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Since assembly processes are continuously increasing in complexity due to the growing number of product variants, the importance of digital assistance systems for handling complexity is growing to support human work in a suitable manner. However, the configuration of the assistance system for the increasing number of product variants can be particularly complex and time consuming. This paper therefore presents a concept to support the implementation of new product variants in existing digital assistance systems in a data-based approach by facilitating the process. Thus, an approach for possible support options depending on the individual data management of companies is identified and presented. The developed approach is examined on a conceptual level which is generally applicable. Finally, to identify the most suitable support within the presented approach, a benefit-oriented evaluation is derived as an outlook.

Die Diversifikation von Produkten erhöht die Komplexität in der Produktion, wodurch die Anforderungen an die Beschäftigten steigen. Durch den Einsatz digitaler Assistenzsysteme kann die menschliche Arbeit in der Produktion unterstützt werden. Dieser Beitrag beschäftigt sich mit den relevanten Funktionen eines digitalen Assistenzsystems als Diskussionsgrundlage bei deren Einführung. The diversification of products makes production more complex and jobs more demanding. Digital assistance systems can support human work in the production area. This article deals with the relevant functions of a digital assistance system as a basis for discussion when implementing them.

Introduction Transverse fractures of the olecranon are commonly fixed using tension-band wiring techniques. However the superficial nature of this area leads to high complication rates requiring removal of metalwork. The purpose of this retrospective study is to report and evaluate functional outcomes of polyethylene tension-band and bioabsorbable Magnesium alloy screw fixation of olecranon fractures. Methods A retrospective case-control study was undertaken. Demographics, injury type and post-operative details were collected. All patients were treated in the same institution by a single surgeon. Primary outcomes included radiographic healing and post-operative range of motion. Secondary outcome was post-operative complications. Results A total of five cases were identified. Mean age was 52.4. The control group was made up of six patients treated with a traditional tension band wire fixation. One patient in study group was lost to follow up. 80% of fractures in study group demonstrated anatomic post-operative radiographic union, compared with 83% of control group. All patients had range of motion above 100°, with full protonation and supination. One patient did have an extension lag of 15°. Conclusion Surgical repair of olecranon fractures is often complicated by the need for re-operation. This method provides both intramedullary fixation and conversion of distraction forces to compression forces with bioabsorbable materials, and aims to reduce the high re-operation rates commonly seen by avoiding the use of permanent indwelling metal hardware.

Many machine learning algorithms depend on the choice of an appropriate similarity or distance measure. Comparing such measures in different domains and on diversely structured data is common, but often performed in regards of an algorithm to cluster or classify the data. In this study, data assessed by experts is analyzed instead. The data is taken from the database of the Federal Institute for Drugs and Medical Devices (BfArM) and represents free text incident reports. The Average Silhouette Width, a cluster density measure, is used to compare the distance measures’ ability to discriminate the data according to the experts’ assessments. The Euclidean distance and four distance measures derived from the Jaccard similarity, the Simple Matching similarity, the Cosine similarity and the Yule similarity are compared on four subsets of this database. The results show, that a better data preprocessing is necessary, possibly due to boilerplate texts being used to write incident reports. These results will also provide the basis to compare improvements by different methods of data preprocessing in the future.

Data Analytics and derived Data Mining are powerful approaches for the analysis of Big Data. There are a lot of commercial Data Analytics applications enterprises can take advantage of. In the past, many firms were still critical of Data Analytics. Through efforts made in the field of the establishment of process standards, managers might be convinced of Data Analytics advantages. Many small and medium-sized organizations are still exempt from this development. The main reasons are a lack of business prioritization, a lack of (IT) knowledge, and a lack of overview of Data Analytics issues. To reduce that problem, we developed a useful process framework. It resembles with existing frameworks, but is highly simplified and easy to use. To exemplify, how this framework can be put into action by the means of a retail site location analysis, we set up a case study as best practice. There we are focusing on Data Mining because it is the most important domain of Data Analytics.

