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Dieses Buch hilft Ihnen, die Methodik FMEA sowie die angrenzenden Themen zu verstehen und anzuwenden. Es räumt mit dem Vorurteil auf, FMEA wäre „nur“ ein Qualitätstool, das von Qualitätsspezialisten durchgeführt wird. Vielmehr kann die FMEA in jeder Branche als Werkzeug benutzt werden, um Produkte, Projekte, Aufgaben und Dienstleistungen äußerst planbar, nachvollziehbar und zielorientiert umzusetzen. Das strukturierte Vorgehen unterstützt Problemlösungen und schafft somit neue Denkansätze (präventive Qualitätssicherungsmethodik und Risikoanalyse). Bei richtiger Anwendung werden Sie Zeit, Geld und Kapazität einsparen. Der Inhalt Einführung in das Thema – Methodik Grundlagen – Moderationstechnik – nachhaltige Einführung im Betrieb – Stolpersteine in der Praxis (oder: Wie bringe ich eine FMEA sicher zum Scheitern) – Software – Produkthaftung in Deutschland – Methoden und Begriffe im Umfeld – Tipps, Tricks und Tools – Vision Die Zielgruppe Entwickler und Planer aller Bereiche und Branchen, in denen Risikobetrachtungen notwendig sind, vor allem in Entwicklungsbereichen der Automobil-, Luft- und Raumfahrtindustrie sowie der Medizintechnik Richter und Anwälte, die sich mit Produkthaftung beschäftigen Der Herausgeber Dipl.-Ing. Martin Werdich absolvierte an der FH Weingarten sein Studium zum Maschinenbauingenieur. Er war mehrere Jahre als Entwickler und Projektleiter in renommierten Firmen tätig. Seit 2006 führt er ein Ingenieurbüro (www.werdichengineering.de) mit Fokus auf Moderation von FMEA Projekten bei namhaften internationalen Konzernen. Des Weiteren ist er FMEA- Methodentrainer und hält Vorträge auf Expertenforen.

Quality control. --- Reliability. --- Industrial safety. --- Electrical engineering. --- Engineering economics. --- Engineering economy. --- Quality Control, Reliability, Safety and Risk. --- Electrical Engineering. --- Engineering Economics, Organization, Logistics, Marketing. --- Failure mode and effects analysis. --- Engineering.

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Fracture mechanics --- Mécanique de la rupture --- 539.42 --- breukmechanica --- fmea (failure mode and effects analysis) --- geometrie --- scheurdetectie --- scheurgedrag --- scheurgroei --- Failure of solids --- Fracture of materials --- Fracture of solids --- Materials --- Mechanics, Fracture --- Solids --- Deformations (Mechanics) --- Strength of materials --- Brittleness --- Penetration mechanics --- Structural failures --- Breakage. Structural fracture. Tensile strength. Breaking strength --- (zie ook: fouten-analyse) --- Fracture --- Fatigue --- 539.42 Breakage. Structural fracture. Tensile strength. Breaking strength --- Mécanique de la rupture

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In an effort to contribute to global efforts by addressing the marine pollution from various emission types, this Special Issue of Ship Lifecyle for Journal of Marine Science and Engineering was inspired to provide a comprehensive insight for naval architects, marine engineers, designers, shipyards, and ship-owners who strive to find optimal ways to survive in competitive markets by improving cycle time and the capacity to reduce design, production, and operation costs while pursuing zero emission. In this context, this Special Issue is devoted to providing insights into the latest research and technical developments on ship systems and operation with a life cycle point of view. The goal of this Special Issue is to bring together researchers from the whole marine and maritime community into a common forum to share cutting-edge research on cleaner shipping. It is strongly believed that such a joint effort will contribute to enhancing the sustainability of the marine and maritime activities. This Special Issue features six novel publications dedicated to this endeavor. First of all, as a proactive response to transitioning to cleaner marine fuel sources, numerous aspects of the excellence of fuel-cell based hybrid ships were demonstrated through four publications. In addition, two publications demonstrated the effectiveness of life cycle assessment (LCA) applicable to marine vessels.

electric propulsion system --- DFE rectifier --- AFE rectifier --- phase angle detector --- hybrid power source --- fuel cell --- molten carbonate fuel cell (MCFC) --- carbon dioxide --- Molten carbonate fuel cell (MCFC) --- Hybrid test bed --- Operation profile --- Power quality --- life cycle --- maintenance costs --- propulsion system maintenance --- research vessel --- LNG-fueled ship --- IMO GHG --- LNG --- MGO --- LCA --- marine fuel --- hybrid power system --- failure mode and effects analysis --- risk priority number --- ship safety --- Kendall’s coefficient --- life cycle assessment (LCA), maritime environment --- sustainable production and shipping --- CO2 emissions --- NOx emissions --- SOx emissions

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This book reports recent advances on Process Monitoring (PM) to cope with the many challenges raised by the new production systems, sensors and “extreme data” conditions that emerged with Industry 4.0. Concepts such as digital-twins and deep learning are brought to the PM arena, pushing forward the capabilities of existing methodologies to handle more complex scenarios. The evolution of classical paradigms such as Latent Variable modeling, Six Sigma and FMEA are also covered. Applications span a wide range of domains such as microelectronics, semiconductors, chemicals, materials, agriculture, as well as the monitoring of rotating equipment, combustion systems and membrane separation processes.

