FIR e. V. an der RWTH Aachen

Overview: Digital transformation is reshaping entire segments and industries: communications, retail, and, increasingly, health care, medicine, agriculture, and manufacturing. While a few companies reach front-runner status, most seem to lag. Digital transformation is a top concern of senior leaders worldwide and motivated the development of this study. This article describes the results of the Patterns of Digitization survey designed to assess how companies are implementing digital transformation. The survey covers the various strategies companies employ, the technologies they invest in, and, in particular, the actions they take to overcome the organizational resistance that is common in most large-scale transformations. We highlight important actions all companies are taking to digitally transform their businesses and the differentiated actions of digitally mature organizations. The insights gleaned from the study should help lagging companies understand what is involved in implementing a digital transformation and what they need to do to catch up.

Overview:The digital transformation of organizations continues at a frenetic pace. While some companies have achieved trailblazer status, others are lagging because they find the transition difficult. Digital leaders play a pivotal role in digital transformation successes because they can inspire organizational and employee confidence in these disruptive and sometimes risky initiatives. We present a Digital Leadership Scale with 15 dimensions. Our scale focuses on successful leadership in digital transformation. We aimed to capture the qualities of leaders leading digitally mature organizations so that leaders of digitally developing organizations can increase their likelihood of success. We also mention the future development of a Digital Leadership Scale self-assessment tool that digital leaders can use to assess their own readiness and ability to accelerate digital initiatives.

The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.

Since 2016, the “Digital in NRW” Competence Centre has been supporting SMEs in the manufacturing industry in designing their individual digital transformation. With an Industry 4.0 maturity assessment, we define the status quo of SMEs, derive SME-specific measures from this, develop a digitalization roadmap and accompany the SME transformation. This paper presents the results of the four-year SME support. By analyzing the results of all maturity assessments, potential analysis and design workshops, we present the most frequent and most effective measures for a successful digital transformation of SMEs. The result of the paper is an action guideline for SMEs to initiate their own digital transformation based on formalized experience.

Since private passenger cars drive on average less than 2 hours per day, each electric vehicle could potentially provide capacities for grid services during more than 22 hours per day. The presented stochastic model, which bases on more than 167,000 data points from a mobility survey, simulates the driving behavior of private passenger cars. The article estimates the availability of electric vehicles for grid balancing services using the generated profiles from a stochastic model. Three basic ("zero-intelligence") charging strategies were applied.In conclusion, more than 90% of all vehicles are parked at any given point in time. Thereof, more than 25% are parked at home at any given time. Moreover, the simulation results show the urgent need for intelligent charging strategies in order to avoid additional peak loads during the evening hours and to make the service potential of electric vehicles available to the grid.

Today's manufacturers are facing numerous challenges such as highly entangled and interconnected supply chains, shortening product lifecycles and growing product complexity. They thus feel the need to adjust and adapt faster on all levels of value creation. Self-optimization as a basic principle appears a promising approach to handle complexity and unforeseen disturbances within supply chains, machines and processes. Therefore it will improve the resilience and competitiveness of manufacturing companies. This paper gives an introduction to the concept of self-optimizing production systems. After a short historical review, the different levels of value creation from supply chain design and management to manufacturing and assembly are analyzed considering their specific demands and needs for self-optimization. Examples from each of these levels are used to illustrate the concept of self-optimization as well as to outline its potential for flexibility and productivity. This paper closes with an outlook on the current scientific work and promising new fields of action.

How can you discover something new, that matches your interest? Recommender Systems have been studied since the 90ies. Their benefit comes from guiding a user through the density of the information jungle to useful knowledge clearings. Early research on recommender systems focuses on algorithms and their evaluation to improve recommendation accuracy using F-measures and other methodologies from signal-detection theory. Present research includes other aspects such as human factors that affect the user experience and interactive visualization techniques to support transparency of results and user control. In this paper, we analyze all publications on recommender systems from the scopus database, and particularly also papers with such an HCI focus. Based on an analysis of these papers, future topics for recommender systems research are identified, which include more advanced support for user control, adaptive interfaces, affective computing and applications in high risk domains.

This article describes digital leadership-specifically character and competency-that differentiate digitally mature organizations from digitally developing organizations. We assess the differentiated actions of leaders of digitally mature organizations and discuss their results. The study is based on Patterns of Digitization survey with insights from 559 decision makers across five geographic regions-America, Europe, Asia, Africa, and Oceania designed to assess how companies are implementing digital transformation, the various strategies they employ, the investments they make, and the actions they take to achieve large-scale institutionalized digital transformations. The insights gleaned from the study should help lagging companies understand what is involved in implementing a digital transformation and what they need to do to catch up.