Active condition monitoring of automation systems is a strongly emerging topic. In this paper a purely data-driven approach is presented which allows for detection of wear-out or faulty situations in machine subsystems, each consisting of a servomotor driving different parts of the machine. The approach is based on empirical analysis of the motor's electric currents, but can be applied to the tracking errors of the servo controller as well. The features gained from the spectra of the motor currents or tracking errors, respectively, are reduced by singular value decomposition and classified by a kernel density based algorithm. Because of the purely data-driven approach the method can also be applied to a variety of different systems.

This paper develops a tractable dynamic microeconomic model of migration decisions that is aggregated to describe the behavior of interregional migration. Our structural approach allows us to deal with dynamic self-selection problems that arise from the endogeneity of location choice and the persistency of migration incentives. Keeping track of the distribution of migration incentives over time has important consequences for the econometrical treatment, because the dynamics of this distribution influences the estimation of structural parameters, such as migration costs. For US interstate migration, we obtain a cost estimate of less than one-half of an average annual household income. This is substantially smaller than the migration costs estimated by previous studies. We attribute this difference to the treatment of the dynamic self-selection problem.

Study Type – Diagnostic (non-consecutive cohort without consistently applied reference standard) Level of Evidence 3b What's known on the subject? and What does the study add? The prognosis of bladder cancer significantly depends on tumour stage and time of diagnosis so early diagnosis is desirable to decrease mortality and treatment costs. The NMP22 test is approved for clinical application by the Food and Drug Administration (FDA) of the US. Previous studies have reported values of 47–100% for sensitivity and 58–91% for specificity with this test, but there is no new data on the predictive value of NMP22 for screening bladder cancer (BC). The most important risk factor for BC is the tobacco consumption but occupational exposure to carcinogenic substances, especially aromatic amines, is regarded as another risk factor. The UroScreen study is a prospective longitudinal study for the early detection of BC. To our knowledge, it is the largest prospective validation study conducted over the longest period of time. The study results led us to conclude that, based on the currently available data, NMP22 should not be regarded as an alternative to endoscopy, and we could not make a general recommendation for screening or follow-up. The UroScreen results indicate that urine-based molecular markers could be a suitable addition to urine cytology and the detection of microhaematuria. OBJECTIVE • To evaluate the value of nuclear matrix protein-22 (NMP22) in bladder cancer (BC) screening, and its effect on variables in a prospective study in a high-risk population. PATIENTS AND METHODS • A total of 1772 chemical workers (mean age 62 years) exposed to carcinogenic aromatic amines were enrolled in the study. • In all, 7091 screening check-ups in 1609 subjects were performed. • Urine samples were collected for a quantitative NMP22 immunoassay, urine analysis and creatinine concentration assessment. • Cystoscopy and subsequent transurethral resection were performed where there were suspicious findings. RESULTS • Histopathological analysis found three papillary urothelial neoplasms of low malignant potential, five recurrent BCs and 13 primary BCs. Three tumours were at a muscle-invasive stage (pT2, pT3a or pT3b). • We found higher NMP22 concentrations (>10 U/mL) in 224 patients, which correctly predicted BC in six cases (sensitivity 97.29%, specificity 28.57%; negative predictive value 99.04%, positive predictive value 12.24%). • Gross haematuria affected NMP22 results (odd ratio [OR] 3.49, 95% confidence interval [CI] 1.81–6.73). Infection also affected NMP22 results (OR 4.13, 95% CI 2.31–7.35). • NMP22 was more frequently positive in urine with creatinine concentration >2.5 g/L (OR 1.61, 95% CI 0.91–2.86). CONCLUSIONS • NMP22 outcomes are affected by haematuria, infection and concentrated urine. • NMP22 alone cannot be recommended for primary screening in a high-risk population nor as an alternative to cystoscopy during follow-up. • A NMP22 test might be a useful adjunct to urine cytology.

We analyse the relation of firm performance and managerial turnover in 19th century German banking by probit estimation. This period covers a major reform of corporate governance. Before the reform performance and turnover were unrelated, whereas after the reform more successful managers left firms more seldom. However, only short-run performance matters in this turnover–success relationship.

