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Product-Focused Software Process Improvement: 22nd International Conference, PROFES 2021, Turin, Italy, November 26, 2021, Proceedings (Lecture Notes in Computer Science #13126)
by Andreas Jedlitschka Maurizio Morisio Marco Torchiano Luca ArditoThis book constitutes the refereed proceedings of the 22nd International Conference on Product-Focused Software Process Improvement, PROFES 2021, held in Turin, Italy, in November 2021. Due to COVID-19 pandemic the conference was held as a hybrid event. The 20 revised papers, including 14 full papers, 3 short papers and 3 industry papers, presented were carefully reviewed and selected from 48 submissions. The papers cover a broad range of topics related to professional software development and process improvement driven by product and service quality needs. They are organized in the following topical sections: agile and migration, requirements, human factors, and software quality.
Product-Focused Software Process Improvement: 23rd International Conference, PROFES 2022, Jyväskylä, Finland, November 21–23, 2022, Proceedings (Lecture Notes in Computer Science #13709)
by Marco Kuhrmann Pekka Abrahamsson Tommi Mikkonen Jil Klünder Davide TaibiThis book constitutes the refereed proceedings of the 23rd International Conference on Product-Focused Software Process Improvement, PROFES 2022, which took place in Jyväskylä, Finland in November 2022.The 24 full technical papers, 9 short papers, and 6 poster papers presented in this volume were carefully reviewed and selected from 75 submissions. The book also contains and 8 doctoral symposium papers and 7 tutorial and workshop papers.The contributions were organized in topical sections as follows: Keynote; Cloud and AI; Empirical Studies; Process Management; Refactoring and Technical Dept; Software Business and Digital Innovation; Testing and Bug Prediction; Posters; Tutorials; Workshop on Engineering Processes and Practices for Quantum Software (PPQS’22); 1st Workshop on Computational Intelligence and Software Engineering (CISE 2022); Doctoral Symposium.
Product-Focused Software Process Improvement: 24th International Conference, PROFES 2023, Dornbirn, Austria, December 10–13, 2023, Proceedings, Part I (Lecture Notes in Computer Science #14483)
by Andrea Janes Andreas Jedlitschka Valentina Lenarduzzi Xiaozhou Li Regine KadgienThis book constitutes the refereed proceedings of the 24th International Conference on Product-Focused Software Process Improvement, PROFES 2023, which took place in Dornbirn, Austria, in December 2023. The 21 full technical papers, 8 short papers, and 1 poster paper presented in this volume were carefully reviewed and selected from 82 submissions. The book also contains one tutorial paper, 12 and workshop papers and 3 doctoral symposium papers.The contributions were organized in topical sections as follows: Part I: Software development and project management; machine learning and data science; software analysis and tools; software testing and quality assurance; security, vulnerabilities, and human factors; Part II: Posters; Tutorials; 2nd Workshop on Computational Intelligence and Software Engineering (CISE 2023); 2nd Workshop on Engineering Processes and Practices for Quantum Software (PPQS’ 23); doctoral symposium.
Product-Focused Software Process Improvement: 24th International Conference, PROFES 2023, Dornbirn, Austria, December 10–13, 2023, Proceedings, Part II (Lecture Notes in Computer Science #14484)
by Andrea Janes Andreas Jedlitschka Valentina Lenarduzzi Xiaozhou Li Regine KadgienThis book constitutes the refereed proceedings of the 24th International Conference on Product-Focused Software Process Improvement, PROFES 2023, which took place in Dornbirn, Austria, in December 2023. The 21 full technical papers, 6 industrial papers, 8 short papers and 1 poster paper were carefully reviewed and selected from 82 submissions. The book also contains one tutorial paper, 11 workshop papers and 3 doctoral symposium papers. The contributions were organized in topical sections as follows: Part I: Software development and project management; machine learning and data science; software analysis and tools; software testing and quality assurance; security, vulnerabilities, and human factors; Part II: Posters; Tutorials; 2nd Workshop on Computational Intelligence and Software Engineering (CISE 2023); 2nd Workshop on Engineering Processes and Practices for Quantum Software (PPQS’ 23); doctoral symposium.
Product-Focused Software Process Improvement: 25th International Conference, PROFES 2024, Tartu, Estonia, December 2–4, 2024, Proceedings (Lecture Notes in Computer Science #15452)
by Dietmar Pfahl Jil Klünder Javier Gonzalez Huerta Hina AnwarThis book constitutes the refereed proceedings of the 25th International Conference on Product-Focused Software Process Improvement, PROFES 2024, held in Tartu, Estonia, during December 2–4, 2024. The 18 full papers, 12 short papers, 9 Industry papers, 2 Workshop papers, 2 Doctoral symposium papers, and one Keynote paper presented in this volume were carefully reviewed and selected from 85 submissions. The main theme of PROFES 2024 was professional software process improvement (SPI) motivated by product, process, and service quality needs. The technical program of PROFES 2024 was selected by a committee of leading experts in software process improvement, software process modeling, and empirical software engineering.
