavelength range of 454 and 474 nm] elicited a significant suppression of the evening rise in endogenous melatonin and subjective as well as objective sleepiness, as indexed by a reduced incidence of slow eye movements and EEG low-frequency activity (1-7 Hz) in frontal brain regions. Concomitantly, sustained attention, as determined by the GO/NOGO task; working memory/attention, as assessed by "explicit timing"; and declarative memory performance in a word-learning paradigm were significantly enhanced in the LED-backlit screen compared with the non-LED condition. Screen quality and visual comfort were rated the same in both screen conditions, whereas the non-LED screen tended to be considered brighter. Our data indicate that the spectral profile of light emitted by computer screens impacts on circadian physiology, alertness, and cognitive performance levels. The challenge will be to design a computer screen with a spectral profile that can be individually programmed to add timed, essential light information to the circadian system in humans.

Cities are complex systems connected to economic, ecological, and demographic conditions and change. They are also characterized by diverging perceptions and interests of citizens and stakeholders. Thus, in the arena of urban planning, we are in need of approaches that are able to cope not only with urban complexity but also allow for participatory and collaborative processes to empower citizens. This to create democratic cities. Connected to the field of smart cities and citizens, we present in this paper, the prototype of an urban digital twin for the 30,000-people town of Herrenberg in Germany. Urban digital twins are sophisticated data models allowing for collaborative processes. The herein presented prototype comprises (1) a 3D model of the built environment, (2) a street network model using the theory and method of space syntax, (3) an urban mobility simulation, (4) a wind flow simulation, and (5) a number of empirical quantitative and qualitative data using volunteered geographic information (VGI). In addition, the urban digital twin was implemented in a visualization platform for virtual reality and was presented to the general public during diverse public participatory processes, as well as in the framework of the “Morgenstadt Werkstatt” (Tomorrow’s Cities Workshop). The results of a survey indicated that this method and technology could significantly aid in participatory and collaborative processes. Further understanding of how urban digital twins support urban planners, urban designers, and the general public as a collaboration and communication tool and for decision support allows us to be more intentional when creating smart cities and sustainable cities with the help of digital twins. We conclude the paper with a discussion of the presented results and further research directions.

Volatile markets and global and inter-industrial networks are creating a radically more dynamic market environment which calls for considerably greater on-demand flexibility in resource deployment. Today's businesses have to respond to evolving trends. As well as increasing flexibility, this also means taking action in two further areas, namely increasing transformability and responding to demographic change. Furthermore the global change towards a fully networked society is in progress, in Germany, in Europe, and of course in the United States – actually more or less all over the world. In this context one significant topic is the “Internet of things and services”. The digital transformation changes business and private life likewise – in a radically and sustainable way. The economic potential is enormous. Topics related to the networking of the internet by far have the most economical potential worldwide. The world becomes more and more digital. This is the Big Business of the future. Digitally networked and data-intensive are the main attributes of a smarter production, the so called industry 4.0. But not only in technology many things are changing, humans and the society transforms, too. To achieve a positive influence on key performance indicators, organizational approaches to enterprise architecture should not be restricted to purely technical aspects but should instead put the focus firmly on employees. The study examines initial design approaches in the areas of qualifications, leadership and demography-resistant work architectures.

CITATION: Von Leipzig, T., et al. 2017. Initialising customer-orientated digital transformation in enterprises. Procedia Manufacturing, 8:517-524, doi:10.1016/j.promfg.2017.02.066.

Automated driving is no longer a future scenario. Several automotive OEM have already presented automated vehicles, which do not require driver's constant attention on the road. But, there are still some challenges to solve before series vehicles can pass from assisted driving to highly automated driving [1; 2]. A principal research question to deal with is how to design Take-Over-Requests (TOR) with respect to the human machine interface (HMI) and reaction times to comply with a TOR. On this account, a driving simulator study with 44 drivers has been conducted at the Fraunhofer Institute for Industrial Engineering. The study took place in a highly automated driving vehicle which controlled longitudinal and lateral control on a highway scenario. Approaching a construction site different TOR strategies were presented. Within this study the time users needed to react on a TOR was measured for a highway scenario. The drivers were fully distracted by a secondary task, a challenging quiz game on a mobile phone. The different TOR strategies comprised a variation of the location for TOR presentation (integrated mobile phone or in-vehicle HMI) as well as a variation of the TOR modality (TOR with brake jerk/without brake jerk). This paper will present and discuss the results in terms of reaction times and driver behavior strategies to comply with the TOR. It delivers advice on the design of transition strategies between automated and manual driving.

