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Woven piezoelectric sensors as part of the textile reinforcement of fiber reinforced plastics
(2019)
Sensor integration in fiber reinforced plastic (FRP) structures enables online process and structural health monitoring (SHM). This paper describes the development and application of woven fabric-based piezoelectric impact and bending sensors for integration into FRP. The work focuses on design and characterization of woven piezoelectric sensors, especially as a part of the reinforcement structure. The reinforcement of the component acts as a sensor in itself and therefore no additional external objects in the form of sensor components or sensor fibers, which could create unwanted weak points within the FRP, are added. The bending test results reveal a direct relationship between the applied load and the sensor signal. Furthermore, the appropriate sensor position in the component cross section was determined and the influence of thermal polarization on the sensor properties was investigated.
Willingness-to-pay for alternative fuel vehicle characteristics : a stated choice study for Germany
(2016)
In the light of European energy efficiency and clean air regulations, as well as an ambitious electric mobility goal of the German government, we examine consumer preferences for alternative fuel vehicles (AFVs) based on a Germany-wide discrete choice experiment among 711 potential car buyers. We estimate consumers’ willingness to-pay and compensating variation (CV) for improvements in vehicle attributes, also taking taste differences in the population into account by applying a latent class model with 6 distinct consumer segments. Our results indicate that about 1/3 of the consumers are oriented towards at least one AFV option, with almost half of them being AFV-affine, showing a high probability of choosing AFVs despite their current shortcomings. Our results suggest that German car buyers’ willingness-to-pay for improvements of the various vehicle attributes varies considerably across consumer groups and that the vehicle features have to meet some minimum requirements for considering AFVs. The CV values show that decision-makers in the administration and industry should focus on the most promising consumer group of ‘AFV aficionados’ and their needs. It also shows that some vehicle attribute improvements could increase the demand for AFVs cost-effectively, and that consumers would accept surcharges for some vehicle attributes at a level which could enable their private provision and economic operation (e.g. fast-charging infrastructure). Improvement of other attributes will need governmental subsidies to compensate for insufficient consumer valuation (e.g. battery capacity).
The present study investigated the possibilities and limitations of using a low-cost NIR spectrometer for the verification of the presence of the declared active pharmaceutical ingredients (APIs) in tablet formulations, especially for medicine screening studies in low-resource settings. Spectra from 950 to 1650 nm were recorded for 170 pharmaceutical products representing 41 different APIs, API combinations or placebos. Most of the products, including 20 falsified medicines, had been collected in medicine quality studies in African countries. After exploratory principal component analysis, models were built using data-driven soft independent modelling of class analogy (DD-SIMCA), a one-class classifier algorithm, for tablet products of penicillin V, sulfamethoxazole/trimethoprim, ciprofloxacin, furosemide, metronidazole, metformin, hydrochlorothiazide, and doxycycline. Spectra of amoxicillin and amoxicillin/clavulanic acid tablets were combined into a single model. Models were tested using Procrustes cross-validation and by projection of spectra of tablets containing the same or different APIs. Tablets containing no or different APIs could be identified with 100 % specificity in all models. A separation of the spectra of amoxicillin and amoxicillin/clavulanic acid tablets was achieved by partial least squares discriminant analysis. 15 out of 19 external validation products (79 %) representing different brands of the same APIs were correctly identified as members of the target class; three of the four rejected samples showed an API mass percentage of the total tablet weight that was out of the range covered in the respective calibration set. Therefore, in future investigations larger and more representative spectral libraries are required for model building. Falsified medicines containing no API, incorrect APIs, or grossly incorrect amounts of the declared APIs could be readily identified. Variation between different NIR-S-G1 spectroscopic devices led to a loss of accuracy if spectra recorded with different devices were pooled. Therefore, piecewise direct standardization was applied for calibration transfer. The investigated method is a promising tool for medicine screening studies in low-resource settings.
Product engineering and subsequent phases of product lifecycles are predominantly managed in isolation. Companies therefore do not fully exploit potentials through using data from smart factories and product usage. The novel intelligent and integrated Product Lifecycle Management (i²PLM) describes an approach that uses these data for product engineering. This paper describes the i²PLM, shows the cause-and-effect relationships in this context and presents in detail the validation of the approach. The i²PLM is applied and validated on a smart product in an industrial research environment. Here, the subsequent generation of a smart lunchbox is developed based on production and sensor data. The results of the validation give indications for further improvements of the i²PLM. This paper describes how to integrate the i²PLM into a learning factory.
