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Page 208 of 977 Results 2071 - 2080 of 9762

Michael Schmitz, Rainer Stark
Integration of Automated Structure Mechanic Analyses into Production Process Simulation

To produce individual variants of a given product, each variant has to be assessed with respect to their mechanical integrity. This is usually done in the course of product design by assessing all required variants. However, during the lifetime of a product several changes of the existing variants occur or new variants will be created. In this paper a method is described how to integrate and automate the assessment of the mechanical integrity of the product variants directly into the production process by exploiting modern computer methods and automated set-up of state-of-the-art CAE methods. We show this on a demonstrator of a smart factory, that produces disks which can be customized to a large extend. The disks undergo a milling process, which alters the structural properties of the disks. Generally, it cannot be guaranteed upfront that a variant that can be produced is also strong enough to withstand the loads in the application. Therefore, the integrated FEM analyses are computing and assessing the load cases deduced from the use cases of the disks and the loads that occur during milling and handling in the factory. The assessment of the results is done automatically and if positive the production process is started.

Maik Frye, Robert Heinrich Schmitt
Quality Improvement of Milling Processes Using Machine Learning-Algorithms

The increasing digitalization and industrial efforts towards artificial intelligence foster the use of Machine Learning (ML)-algorithms in the production environment. Within production, different application areas and use-cases arise for the usage of ML. In this paper, we focus on the implementation of ML- algorithms for a milling process where critical process conditions are predicted. Based on the predicted process conditions, the machining parameters can be adjusted in advance to avoid critical conditions of the process. The avoidance of critical process conditions increases the quality of the products, since quality characteristics such as surface roughness or dimensional deviations can be influenced. To ensure the transferability of the results to other applications, we follow a methodical approach. The results of the ML- models are discussed critically and further steps are derived in order to use ML-models successfully in the future.

Michy Alice, Dejan Pejovski, Loredana Cristaldi
Remaining Useful Life Estimation of Industrial Circuit Breakers by Data-Driven Prognostic Algorithms Based on Statistical Similarity and Copula Correlation

Predicting the future behaviour of an item or a complex system based on its past history is the aim of data-driven algorithms. In our paper, we present two algorithms for predicting the Remaining Useful Life (RUL) of industrial circuit breakers (CB) which make use of on-site collected data related to CB’s health condition. In the first algorithm, a sub- fleet of CBs is identified by applying the two-sample Kolmogorov-Smirnov Test which relies on statistical similarity between the observations. Once chosen the sub-fleet, the algorithm attempts to exploit correlations between the variation of health condition and sampling time using copulas. The second algorithm models the correlation structure between the time at which a certain degradation level occurs and the item’s End of Life (EOL). Both algorithms are used to estimate the item’s Remaining Useful Life through the Monte Carlo method. The use of copulas attempts to exploit also the information on the correlation structure in the data in order to obtain a higher accuracy in the estimation.

Lukas Lingitz, Alexander Gaal, Thomas Ryback, Viola Gallina
Improving the Planning Quality in Production Planning and Control with Machine Learning

There are always deviations between production planning and subsequent execution. These deviations are caused by uncertainties, e.g. inaccurate or insufficient planning data (e.g. data quality and availability), inappropriate planning and control systems or unforeseeable events. Production planners therefore use buffers in the form of inventories or extended transitional periods to create possibilities for implementing corrective measures in production control. Buffers, however, lead to increased coordination and control effort and to negative effects, e.g. on inventory, throughput time and capacity utilization. Furthermore, it was found that the reliability of the production plans and thus the planning quality (PQ) can drop down to 25% in the first three days after plan creation [1]. Potentials for more accurate planning remains largely unexploited. The objective of this paper is to investigate the possibilities to increase planning quality. Two approaches are presented, focusing on reducing gaps between master data and predicted data used during the production planning process.

Sergey Muravyov, Liudmila Khudonogova
A consensus ranking based proposal for combining data in adjustment of the fundamental physical constant values

To ensure the traceability of testing and diagnostic equipment it is necessary to provide a chain of comparisons connecting the equipment with primary standards of the SI units based on fundamental physical constants. The values of the constants are regularly determined by an adjustment procedure which requires consistency of input data and an assumed statistical model. In this paper, it is proposed to apply the developed interval fusion with preference aggregation (IF&PA) method for combining data and determining a consensus value of a fundamental constant. Due to its high robustness, accuracy and reliability confirmed by the numerical experimental results, the IF&PA does not require a consistency check and works well without using any statistical assumptions. Usage of the IF&PA is demonstrated by example of processing the simulated interval data and real values of the Planck constant used in the adjustment in 2006 and 2017. The outcome comparison with the estimates obtained by other methods, including the procedures based on Birge ratio, modified Birge ratio, random effects model and fixed effects model, is carried out.