The Quadruple Helix Model of innovation recognizes four major actors in the innovation system: science, policy, industry, and society. In keeping with this model, more and more governments are prioritizing greater public involvement in innovation processes. The goal of this study was to identify desirable and productive forms of interaction between the scientific community and the public. Our analysis focuses on the point of view of societal actors, which has so far been largely neglected in scientific literature and political discourse. To this end, we interviewed 50 laypersons with participatory research and innovation experience in Germany to document their opinions of the value of such interaction, the goals it should pursue, and the forms it should take. Rather than preferring the democratization of science in general, interviewees expressed the desire for more extensive opportunities to introduce scientific and technological considerations as part of bidirectional exchanges between academia and society. This paper proposes a layperson typology intended to help design participatory processes that facilitate such exchanges and includes the differences in opinions between men and women.

Innovation has been widely recognized as the key driver of economic growth. However, in the knowledge-driven economy, the nature of innovation is changing. Both technologies and innovations are becoming more complex as the knowledge content has increased. Due to the amount of different knowledge domains, individual players cannot develop anymore all the competencies necessary to create innovation in the knowledge-driven economy. Successful innovators therefore join to form innovation networks that allow them to source flexibly competencies and to offer innovations that are complete solutions and not just products. The traditional linear model from research and development as a basis of innovations is thus shifting to a model with a wide network of sources and partners integrating complementary competencies. Managing innovation in such a network poses new challenges for companies as they need to adapt their way of working and develop ‘networking’ competencies. In this paper, success factors are derived that networks and companies need to adopt to create innovation. For the support of the management of such networks, the innovation roadmapping methodology is proposed. Previously only applied for innovation management in individual organizations, innovation roadmapping should be used as a means to identify and exploit ideas and to align the innovation efforts in the network.

A method and a set of supporting tools have been developed for an improved integration of user interface design with software engineering methods and tools. Animated user interfaces for database-oriented applications are generated from an extended data model and a new graphical technique for specifying dialogues. Based on views defined for the data model, an expert system uses explicit design rules derived from existing guidelines for producing the static layout of the user interface. A petri net based technique called dialogue nets is used for specifying the dynamic behaviour. Output is generated for an existing user interface management system. The approach supports rapid prototyping while using the advantages of standard software engineering methods.

The path toward founding a venture is changing. In fact, future-oriented competencies are key in entrepreneurial aspirations. In an increasingly digital society, the intention to become an entrepreneur is strongly influenced by individual digital competencies. In our study, we explore whether and how digital competencies unfold into entrepreneurial intention. Using a diverse, time-lagged dataset of participants of a massive open online course (MOOC), we test for an effect of digital competencies on entrepreneurial intention, dually mediated by individual entrepreneurial orientation and self-efficacy. Our results empirically confirm the often assumed positive influence of digital competencies on entrepreneurial intention, and surprisingly, reveal that this relationship only manifests in mediation. We discuss our findings paying specific attention to research on the entrepreneurial mindset, education, and the role of digital technologies in entrepreneurship. For entrepreneurship practice, our insights imply that educators and aspiring entrepreneurs are well-advised to develop entrepreneurial and digital proclivity in concert.

The adoption of advanced manufacturing intelligence technologies requires managing the interaction of information in Product-Service Systems (PSS) by combining Product (PLM) and Service Lifecycle Management (SLM). While up to now no sound methodology exists, there is a strong need to have bi-directional coordination and interaction between PLM and SLM in a systematic way. A further challenge is to close loops, for example feedback from service delivery to the beginning-of-life phase of products. The objective of this paper is therefore to identify the interactions between SLM and PLM in manufacturing firms, based on expert interviews and illustrated in PSS use cases.

Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1-4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models' predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models' forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models' past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models' forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models' forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models' forecasts of deaths (N=763 predictions from 20 models). Across a 1-4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks. Funding: AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 (https://www.nfdi4health.de/task-force-covid-19-2) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z).

The paper proposes a model for assessing the maturity of new service development (NSD) processes in manufacturing companies that offer product-services. The model adopts a five-stage scale on which key elements are evaluated according to the following dimensions: (1) the approach used to manage processes and projects (2) the use of specific resources, skills and tools (3) the involvement of customers, suppliers and other stakeholders and (4) the adoption of performance management systems. An empirical application of the model was carried out based on an inter-company workshop and in-depth interviews. Such a model allows not only to describe the maturity of NSD processes of a company but also to identify the main gaps and to prioritize improvement actions.

Determination of the right time for machine maintenance is a major challenge for many industrial companies. Currently, most companies react on occurring breakdowns (reactive maintenance) or maintenance is carried out in scheduled time intervals (preventive maintenance). These results in either unexpected production stops, or a waste of machine working hours, because components are switched too early. Consequently, predictive maintenance strategies offer a big potential. An essential part of predictive maintenance is the estimation of the Remaining Useful Life (RUL) of machine assets. RUL estimation approaches are based on statistical methods and derived algorithms. Thus, a lot of data is needed for a good estimation. Additionally, data can be generated by means of simulation to improve the RUL estimation. However, companies hardly have an overview of available data and according modules, which are needed for a holistic predictive maintenance strategy. This paper shows an approach for a predictive maintenance strategy dealing with acquisition, processing, and analysis of historical field data as well as the generation of respective simulation data. A structured process map with a derived systematic strategy will give companies an idea of how they can integrate predictive maintenance into existing processes. By incorporating the concept of a digital twin of a production machine, the interaction of measured and estimated as well as generated data by means of simulation, are shown. The digital twin could deliver results to retrofit data-driven prediction models, in order to improve the estimation of the RUL.

Purpose The aim of this study is to investigate the role of key strategic factors in new service development (NSD). In particular, the role of service development strategy, a formalised development process, integrated development teams and customer co‐creation were investigated and the results were compared with managers' beliefs. Design/methodology/approach The study used a sample of more than 500 service development projects to test a NSD conceptual model. Regression analysis was used to test the relative importance of the key strategic factors, and the results were compared with managers' beliefs. Findings The results show that managers believe that customer co‐creation is most important in order to succeed with NSD. However, contrary to management belief, a service development strategy is the “missing link” in improving NSD performance. In addition, the research highlighted an interaction effect between integrated development teams and customer co‐creation, which means that project managers should focus on individual competencies on the development team and how they interact with customers throughout the NSD process. Originality/value For a long time, NSD has failed to receive the attention it deserves, not just in practice but also in service research. This study shows that the number of new services put on the market and then withdrawn because of low sales remains as high as 43 per cent. This paper contributes knowledge on how to reduce the number of failures in NSD by pointing out the key strategic factors that influence NSD performance.

Adaptive user interfaces can make technology more accessible. Quite a number of conceptual and technical approaches have been proposed for adaptations to diverse user needs, multiple devices or multiple environments. Little work, however, has been directed at integrating all the essential aspects of adaptive user interfaces for accessibility in one system. In this paper, we present our generic MyUI infrastructure for increased accessibility through automatically generated adaptive user interfaces. The multimodal design patterns repository serves as the basis for a modular approach to individualized user interfaces. This open and extensible pattern repository makes the adaptation rules transparent for designers and developers who can contribute to the repository by sharing their knowledge about accessible design. The adaptation architecture and procedures enable user interface generation and dynamic adaptations during run-time. For the specification of an abstract user interface model, a novel statecharts-based notation has been developed. A development tool supports the interactive creation of the graphical user interface model.