Production Kubernetes
by John Harris Josh Rosso Rich Lander Alex BrandKubernetes has become the dominant container orchestrator, but many organizations that have recently adopted this system are still struggling to run actual production workloads. In this practical book, four software engineers from VMware bring their shared experiences running Kubernetes in production and provide insight on key challenges and best practices.The brilliance of Kubernetes is how configurable and extensible the system is, from pluggable runtimes to storage integrations. For platform engineers, software developers, infosec, network engineers, storage engineers, and others, this book examines how the path to success with Kubernetes involves a variety of technology, pattern, and abstraction considerations.With this book, you will:Understand what the path to production looks like when using KubernetesExamine where gaps exist in your current Kubernetes strategyLearn Kubernetes's essential building blocks--and their trade-offsUnderstand what's involved in making Kubernetes a viable location for applicationsLearn better ways to navigate the cloud native landscape
Production Pipeline Fundamentals for Film and Games
by Renee DunlopEvery production is built on the backbone of the pipeline. While a functional and flexible pipeline can’t assure a successful project, a weak pipeline can guarantee its demise. A solid pipeline produces a superior product in less time and with happier artists who can remain creative throughout the grueling production schedule. Walk through the foundational layers of the production pipeline, including IT infrastructure, software development practices and deployment policies, asset management, shot management, and rendering management. Production Pipeline Fundamentals for Film and Games will teach you how to direct limited resources to the right technological initiatives, getting the most for every dollar spent. Learn how to prepare for and manage all aspects of the pipeline with this entirely unique, one-of-a-kind guide. Expand your knowledge with real-world pipeline secrets handed to you by a stellar group of professionals from across the globe. Visit the companion website for even further resources on the pipeline.
Production Planning and Control in Semiconductor Manufacturing: Big Data Analytics and Industry 4.0 Applications (SpringerBriefs in Applied Sciences and Technology)
by Tin-Chih Toly ChenThis book systematically analyzes the applicability of big data analytics and Industry 4.0 from the perspective of semiconductor manufacturing management. It reports in real examples and presents case studies as supporting evidence. In recent years, technologies of big data analytics and Industry 4.0 have been frequently applied to the management of semiconductor manufacturing. However, related research results are mostly scattered in various journal issues or conference proceedings, and there is an urgent need for a systematic integration of these results. In addition, many related discussions have placed too much emphasis on the theoretical framework of information systems rather than on the needs of semiconductor manufacturing management. This book addresses these issues.
Production Ready OpenStack - Recipes for Successful Environments
by Arthur BerezinOver 90 practical and highly applicable recipes to successfully deploy various OpenStack configurations in production About This Book * Get a deep understanding of OpenStack's internal structure and services * Learn real-world examples on how to build and configure various production grade use cases for each of OpenStack's services * Use a step-by-step approach to install and configure OpenStack's services to provide Compute, Storage, and Networking as a services for cloud workloads Who This Book Is For If you have a basic understanding of Linux and Cloud computing and want to learn about configurations that OpenStack supports, this is the book for you. Knowledge of virtualization and managing Linux environments is expected. Prior knowledge or experience of OpenStack is not required, although beneficial. What You Will Learn * Plan an installation of OpenStack with a basic configuration * Deploy OpenStack in a highly available configuration * Configure Keystone Identity services with multiple types of identity backends * Configure Glance Image Store with File, NFS, Swift, or Ceph image backends and use local image caching * Design Cinder to use a single storage provider such as LVM, Ceph, and NFS backends, or to use multiple storage backends simultaneously * Manage and configure the OpenStack networking backend * Configure OpenStack's compute hypervisor and the instance scheduling mechanism * Build and customize the OpenStack dashboard In Detail OpenStack is the most popular open source cloud platform used by organizations building internal private clouds and by public cloud providers. OpenStack is designed in a fully distributed architecture to provide Infrastructure as a Service, allowing us to maintain a massively scalable cloud infrastructure. OpenStack is developed by a vibrant community of open source developers who come from the largest software companies in the world. The book provides a comprehensive and practical guide to the multiple uses cases and configurations that OpenStack supports. This book simplifies the learning process by guiding you through how to install OpenStack in a single controller configuration. The book goes deeper into deploying OpenStack in a highly available configuration. You'll then configure Keystone Identity Services using LDAP, Active Directory, or the MySQL identity provider and configure a caching layer and SSL. After that, you will configure storage back-end providers for Glance and Cinder, which will include Ceph, NFS, Swift, and local storage. Then you will configure the Neutron networking service with provider network VLANs, and tenant network VXLAN and GRE. Also, you will configure Nova's Hypervisor with KVM, and QEMU emulation, and you will configure Nova's scheduler filters and weights. Finally, you will configure Horizon to use Apache HTTPD and SSL, and you will customize the dashboard's appearance. Style and approach This book consists of clear, concise instructions coupled with practical and applicable recipes that will enable you to use and implement the latest features of OpenStack.