L. L. Martins, M. C. Almeida, A. S. Ribeiro
Challenges of dimensional quantification in CCTV inspection in drain and sewer systems

This paper addresses the metrological quality of dimensional measurements based on images obtained from CCTV inspections in drain and sewer systems. In this type of indirect visual inspection, a significant number of absolute and relative dimensional quantities can be quantified, contributing to the characterization of the observations and, consequently, to the analysis of performance of drain and sewer systems outside buildings.
Unfavourable environmental factors and conditions within the drain or sewer components affect estimation of the quantities of interest and the quality of the recorded images (lighting, lack of reference points, geometric irregularities and subjective assessments, among others). Quantification improvement of the dimensional quantities is a key objective to achieve a better value from these inspections. This study contributes to improve the quality of the dimensional measurements by defining experimental procedures, which can be applied to the optical systems used in CCTV inspection.
The paper describes the European normative framework for these inspection activities and proposes approaches aiming at increasing confidence in the dimensional measurements, based on the metrological characterization of the optical systems used, as well as their integration in a traceability chain. Results presented and discussed include the evaluation of measurement uncertainty.

Yukio Hiranaka
Multiple Heat Source Estimation by using Backward Simulator

The exact inverse solutions for real measurements are becoming realistic with the progress of computational performances. As an example, heat generation and release transients can be estimated from the temperature measurement if the thermal model is known. Although the inverse solver needs the correct knowledge of the target model, the method of backward simulation has a capability of determining the model structure and the model parameters by itself. A simple case of one heat source model has been shown as a successful example. In this paper, we describe an application of the method to a two heat source case, and show its result for a simulated temperature data.

Giuliano Cipolletta, Antonio Delle Femine, Daniele Gallo, Carmine Landi, Mario Luiso
Design Approach for a Stand Alone Merging Unit

In order to enhance levels of security and reliability of power systems, allowing for advanced remote diagnostics, Merging Units (MUs) play a key role. Some of the benefits are a more efficient transmission of electricity and a better integration with renewable energy systems. In this paper an implementation of a Stand Alone Merging Unit (SAMU), compliant with the IEC 61850-9-2 standard and based on a low cost ARM microcontroller, is described. It acquires two signals, one voltage and one current, and it sends the samples over the Ethernet connection. A high-resolution analog to digital converter (ADC), synchronized to the Universal Time coordinated (UTC) through a Global Positioning System (GPS) disciplined oscillator, is used. The results of the characterization of the ADC are presented.

Yeying Chen, Giovanni D'Avanzo, Antonio Delle Femine, Daniele Gallo, Carmine Landi, Mario Luiso, Enrico Mohns
Metrological Performances of Current Transformers Under Amplitude Modulated Currents

All the measurement tasks, f.i. metering, protection and diagnostics, in electricity distribution and trasmission grids need instrument transformers (ITs) to scale voltage and current down to levels compatible with measuring instruments. Inductive voltage and current transformers (VTs and CTs) are still the most used ITs; however, their behaviour in presence of disturbances is not fully assessed. This paper analyses the behavior of CTs in presence of amplitude modulations, which is one of the disturbance under which the performance of Phasor Measurement Units (PMUs) has to be assessed. A measurement setup, able to test current transformers in accordance to the IEEE Std. C37.118.1 about the PMU performance testing, has been realized. Experimental tests on a commercial CT, changing the modulation frequency, are presented.

László Móricz, Zsolt János Viharos, András Németh, András Szépligeti
Product quality and cutting tool analysis for micro-milling of ceramics

Based on their favourable mechanical features, applications of ceramics are continuously spreading in industrial environment. Such a good feature is their resistance against heat shock, so, currently they are applied e.g. as coating material for gas turbines. The main aims of the paper to follow the wearing process of the micro-milling tool during machining of ceramics and to compare it against the geometrical changes of the machined ceramic workpiece, applied as a special monitoring technique.

Page 208 of 977 Results 2071 - 2080 of 9762