Technology: general issues --- spatial-temporal data --- pasting process --- process image --- convolutional neural network --- Industry 4.0 --- auto machine learning --- failure mode effects analysis --- risk priority number --- rolling bearing --- condition monitoring --- classification --- OPTICS --- statistical process control --- control chart pattern --- disruptions --- disruption management --- fault diagnosis --- construction industry --- plaster production --- neural networks --- decision support systems --- expert systems --- failure mode and effects analysis (FMEA) --- discriminant analysis --- non-intrusive load monitoring --- load identification --- membrane --- data reconciliation --- real-time --- online --- monitoring --- Six Sigma --- multivariate data analysis --- latent variables models --- PCA --- PLS --- high-dimensional data --- statistical process monitoring --- artificial generation of variability --- data augmentation --- quality prediction --- continuous casting --- multiscale --- time series classification --- imbalanced data --- combustion --- optical sensors --- spectroscopy measurements --- signal detection --- digital processing --- principal component analysis --- curve resolution --- data mining --- semiconductor manufacturing --- quality control --- yield improvement --- fault detection --- process control --- multi-phase residual recursive model --- multi-mode model --- process monitoring --- n/a

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This book reports recent advances on Process Monitoring (PM) to cope with the many challenges raised by the new production systems, sensors and “extreme data” conditions that emerged with Industry 4.0. Concepts such as digital-twins and deep learning are brought to the PM arena, pushing forward the capabilities of existing methodologies to handle more complex scenarios. The evolution of classical paradigms such as Latent Variable modeling, Six Sigma and FMEA are also covered. Applications span a wide range of domains such as microelectronics, semiconductors, chemicals, materials, agriculture, as well as the monitoring of rotating equipment, combustion systems and membrane separation processes.

Technology: general issues --- spatial-temporal data --- pasting process --- process image --- convolutional neural network --- Industry 4.0 --- auto machine learning --- failure mode effects analysis --- risk priority number --- rolling bearing --- condition monitoring --- classification --- OPTICS --- statistical process control --- control chart pattern --- disruptions --- disruption management --- fault diagnosis --- construction industry --- plaster production --- neural networks --- decision support systems --- expert systems --- failure mode and effects analysis (FMEA) --- discriminant analysis --- non-intrusive load monitoring --- load identification --- membrane --- data reconciliation --- real-time --- online --- monitoring --- Six Sigma --- multivariate data analysis --- latent variables models --- PCA --- PLS --- high-dimensional data --- statistical process monitoring --- artificial generation of variability --- data augmentation --- quality prediction --- continuous casting --- multiscale --- time series classification --- imbalanced data --- combustion --- optical sensors --- spectroscopy measurements --- signal detection --- digital processing --- principal component analysis --- curve resolution --- data mining --- semiconductor manufacturing --- quality control --- yield improvement --- fault detection --- process control --- multi-phase residual recursive model --- multi-mode model --- process monitoring --- spatial-temporal data --- pasting process --- process image --- convolutional neural network --- Industry 4.0 --- auto machine learning --- failure mode effects analysis --- risk priority number --- rolling bearing --- condition monitoring --- classification --- OPTICS --- statistical process control --- control chart pattern --- disruptions --- disruption management --- fault diagnosis --- construction industry --- plaster production --- neural networks --- decision support systems --- expert systems --- failure mode and effects analysis (FMEA) --- discriminant analysis --- non-intrusive load monitoring --- load identification --- membrane --- data reconciliation --- real-time --- online --- monitoring --- Six Sigma --- multivariate data analysis --- latent variables models --- PCA --- PLS --- high-dimensional data --- statistical process monitoring --- artificial generation of variability --- data augmentation --- quality prediction --- continuous casting --- multiscale --- time series classification --- imbalanced data --- combustion --- optical sensors --- spectroscopy measurements --- signal detection --- digital processing --- principal component analysis --- curve resolution --- data mining --- semiconductor manufacturing --- quality control --- yield improvement --- fault detection --- process control --- multi-phase residual recursive model --- multi-mode model --- process monitoring