In addition to increased safety by detecting possible overload, continuous component monitoring by sensor integration makes the use of fiber reinforced plastics more cost-effective. Since the components are continuously monitored, one can switch from time-based to condition-based maintenance. However, the integration of conventional sensor components causes weak points, as foreign objects are inserted into the reinforcing structure. In this paper, we examine the use of the textile reinforcement as a sensor in itself. We describe how bending sensors can be formed by slightly modifying in the composite’s reinforcement structure. We investigated two different sensor principles. (1) The integration of textile plate capacitors into the structure; (2) The construction of textile piezo elements as part of the reinforcing structure. The bending test results reveal that textile plate capacitors show a load-dependent signal output. The samples with textile piezo elements show a significant increase in signal strength.
Context: Organizations increasingly develop software in a distributed manner. The cloud provides an environment to create and maintain software-based products and services. Currently, it is unknown which software processes are suited for cloud-based development and what their effects in specific contexts are.
Objective: We aim at better understanding the software process applied to distributed software development using the cloud as development environment. We further aim at providing an instrument which helps project managers comparing different solution approaches and to adapt team processes to improve future project activities and outcomes.
Method: We provide a simulation model which helps analyzing different project parameters and their impact on projects performed in the cloud. To evaluate the simulation model, we conduct different analyses using a Scrumban process and data from a project executed in Finland and Spain. An extra adaptation of the simulation model for Scrum and Kanban was used to evaluate the suitability of the simulation model to cover further process models.
Results: A comparison of the real project data with the results obtaind from the different simulation runs shows the simulation producing results close to the real data, and we could successfully replicate a distributed software project. Furthermore, we could show that the simulation model is suitable to address further process models.
Conclusion: The simulator helps reproducing activities, developers, and events in the project, and it helps analyzing potential tradeoffs, e.g., regarding throughput, total time, project size, team size and work-in-progress limits. Furthermore, the simulation model supports project managers selecting the most suitable planning alternative thus supporting decision-making processes.
Process quality has reached a high level on mass production, utilizing well known methods like the DoE. The drawback of the unterlying statistical methods is the need for tests under real production conditions, which cause high costs due to the lost output. Research over the last decade let to methods for correcting a process by using in-situ data to correct the process parameters, but still a lot of pre-production is necessary to get this working. This paper presents a new approach in improving the product quality in process chains by using context data - which in part are gathered by using Industry 4.0 devices - to reduce the necessary pre-production.
Vehicles have been so far improved in terms of energy-efficiency and safety mainly by optimising the engine and the power train. However, there are opportunities to increase energy-efficiency and safety by adapting the individual driving behaviour in the given driving situation. In this paper, an improved rule match algorithm is introduced, which is used in the expert system of a human-centred driving system. The goal of the driving system is to optimise the driving behaviour in terms of energy-efficiency and safety by giving recommendations to the driver. The improved rule match algorithm checks the incoming information against the driving rules to recognise any breakings of a driving rule. The needed information is obtained by monitoring the driver, the current driving situation as well as the car, using in-vehicle sensors and serial-bus systems. On the basis of the detected broken driving rules, the expert system will create individual recommendations in terms of energy-efficiency and safety, which will allow eliminating bad driving habits, while considering the driver needs.
Managerial accountants spend a large part of their working time on more operational activities in cost accounting, reporting, and operational planning and budgeting. In all these areas, there has been increasing discussion in recent years, both in theory and practice, about using more digital technologies. For reporting, this means not only an intensified discussion of technologies such as RPA and AI but also more intensive changes to existing reporting systems. In particular, management information systems (MIS), which are maintained by managerial accountants and used by managers for corporate management, should be mentioned here. Based on an empirical survey in a large German company, this article discusses the requirements and assessments of users when switching from a regular MIS to a cloud-based system.
Unsaturated polyester resins (UPR) and vinyl ester resins (VER) are among the most commercially important thermosetting matrix materials for composites. Although comparatively low cost, their technological performance is suitable for a wide range of applications, such as fiber-reinforced plastics, artificial marble or onyx, polymer concrete, or gel coats. The main areas of UPR consumption include the wind energy, marine, pipe and tank, transportation, and construction industries. This chapter discusses basic UPR and VER chemistry and technology of manufacturing, and consequent applications. Some important properties and performance characteristics are discussed, such as shrinkage behavior, flame retardance, and property modification by nanoparticles. Also briefly introduced and described are the practical aspects of UPR and VER processing, with special emphasis on the most widely used technological approaches, such as hand and spray layup, resin infusion, resin transfer molding, sheet and bulk molding, pultrusion, winding, and centrifugal casting.