Production Research: 10th International Conference of Production Research - Americas, ICPR-Americas 2020, Bahía Blanca, Argentina, December 9-11, 2020, Revised Selected Papers, Part I (Communications in Computer and Information Science #1407)
by Daniel Alejandro Rossit Fernando Tohmé Gonzalo Mejía DelgadilloThis two-volume set presents selected and revised papers from the 10th International Conference of Production Research - Americas, ICPR-Americas 2020, held in Bahía Blanca, Argentina, in December 2020. Due to the COVID-19 pandemic the conference was held in a fully virtual format. The 41 full papers and 11 short papers were thoroughly reviewed and selected from 275 submissions. They are organized in topical sections on optimization; metaheuristics and algorithms; industry 4.0 and cyber-physical systems; smart city; intelligent systems and decision sciences; simulation; machine learning and big data.
Production Research: 10th International Conference of Production Research - Americas, ICPR-Americas 2020, Bahía Blanca, Argentina, December 9-11, 2020, Revised Selected Papers, Part II (Communications in Computer and Information Science #1408)
by Daniel Alejandro Rossit Fernando Tohmé Gonzalo Mejía DelgadilloThis two-volume set presents selected and revised papers from the 10th International Conference of Production Research - Americas, ICPR-Americas 2020, held in Bahía Blanca, Argentina, in December 2020. Due to the COVID-19 pandemic the conference was held in a fully virtual format. The 41 full papers and 11 short papers were thoroughly reviewed and selected from 275 submissions. They are organized in topical sections on optimization; metaheuristics and algorithms; industry 4.0 and cyber-physical systems; smart city; intelligent systems and decision sciences; simulation; machine learning and big data.
Production Systems and Supply Chain Management in Emerging Countries: Selected papers from the International Conference on Production Research (ICPR)
by Nubia Velasco Gonzalo MejíaThe book presents several highly selected cases in emerging countries where the production-logistics systems have been optimized or improved with the support of mathematical models. The book contains a selection of papers from the 5th International Conference on Production Research (ICPR) Americas 2010 held on July 21-23 in Bogotá, Colombia. The main topic of the conference was "Technologies in Logistics and Manufacturing for Small and Medium Enterprises" which is perfectly aligned with the realities of emerging countries. The book presents methodologies and case studies related to a wide variety of production/logistics systems such as diary production, auto parts, steel and iron production, and financial services. It is focused but not limited to Small/Medium Enterprises.
Production Volume Rendering: Design and Implementation
by Magnus WrenningeDue to limited publicly available software and lack of documentation, those involved with production volume rendering often have to start from scratch creating the necessary elements to make their system work. Production Volume Rendering: Design and Implementation provides the first full account of volume rendering techniques used for feature anima
Production at the Leading Edge of Technology: Proceedings of the 11th Congress of the German Academic Association for Production Technology (WGP), Dresden, September 2021 (Lecture Notes in Production Engineering)
by Peter Nyhuis Alexander Brosius Bernd-Arno Behrens Wolfgang Hintze Steffen Ihlenfeldt Welf-Guntram DrosselThis congress proceedings provides recent research on leading-edge manufacturing processes. The aim of this scientific congress is to work out diverse individual solutions of "production at the leading edge of technology" and transferable methodological approaches. In addition, guest speakers with different backgrounds will give the congress participants food for thoughts, interpretations, views and suggestions.The manufacturing industry is currently undergoing a profound structural change, which on the one hand produces innovative solutions through the use of high-performance communication and information technology, and on the other hand is driven by new requirements for goods, especially in the mobility and energy sector. With the social discourse on how we should live and act primarily according to guidelines of sustainability, structural change is gaining increasing dynamic.It is essential to translate politically specified sustainability goals into socially accepted and marketable technical solutions. Production research is meeting this challenge and will make important contributions and provide innovative solutions from different perspectives.