Abstract Lateral terrestrial water flow is usually not considered in regional climate modeling. This study focuses on the impact of increased hydrological model complexity for the description of the land‐atmosphere interactions in a complex terrain region. For this purpose, we apply the Weather Research and Forecasting (WRF) model with its hydrological modeling extension package WRF‐Hydro for the case of the Heihe River Basin in convection permitting atmospheric resolution (3 km). The Heihe River Basin (143,200 km 2 ) is an arid‐semiarid inland river basin in Northwestern China. By comparing model simulations results with and without coupling for the period 2008–2010, the effect of lateral terrestrial water flow on land‐atmosphere interactions is evaluated with a joint atmospheric‐terrestrial water budget analysis, a regional precipitation recycling analysis and a fully three‐dimensional atmospheric moisture tracing method (evaporation tagging). The coupled modeling system WRF‐Hydro simulates near‐surface temperature and precipitation variability similar to the WRF model and demonstrates, in addition, its ability to reproduce daily streamflow. In the fully coupled mode, as a consequence of lateral terrestrial water flow description, the redistribution of infiltration excess in the mountainous area produces higher soil moisture content in the root zone, increases the terrestrial water storage and evapotranspiration, and decreases the total runoff. The resulting wetting and cooling in the near surface affects the regional climate by changing the regional water vapor transports and water vapor content, while, in turn, inducing precipitation differences. Overall, the fully coupled modeling increases the recycling rate, indicating that lateral terrestrial water flow influences regional climate in our study area.

"Open innovation" and "external search" for new ideas are central topics in the recent discourse in innovation research. External search helps firms to identify new opportunities for innovation and alleviates the risks of local search. It is widely acknowledged that novel ideas regularly emerge from the combination of distant pieces of knowledge and interaction with "idea suppliers" from distant knowledge domains. However, the current discussion on open innovation has hardly touched upon the question of how firms can systematically search for cross-industry innovation inputs in the fuzzy front-end of the innovation process. This paper links relevant concepts of cognitive psychology and management theory — such as analogical problem solving and the principle of isomorphism — with open innovation in the front-end. It discusses relevant dimensions of systematic search for innovation across industries. A piloted framework is presented that assists firms in systematically and interactively searching for external innovation inputs in distant industries. This framework supports external innovation search in distant industries for a fuzzy customer problem. The results of this participatory action research indicate that a systematic and interactive search process is of practical value to innovation managers. It also points out contingencies of cross-industry innovation search.

Abstract Background Social acceptance presents a major challenge for Germany’s transition to green energy. As a power-to-x technology, green hydrogen is set to become a key component of a future sustainable energy system. With a view to averting conflicts like those surrounding wind energy, we have investigated social acceptance of green hydrogen at an early stage in its implementation, before wider rollout. Our study uses a mixed-method approach, wherein semi-structured interviews ( n = 24) and two participatory workshops ( n = 51) in a selected region in central Germany serve alongside a representative survey ( n = 2054) as the basis for both understanding social attitudes and reaching generalisable conclusions. Results Overall, it is possible to observe both a marked lack of knowledge and a large degree of openness towards green hydrogen and its local use, along with high expectations regarding environmental and climate protection. We reach three key conclusions. First, acceptance of green hydrogen relies on trust in science, government, the media, and institutions that uphold distributive justice, with consideration for regional values playing a vital role in establishing said trust. Second, methodologically sound participatory processes can promote acceptance, and active support in particular. Third, recurrent positive participatory experiences can effectively foster trust. Conclusions Accordingly, we argue that trust should be strengthened on a structural level, and that green hydrogen acceptance should be understood as a matter of responsible innovation. As the first empirical investigation into social acceptance of green hydrogen, and by conceptually interlinking acceptance research and responsible innovation, this study constitutes an important contribution to existing research.

In recent years the open innovation paradigm has gained great attention in research on innovation and strategic management. Current research indicates that firms are opening up their innovation processes and adapt their business models to benefit not only from internal but also from external ideas and knowledge. So far, most of the research on open innovation has been focused on open innovation practices in large firms and has not considered open innovation in SMEs adequately. For this reason, our paper investigates organizational capabilities for managing open innovation in SMEs.Based on a case study analysis of the company CAS Software AG the researchers argue that SMEs have to build up new managerial capabilities within six dimensions of an integrated managerial system for open innovation.In addition the paper reveals the prosperous transformation process of the CAS Software AG towards an open innovator highlighting its characteristic of a guided evolution by means of a maturity model.