Subscription business transforms traditional business models of machinery and plant engineering. Many manufacturing companies struggle to pull out the potential created by Industry 4.0 and make it economically usable. In addition to technological innovations, it is necessary to transform the business model. This leads to a shift from ownership-based and product-centric business models to outcome-based business models, which focus on the customer’s value and thus realize a unique value proposition and competitive advantage – the outcome economy. Based on a case study analysis among manufacturing companies, this paper provides further clarification including a definition and constituent characteristics of subscription business models in machinery and plant engineering.

Subscription business models have a major role for monetizing products and services for manufacturing companies in the age of Industry 4.0. As the manufacturing industry has difficulties generating revenues through digitalization, the implementation of innovative business models are essential to remain successful. Physical assets are often capital-intensive and require a more complex manufacturing process than subscription business models. Moreover, subscription models can focus on the individual customer benefit and a consistent service transformation, constituting a unique selling proposition and a competitive advantage. Hence, the following paper provides a management model that enables manufacturing companies to successfully realize the transformation towards a subscription business model. The management model presents four major fields of action, each matched with one design principle that must be considered when dealing with subscription models in the manufacturing industry. These principles were determined by an in-depth case study analysis among various manufacturing companies. Opportunities, challenges and recommendations for action were then systematically derived and integrated into the management model.

Overview: The speed of innovation is accelerating, which means that leaders need to move more quickly and be able to pivot their whole organizations faster than ever before. The critical leadership skills needed for successful digital transformation therefore differ from what has proven to be most effective in the past. In the digital landscape, leadership must change from an emphasis on competency to a focus on trust.

Matching supply capacity and customer demand is challenging for companies. Practitioners often fail due to a lack of information or delays in the decision-making process. Moreover, researchers fail to holistically consider demand patterns and their dynamics over time. Thus, the aim of this study is to propose a holistic approach for manufacturing organizations to change or manage their capacity. The viable system model was applied in this study. The focus of the research is the clustering of manufacturing and assembly companies. The goal of the developed capacity management model is to be able to react to all potential demand scenarios by making decisions regarding labor and correct investments and in the right moment based on the needed information. To ensure this, demand data series are analyzed enabling autonomous decision-making. In conclusion, the proposed approach enables companies to have internal mechanisms to increase their adaptability and reactivity to customer demands. In order to prove the conceptual model, a simulation of an automotive plant case study was performed, comparing it to classical approaches.

Abstract Functionalization of polyoxotungstates with organoarsonate coligands enabling surface decoration was explored for the triangular cluster architectures of the composition [CoII9(H2O)6(OH)3(p-RC6H4AsVO3)2(α-PV2WVI15O56)3]25– ({Co9(P2W15)3}, R = H or NH2), isolated as Na25[Co9(OH)3(H2O)6(C6H5AsO3)2(P2W15O56)3]·86H2O (Na-1; triclinic, P1̅, a = 25.8088(3) Å, b = 25.8336(3) Å, c = 27.1598(3) Å, α = 78.1282(11)°, β = 61.7276(14)°, γ = 60.6220(14)°, V = 13888.9(3) Å3, Z = 2) and Na25[Co9(OH)3(H2O)6(H2NC6H4AsO3)2(P2W15O56)3]·86H2O (Na-2; triclinic, P1̅, a = 14.2262(2) Å, b = 24.8597(4) Å, c = 37.9388(4) Å, α = 81.9672(10)°, β = 87.8161(10)°, γ = 76.5409(12)°, V = 12920.6(3) Å3, Z = 2). The axially oriented para-aminophenyl groups in 2 facilitate the formation of self-assembled monolayers on gold surfaces and thus provide a viable molecular platform for charge transport studies of magnetically functionalized polyoxometalates. The title systems were isolated and characterized in the solid state, in aqueous solutions, and on metal surfaces. Using conducting tip atomic force microscopy, the energies of {Co9(P2W15)3} frontier molecular orbitals in the surface-bound state were found to directly correlate with cyclic voltammetry data in aqueous solution.

Factory automation and production are currently undergoing massive changes, and 5G is considered being a key enabler. In this paper, we state uses cases for using 5G in the factory of the future, which are motivated by actual needs of the industry partners of the “5Gang” consortium. Based on these use cases and the ones by 3GPP, a 5G system architecture for the factory of the future is proposed. It is set in relation to existing architectural frameworks.