Production at the leading edge of technology: Proceedings of the 10th Congress of the German Academic Association for Production Technology (WGP), Dresden, 23-24 September 2020 (Lecture Notes in Production Engineering)
by Alexander Brosius Bernd-Arno Behrens Wolfgang Hintze Steffen Ihlenfeldt Jens Jens WulfsbergThis congress proceedings provides recent research on leading-edge manufacturing processes. The aim of this scientific congress is to work out diverse individual solutions of "production in the border area" and transferable methodological approaches. In addition, guest speakers with different backgrounds will give the congress participants food for thoughts, interpretations, views and suggestions.The manufacturing industry is currently undergoing a profound structural change, which on the one hand produces innovative solutions through the use of high-performance communication and information technology, and on the other hand is driven by new requirements for goods, especially in the mobility and energy sector. With the social discourse on how we should live and act primarily according to guidelines of sustainability, structural change is gaining increasing dynamic.It is essential to translate politically specified sustainability goals into socially accepted and marketable technical solutions. Production research is meeting this challenge and will make important contributions and provide innovative solutions from different perspectives.
Production-Ready Applied Deep Learning: Learn how to construct and deploy complex models in PyTorch and TensorFlow deep learning frameworks
by Tomasz Palczewski Jaejun (Brandon) Lee Lenin MookiahSupercharge your skills for developing powerful deep learning models and distributing them at scale efficiently using cloud servicesKey FeaturesUnderstand how to execute a deep learning project effectively using various tools availableLearn how to develop PyTorch and TensorFlow models at scale using Amazon Web ServicesExplore effective solutions to various difficulties that arise from model deploymentBook DescriptionMachine learning engineers, deep learning specialists, and data engineers encounter various problems when moving deep learning models to a production environment. The main objective of this book is to close the gap between theory and applications by providing a thorough explanation of how to transform various models for deployment and efficiently distribute them with a full understanding of the alternatives.First, you will learn how to construct complex deep learning models in PyTorch and TensorFlow. Next, you will acquire the knowledge you need to transform your models from one framework to the other and learn how to tailor them for specific requirements that deployment environments introduce. The book also provides concrete implementations and associated methodologies that will help you apply the knowledge you gain right away. You will get hands-on experience with commonly used deep learning frameworks and popular cloud services designed for data analytics at scale. Additionally, you will get to grips with the authors' collective knowledge of deploying hundreds of AI-based services at a large scale.By the end of this book, you will have understood how to convert a model developed for proof of concept into a production-ready application optimized for a particular production setting.What you will learnUnderstand how to develop a deep learning model using PyTorch and TensorFlowConvert a proof-of-concept model into a production-ready applicationDiscover how to set up a deep learning pipeline in an efficient way using AWSExplore different ways to compress a model for various deployment requirementsDevelop Android and iOS applications that run deep learning on mobile devicesMonitor a system with a deep learning model in productionChoose the right system architecture for developing and deploying a modelWho this book is forMachine learning engineers, deep learning specialists, and data scientists will find this book helpful in closing the gap between the theory and application with detailed examples. Beginner-level knowledge in machine learning or software engineering will help you grasp the concepts covered in this book easily.
Production-Ready Microservices: Building Standardized Systems Across an Engineering Organization
by Susan J. FowlerOne of the biggest challenges for organizations that have adopted microservice architecture is the lack of architectural, operational, and organizational standardization. After splitting a monolithic application or building a microservice ecosystem from scratch, many engineers are left wondering what’s next. In this practical book, author Susan Fowler presents a set of microservice standards in depth, drawing from her experience standardizing over a thousand microservices at Uber. You’ll learn how to design microservices that are stable, reliable, scalable, fault tolerant, performant, monitored, documented, and prepared for any catastrophe.Explore production-readiness standards, including:Stability and Reliability: develop, deploy, introduce, and deprecate microservices; protect against dependency failuresScalability and Performance: learn essential components for achieving greater microservice efficiencyFault Tolerance and Catastrophe Preparedness: ensure availability by actively pushing microservices to fail in real timeMonitoring: learn how to monitor, log, and display key metrics; establish alerting and on-call proceduresDocumentation and Understanding: mitigate tradeoffs that come with microservice adoption, including organizational sprawl and technical debt
Productionizing AI: How to Deliver AI B2B Solutions with Cloud and Python
by Barry WalshThis book is a guide to productionizing AI solutions using best-of-breed cloud services with workarounds to lower costs. Supplemented with step-by-step instructions covering data import through wrangling to partitioning and modeling through to inference and deployment, and augmented with plenty of Python code samples, the book has been written to accelerate the process of moving from script or notebook to app. From an initial look at the context and ecosystem of AI solutions today, the book drills down from high-level business needs into best practices, working with stakeholders, and agile team collaboration. From there you’ll explore data pipeline orchestration, machine and deep learning, including working with and finding shortcuts using artificial neural networks such as AutoML and AutoAI. You’ll also learn about the increasing use of NoLo UIs through AI application development, industry case studies, and finally a practical guide to deploying containerized AI solutions. The book is intended for those whose role demands overcoming budgetary barriers or constraints in accessing cloud credits to undertake the often difficult process of developing and deploying an AI solution. What You Will Learn Develop and deliver production-grade AI in one monthDeploy AI solutions at a low costWork around Big Tech dominance and develop MVPs on the cheapCreate demo-ready solutions without overly complex python scripts/notebooks Who this book is for: Data scientists and AI consultants with programming skills in Python and driven to succeed in AI.