This paper reports on the measurements of the near-wall turbulence statistics in a fully developed channel flow. The flow measurements were carried out with a novel laser Doppler velocity profile sensor with a high spatial resolution. The sensor provides both the information of velocity and position of individual tracer particles inside the measurement volume. Hence, it yields the velocity profile inside the measurement volume, in principle, without the sensor being mechanically traversed. Two sensor systems were realized with different techniques. Typically the sensor has a relative accuracy of velocity measurement of 10 −3 and the spatial resolution of a few micrometers inside the measurement volume of about 500 μm long. The streamwise velocity was measured with two independent sensor systems at three different Reynolds number conditions. The resulting turbulence statistics show a good agreement with available data of direct numerical simulations up to fourth order moment. This demonstrates the velocity profile sensor to be one of the promising techniques for turbulent flow research with the advantage of a spatial resolution more than one magnitude higher than a conventional laser Doppler technique.

This paper reports about the first application of a laser Doppler velocity profile sensor for precise flow rate measurements of natural gas under high pressure. The profile sensor overcomes the limitations of conventional laser Doppler anemometry (LDA) namely the effect of spatial averaging and the effect of fringe spacing variation (virtual turbulence). It uses two superposed, fan-like interference fringe systems to determine the axial position of a tracer particle inside the LDA’s measurement volume. Consequently, a spatial resolution of about 1 μm can be achieved and the effect of virtual turbulence is nearly eliminated. These features predestine the profile sensor for flow rate measurements with high precision. Velocity profile measurements were performed at the German national standard for natural gas, one of the world′s leading test facilities for precision flow rate measurements. As a result, the velocity profile of the nozzle flow could be resolved more precisely than with a conventional LDA. Moreover, the measured turbulence intensity of the core flow was of 0.14% mean value and 0.07% minimum value, which is significantly lower than reference measurements with a conventional LDA. The paper describes the performed measurements, gives a discussion and shows possibilities for improvements. As the main result, the goal of 0.1% flow rate uncertainty seems possible by an application of the profile sensor.

Es werden ein auf der Laser-Doppler-Anemometrie basierender neuartiger interferometrischer Sensor und entsprechende Konzepte zur Signalverarbeitung vorgestellt. Der Sensor ermöglicht es, entlang einer Linie das Geschwindigkeitsprofil von Strömungen mit einer Ortsauflösung bis in den Sub-Mikrometerbereich zu vermessen und eignet sich deshalb besonders für Turbulenzforschung, Mikrofluidik und Durchflussmessungen. Die Kombination zweier solcher Sensoren erlaubt die Bestimmung von drei Geschwindigkeitskomponenten innerhalb eines zweidimensionalen Bereichs ohne Verwendung einer Kamera und bietet aufgrund der geringen Messunsicherheit Vorteile gegenüber abbildenden Verfahren.

Systems for process automation become increasingly complex and also tend to be composed of autonomous subsystems, which is strongly driven by the progress made in information technology. An active field of research is the implementation of monitoring and control at sub-system level using cognitive approaches. In this paper we present a method for autonomous and sensorless condition monitoring of an electric drive train. Based on experiment design we measured phase currents of a physical demonstrator device including mechanical defects and extracted signal features using proper orthogonal decomposition. In favor of classification of different defect states we performed a linear discriminant analysis, which yields appropriate data for a Fuzzy-Pattern-Classification algorithm. As a result we were able to identify different reference defect states as well as previously unknown states.

In this contribution, a model of a drum motor is presented. This model was designed for description of dynamic behaviour of the drum motor as well as for the possible implementation of several wearing phenomena. Using this model, a better understanding of wear and tear phenomena has been achieved by carrying out a considerable number of simulation runs using different operational and wearing conditions. Using this information, important knowledge about detection of wearout signs was able to be gained. Often, mathematical models with different levels of detail are used. In these cases, it may be a difficult task to obtain reliable parameters. In this paper, we present three different approaches for establishing a model structure and for the determination of needed parameters. This way, we were able to define every part of the model with an appropriate level of detail and equip them with adequate parameter values.