The investment in Enterprise resource planning (ERP) systems is indispensable for manufacturing companies to obtain competitive advantages in the globalized market. However, end-users are confronted with complex interfaces and poor usability of these systems. In the present multi-factorial experiment, we examined the effects of information complexity and presentation as a key aspect of usability with consideration of human factors on decision quality. By using alphanumeric tables of simulated ERP system data to make a decision, users’ decision quality dropped with increasing information complexity and the use of a poor presentation. Furthermore, interactive effects of two different aspects of information complexity (data amount and task complexity) as well as compensatory effects through human factors were revealed. These findings show the importance of empirical user studies in this field and provide several practical implication. Especially, user-centered design processes can substantially contribute to a successful implementation of complex information systems, such as ERP systems.

Abstract Anisotropic samples of lyotropic liquid crystalline (LLC) phases of valine derived polyaryl acetylenes were employed as chiral alignment media for the measurement of residual dipolar couplings (RDCs) of 12 small, chiral, organic molecules. The quadrupolar splitting of the deuterium signal of CDCl3 can be adjusted by temperature and concentration changes from 0 to 350 Hz. The LLC phases showed excellent orienting properties for all analytes bearing various functional groups. The precise extraction of RDCs in the range of up to ±30 Hz from F2‐coupled HSQC spectra was possible. Additionally, the chiral environment led to diastereomorphous interactions with the enantiomers of chiral analytes leading to two different sets of RDCs. This differential order effect was particularly pronounced with H‐bond donors like alcohols and 2° amines.

One of the major challenges facing today's manufacturing industry is to differentiate from competition in a highly globalized world. As a consequence to the increasing competitive pressure, many companies transform their product centered business models towards service based business models to differentiate from competition. However, the transformation is often underestimated regarding its complexity and its management challenges to behavioral change. As a consequence lots of transformation initiatives fail. Besides difficulties in structuring the magnitude of changes in processes and structures, many transformation managers do not perceive the risk of employee resistance against changes, which is one of the key factors causing the failure of transformation. The objective of this paper is to enhance the existing body of research on manufacturer's organizational transformation towards Product-Service Systems. More detailed, the objective is to develop new knowledge to support the management during the decision-making process in the way how and by means of which instruments the change of behavior can be supported when transforming from a manufacturer to a solution. We developed a reference framework which structures and defines the relevant dimensions of behavioral change. The identification and validation of the success factors build the second component of our research. We conducted an empirical investigation in the German manufacturing industry and got 79 data sets. Structural equation modelling was applied for the analyses and the validation of the hypotheses. By this analysis we linked management practice with employee behavior and transformational success variables. On the basis of the gained insights decisions can be made concerning the successful transformation from manufacturer to a solution-oriented service provider.

Many digital leaders are currently dealing with expanding into the highly sought-after “holy grail” of digitization by deploying Artificial Intelligence (AI) solutions. While AI projects of all types are being launched prolifically, clouds of doubt are forming around the credibility of AI results. AI has many potential benefits for businesses, but these will be realized only if people trust these tools to produce unbiased results. Managing transformation in the digital age requires leaders who not only understand the potential of these tools but also possess the necessary human skills to reshape the organization. This paper addresses one particular human dimension in some depthethical AI-and the actions successful digital leaders take to build trust in its results. It introduces a conceptual model of ethical AI considerations to ensure the use of this potentially lucrative, yet disruptive technology is indeed fair, explainable, and productive.

Abstract In this paper, we propose a communication network architecture for industrial applications that combines new 5G technologies with other existing communication technologies on the shop floor. This architecture connects private and public mobile networks with local networking technologies to achieve a flexible setup addressing many different industrial use cases. We show how the advancements introduced around the new 5G mobile technology can address a wide range of industrial requirements. We further describe relevant use cases and develop an overall communication system architecture proposal, which is able to fulfill not only technical requirements but also system requirements, which result from specific applications existing in today’s and future manufacturing scenarios.

This paper addresses the challenge of modelling individual cyber-physical systems (CPS) for small and medium-sized enterprises (SMEs) in manufacturing industries. CPS are key technology building blocks for the implementation of Industrie 4.0. Especially for SMEs the increase of production efficiency and reduction of manufacturing costs through CPS offer potential to maintain their competitiveness, and innovation capacity. Although SMEs perceive the potential of CPS, they often lack financial and human resources to acquire the necessary CPS-competencies as well as an overview of all the currently available technological solutions. To overcome this issue a matching platform will offer SMEs support in finding suitable CPS-components by letting them express their functional and technical requirements. The matching logic is based on a set of morphologies that encompasses the functional and requirement spectrum of CPS-components. The matching algorith analyses the input for congruence of requirements and available technologies and suggests suitable technology combinations. This paper describes the methodology of the matching platform, and introduces the research work to define and to develop the technology morphologies. The presented results facilitate the selection and configuration of CPS for SMEs.