Unsaturated polyester resins (UPR) and vinyl ester resins (VER) are among the most commercially important thermosetting matrix materials for composites. Although comparatively low cost, their technological performance is suitable for a wide range of applications, such as fiber-reinforced plastics, artificial marble or onyx, polymer concrete, or gel coats. The main areas of UPR consumption include the wind energy, marine, pipe and tank, transportation, and construction industries.
This chapter discusses basic UPR and VER chemistry and technology of manufacturing, and consequent applications. Some important properties and performance characteristics are discussed, such as shrinkage behavior, flame retardance, and property modification by nanoparticles. Also briefly introduced and described are the practical aspects of UPR and VER processing, with special emphasis on the most widely used technological approaches, such as hand and spray layup, resin infusion, resin transfer molding, sheet and bulk molding, pultrusion, winding, and centrifugal casting.
Twitter and citations
(2023)
Social media, especially Twitter, plays an increasingly important role among researchers in showcasing and promoting their research. Does Twitter affect academic citations? Making use of Twitter activity about columns published on VoxEU, a renowned online platform for economists, we develop an instrumental variable strategy to show that Twitter activity about a research paper has a causal effect on the number of citations that this paper will receive. We find that the existence of at least one tweet, as opposed to none, increases citations by 16-25%. Doubling overall Twitter engagement boosts citations by up to 16%.
Industrial practice is characterized by random events, also referred to as internal and external turbulences, which disturb the target-oriented planning and execution of production and logistics processes. Methods of probabilistic forecasting, in contrast to single value predictions, allow an estimation of the probability of various future outcomes of a random variable in the form of a probability density function instead of predicting the probability of a specific single outcome. Probabilistic forecasting methods, which are embedded into the analytics process to gain insights for the future based on historical data, therefore offer great potential for incorporating uncertainty into planning and control in industrial environments. In order to familiarize students with these potentials, a training module on the application of probabilistic forecasting methods in production and intralogistics was developed in the learning factory 'Werk150' of the ESB Business School (Reutlingen University). The theoretical introduction to the topic of analytics, probabilistic forecasting methods and the transition to the application domain of intralogistics is done based on examples from other disciplines such as weather forecasting and energy consumption forecasting. In addition, data sets of the learning factory are used to familiarize the students with the steps of the analytics process in a practice-oriented manner. After this, the students are given the task of identifying the influencing factors and required information to capture intralogistics turbulences based on defined turbulence scenarios (e.g. failure of a logistical resource) in the learning factory. Within practical production scenario runs, the students apply probabilistic forecasting using and comparing different probabilistic forecasting methods. The graduate training module allows the students to experience the potentials of using probabilistic forecasting methods to improve production and intralogistics processes in context with turbulences and to build up corresponding professional and methodological competencies.
In countries such as Germany, where municipalities have planning sovereignty, problems of urban sprawl often arise. As the dynamics of land development have not substantially subsided over the last years, the national government decided to test the instrument of ‘Tradable Planning Permits’ (TPP) in a nationwide field experiment with 87 municipalities involved. The field experiment was able to implement the key features of a TPP system in a laboratory setting with approximated real socioeconomic and planning conditions. In a TPP system allocated planning permits must be used by municipalities for developing land. The permits can be traded between local jurisdictions, so that they have flexibility in deciding how to comply with the regulation. In order to evaluate the performance of such a system, specific field data about future building areas and their impact on community budgets for the period 2014–2028 were collected. The field experiment contains several sessions with representatives of the municipalities and with students. The participants were confronted with two (municipalities) and four (students) schemes. The results show that a trading system can curb down land development in an effective and also efficient manner. However, depending on the regulatory framework, the trading schemes show different price developments and distributional effects. The unexperienced representatives of the local authorities can easily handle with the permits in the administration and in the established market. A trading scheme sets very high incentives to save open space and to direct development activities to areas within existing planning boundaries. It is therefore a promising instrument for Germany and also other regions or countries with an established land-use planning system.