Design of micro systems, MEMS or mechatronic systems is dominated by the interaction of effects from different physical domains. One important approach to decrease the number of design cycles significantly is system level modeling and simulation. The main challenges for the efficient use of modeling and simulation are a systematic approach for behavioral modeling, automated model generation as well as powerful simulation frameworks. Especially for the latter flexible handling of different models of computation is crucial.

Reliability of machines and facilities has played an important role since many years. Nowadays, attention is also paid to maintenance times. Maintenance standstills are to be reduced as far as possible. On the other hand, technical systems are subject to signs of wear and tear which are in general growing slowly and imperceptibly. The gradual abrasion of applied tools may lead to poor production tolerances or to a component’s standstill. Hence, a condition-based maintenance strategy will be of increasing importance. Such a strategy requires a permanent condition monitoring during operation. To this end, reliable high-performance algorithms for signal processing, feature extraction, and classification are needed. Modeling the process of wear and tear may be useful to find the particular steps of the condition monitoring system’s signal processing. This strategy was investigated by means of one very important device from automation engineering, a hydraulic axial piston pump. The procedure of getting signals by an appropriate Modelica model of the main parts of the pump is shown within the paper. Additionally, the manipulation process for the signals and the steps of classification are shortly presented to give an overview to the possibilities of model-based signal generation based on a Modelica model. The advantages of the multi-physics modeling language are emphasized because the axial piston pump model combines the mechanical and the hydraulic domain in a very efficient way.

Cubature methods, a powerful alternative to Monte Carlo due to Kusuoka [Adv. Math. Econ., 2004, 6, 69–83] and Lyons–Victoir [Proc. R. Soc. Lond. Ser. A, 2004, 460, 169–198], involve the solution to numerous auxiliary ordinary differential equations (ODEs). With focus on the Ninomiya–Victoir algorithm [Appl. Math. Finance, 2008, 15, 107–121], which corresponds to a concrete level 5 cubature method, we study some parametric diffusion models motivated from financial applications, and show the structural conditions under which all involved ODEs can be solved explicitly and efficiently. We then enlarge the class of models for which this technique applies by introducing a (model-dependent) variation of the Ninomiya–Victoir method. Our method remains easy to implement; numerical examples illustrate the savings in computation time.

We investigate photonic crystal waveguides that are formed by holes of reduced diameter within a hexagonal lattice of cylindrical airholes in thin freestanding silicon slabs. The waveguides operate in both an even-symmetry bandgap and a partial gap of odd-symmetry modes that form a complete two-dimensional bandgap under the light line. The operating frequency is tuned by the small-hole diameter to fit within the range of both bandgaps and to match a free-space wavelength of 1550 nm. Their narrow bandwidth and low group velocity of light propagation renders the waveguides useful as filters or sensing elements. Because of the strong dependence of the waveguide mode characteristics on structural changes, the highest-precision lithographic fabrication techniques must be applied.

This paper proposes to exploit a reform in legal rules of corporate governance to identify contractual incentives from the correlation of executive pay and firm performance. In particular, we refer to a major shift in the legal and institutional environment, the reform of the German joint-stock companies act in 1884. We analyze a sample of executive pay for 46 firms for the years 1870 to 1911. In 1884, a law reform substantially enhanced corporate control, strengthened the monitoring incentives of shareholders, and reduced the discretionary power of executives in Germany. Pay-performance sensitivity decreased significantly after this reform. While executives received a bonus of about three to five per cent in profits before 1884, after the reform this parameter decreased to a profit share of about two per cent. At least the profit share that is eliminated by the reform must have been incentive pay before. This incentive mechanism was replaced by other elements of corporate governance.

We report about a novel Laser-Doppler velocity profile sensor with high spatial resolution in the micrometer range. The sensor can be used for applications in fluid mechanics, e.g. flow measurements. Miniaturized sensors are often necessary to measure outside the laboratory. One approach utilizes a diffractive optical element (DOE) in order to reduce the number of optical elements. Another approach utilizes a frequency division multiplexing, where the frequency of multiple laser diode beams are controlled and superposed. Both approaches are discussed and compared.

Differences in regional unemployment rates are often used to describe regional economic inequality. This paper asks whether changes in regional unemployment differences in West Germany are persistent over time. Only if such changes are persistent, the differences are a sensible measure of inequality and only then can policies be effective that aim at lowering the dispersion of unemployment rates. Our analysis follows a time-series approach to economic convergence and we test whether unemployment differences between regions are stationary or not. While univariate tests show that changes in unemployment differences are persistent, more powerful panel tests find them to be only transitory. However, these tests reveal only a moderate speed of convergence. Since there is a structural break following the second oil crisis, we also employ unit-root tests that allow for such break. Again we find strong evidence for convergence and now also the speed of convergence is found to be very high. Both results, the presence of regime-wise conditional convergence in regional unemployment rates and fast equilibrium adjustment, have important implications for economic policy targeted at regional unemployment. On the one hand, small government interventions loose their effect quickly as unemployment rates adjust back to their equilibrium levels. On the other hand, large interventions might move the economy from one equilibrium of regional unemployment rates to the other. This means the policy intervention needs to take the form of a substantial regime shift. Most policies that aim at reducing relative unemployment differentials are unlikely to make permanent contributions to social welfare.

This paper analyzes the interaction of financial frictions and non-convex adjustment costs. Non-convex adjustment costs imply that firm-level investment is lumpy. Firms invest infrequently but each investment is large. This allows financial variables to influence investment along two margins. They can alter the size of the stock of capital a company wishes to hold in the long run or they can influence the frequency at which investment projects are undertaken. The empirical analysis of this paper reveals that finance has nearly no long-run influence on the stock of capital in a sample of German companies. By contrast, the influence of finance on investment decisions is substantial. Consequently, finance primarily affects investment frequencies and financial factors and fundamental capital productivity strongly interact in the determination of investment.

The present paper proposes to employ a major shift in the legal and institutional environment to identify contractual incentives from the correlation of executive pay and firm performance. We use the reform of the German stock companies act in 1884 as such a major shift and estimate the sensitivity of the pay to firm performance between 1870 and 1910 for executives of nine large banks. The reform substantially enhanced corporate control and strengthened monitoring incentives. Accordingly, we find the pay-performance sensitivity to decrease significantly after the reform. While executives received a bonus of 39 M per 1000 M increase in profits before 1884, after the reform the sensitivity decreased by two-thirds.

In this paper we present a laser sensor for highly spatially resolved flow imaging without using a camera. The sensor is an extension of the principle of laser Doppler anemometry (LDA). Instead of a parallel fringe system, diverging and converging fringes are employed. This method facilitates the determination of the tracer particle position within the measurement volume and leads to an increased spatial and velocity resolution compared to conventional LDA. Using a total number of four fringe systems the flow is resolved in two spatial dimensions and the orthogonal velocity component. Since no camera is used, the resolution of the sensor is not influenced by pixel size effects. A spatial resolution of 4 microm in the x direction and 16 microm in the y direction and a relative velocity resolution of 1x10(-3) have been demonstrated up to now. As a first application we present the velocity measurement of an injection nozzle flow. The sensor is also highly suitable for applications in nano- and microfluidics, e.g., for the measurement of flow rates.

For the investigation of turbulent flows, the measurement of Lagrangian acceleration is of great interest as it represents a direct component of the Navier–Stokes equations. The presented sensor is based on the common laser Doppler technique, but offers in addition combined high spatial resolution in the micrometre range and the possibility of measuring the velocity component along the optical axis. As a result of the sensor setup, signals of particles with inclined trajectories show frequency modulation within a single burst similar to the signal of an accelerated particle. A model-based approach to distinguish between both quantities is presented, and a signal processing technique based on the Hilbert transform has been developed. The processing is comparatively fast and showed good agreement with preset values, even for signals of poor quality. The variance of velocity and acceleration measurements nearly reaches the Cramer–Rao lower bound. Experimental verification is done by the measurement of a harmonic oscillator with known parameters and a stagnation flow within a free jet.

The permittivity of a ferroelectric n-type semiconductor varies smoothly with depth beneath a reversed biased Schottky contact. In partially depleted films, the depletion layer controls the capacitance. In fully depleted films the inverse capacitance is proportional to the thickness, which suggests that Schottky effects do not cause dead-layer behavior.