Towards a model for holistic mapping of supply chains by means of tracking and tracing technologies
(2022)
The usage of tracking and tracing technologies not only enables transparency and visibility of supply chains but also offers far-reaching advantages for companies, such as ensuring product quality or reducing supplier risks. Increasing the amount of shared information supports both internal and external planning processes as well as the stability and resilience of globally operating value chains. This paper aims to differentiate and define the functionalities of tracking and tracing technologies that are frequently used interchangeably in literature. Furthermore, this paper incorporates influencing factors impacting a sequencing of the connected world in Industry4.0 supply chain networks. This includes legal influences, the embedment of supply chain-related standards, and new possibilities of emerging technologies. Finally, the results are summarized in a model for the holistic mapping of supply chains by means of tracking and tracing technologies. The resulting technological solutions that can be derived from the model enable companies to address missing elements in order to enable the holistic mapping of supply chain events as well as the transparent representation of a digital shadow throughout the entire supply chain.
Instead of waiting for and constantly adapting to details of political interventions, utilities need to focus on their environment from a holistic perspective. The unique position of the company - be it a local utility, a bigger player, or an international utility specializing in specitic segments - has to be the basis of goals and strategies. But without consistent translation of these goals and strategies into processes, structures, and company culture, a strategy remains pure theory. Companies need to engage in a continuing learning process. This means being willing to pass on strategies, to slow down or speed up, to work from a different angle etc.
The data presented in this article characterize the thermomechanical and microhardness properties of a novel melamine-formaldehyde resin (MF) intended for the use as a self-healing surface coating. The investigated MF resin is able to undergo reversible crosslinking via Diels Alder reactive groups. The microhardness data were obtained from nanoindentation measurements performed on solid resin film samples at different stages of the self-healing cycle. Thermomechanical analysis was performed under dynamic load conditions. The data provide supplemental material to the manuscript published by Urdl et al. 2020 (https://doi.org/10.1016/j.eurpolymj.2020.109601) on the self-healing performance of this resin, where a more thorough discussion on the preparation, the properties of this coating material and its application in impregnated paper-based decorative laminates can be found.
In the course of a more intensive energy generation from regenerative sources, an increased number of energy storages is required. In addition to the widespread means of storing electric energy, storing energy thermally can contribute significantly. However, limited research exists on the behaviour of thermal energy storages (TES) in practical operation. While the physical processes are well known, it is nevertheless often not possible to adequately evaluate its performance with respect to the quality of thermal stratification inside the tank, which is crucial for the thermodynamic effectiveness of the TES. The behaviour of a TES is experimentally investigated in cyclic charging and discharging operation in interaction with a cogeneration (CHP) unit at a test rig in the lab. From the measurements the quality of thermal stratification is evaluated under varying conditions using different metrics such as normalised stratification factor, modified MIX number, exergy number and exergy efficiency, which extends the state of art for CHP applications. The results show that the positioning of the temperature sensors for turning the CHP unit on and off has a significant influence on both the effective capacity of a TES and the quality of thermal stratification inside the tank. It is also revealed that the positioning of at least one of these sensors outside the storage tank, i.e. in the return line to the CHP unit, prevents deterioration of thermal stratification, thereby enhancing thermodynamic effectiveness. Furthermore, the effects of thermal load and thermal load profile on effective capacity and thermal stratification are discussed, even though these are much smaller compared to the effect of positioning the temperature sensors.
Theory and practice of implementing a successful enterprise IoT strategy in the industry 4.0 era
(2021)
Since the arrival of the internet and affordable access to technologies, digital technologies have occupied a growing place in industries, propelling us towards a 4th industrial revolution: Industry 4.0. In today’s era of digital upheaval, enterprises are increasingly undergoing transformations that are leading to their digitalization. The traditional manufacturing industry is in the throes of a digital transformation that is accelerated by exponentially growing technologies (e.g., intelligent robots, Internet of Things, sensors, 3D printing). Around the world, enterprises are in a frantic race to implement solutions based on IoT to improve their productivity, innovation, and reduce costs and improve their markets on the international scene. Considering the immense transformative potential that IoTs and big data have to bring to the industrial sector, the adoption of IoT in all industrial systems is a challenge to remain competitive and thus transform the industry into a smart factory. This paper presents the description of the innovation and digitalization process, following the Industry 4.0 paradigm to implement a successful enterprise IoT strategy.
We investigated the state of artificial intelligence (AI) in pharmaceutical research and development (R&D) and outline here a risk and reward perspective regarding digital R&D. Given the novelty of the research area, a combined qualitative and quantitative research method was chosen, including the analysis of annual company reports, investor relations information, patent applications, and scientific publications of 21 pharmaceutical companies for the years 2014 to 2019. As a result, we can confirm that the industry is in an ‘early mature’ phase of using AI in R&D. Furthermore, we can demonstrate that, despite the efforts that need to be managed, recent developments in the industry indicate that it is worthwhile to invest to become a ‘digital pharma player’.