Productive Multivocality in the Analysis of Group Interactions
by Nancy Law Kristine Lund Daniel D. Suthers Carolyn Penstein Rosé Chris TeplovsThe key idea of the book is that scientific and practical advances can be obtained if researchers working in traditions that have been assumed to be mutually incompatible make a real effort to engage in dialogue with each other, comparing and contrasting their understandings of a given phenomenon and how these different understandings can either complement or mutually elaborate on each other. This key idea applies to many fields, particularly in the social and behavioral sciences, as well as education and computer science. The book shows how we have achieved this by presenting our study of collaborative learning during the course of a four-year project. Through a series of five workshops involving dozens of researchers, the 37 editors and authors involved in this project studied and reported on collaborative learning, technology enhanced learning, and cooperative work. The authors share an interest in understanding group interactions, but approach this topic from a variety of traditional disciplinary homes and theoretical and methodological traditions. This allows the book to be of use to researchers in many different fields and with many different goals and agendas.
Productive and Efficient Data Science with Python: With Modularizing, Memory profiles, and Parallel/GPU Processing
by Tirthajyoti SarkarThis book focuses on the Python-based tools and techniques to help you become highly productive at all aspects of typical data science stacks such as statistical analysis, visualization, model selection, and feature engineering. You’ll review the inefficiencies and bottlenecks lurking in the daily business process and solve them with practical solutions. Automation of repetitive data science tasks is a key mindset that is promoted throughout the book. You’ll learn how to extend the existing coding practice to handle larger datasets with high efficiency with the help of advanced libraries and packages that already exist in the Python ecosystem. The book focuses on topics such as how to measure the memory footprint and execution speed of machine learning models, quality test a data science pipelines, and modularizing a data science pipeline for app development. You’ll review Python libraries which come in very handy for automating and speeding up the day-to-day tasks. In the end, you’ll understand and perform data science and machine learning tasks beyond the traditional methods and utilize the full spectrum of the Python data science ecosystem to increase productivity. What You’ll Learn Write fast and efficient code for data science and machine learningBuild robust and expressive data science pipelines Measure memory and CPU profile for machine learning methods Utilize the full potential of GPU for data science tasks Handle large and complex data sets efficiently Who This Book Is For Data scientists, data analysts, machine learning engineers, Artificial intelligence practitioners, statisticians who want to take full advantage of Python ecosystem.
Productivity Management: Keane's Project Management Approach for Systems Development, Second Edition
by Donald H. PlummerComplete with examples and case studies, this book boils down myriad implementation factors into six basic principles for designing - and using - computer software.
Productivity with Health, Safety, and Environment: Select Proceedings of HWWE 2019 (Design Science and Innovation)
by Rauf Iqbal Vivek Khanzode Arvind Bhardwaj Lakhwinder Pal SinghThis volume comprises select proceedings of the International Conference on Humanizing Work and Work Environment organized by the Indian Society of Ergonomics (HWWE2019). The book presents research findings on different areas of ergonomics for developing appropriate tools and work environment considering capabilities and limitations of working people for maximum effectiveness on their performance. This volume will be of interest to academics, professionals and practitioners in the field of ergonomics.
Productizing Quantum Computing: Bring Quantum Computing Into Your Organization
by Srinjoy Ganguly Dhairyya Agarwal Shalini DLeverage the benefits of quantum computing by identifying business use cases and understanding how to design and develop quantum products and services. This book will guide you to effectively productize quantum computing, including best practices, recommendations, and proven methods to help you navigate the challenges and risks of this emerging technology. The book starts with a thorough introduction to quantum computing, followed by its various algorithms and applications. You will then learn how to build a strong foundation in classical computing, seek practical experience, and stay up-to-date with the latest developments in the field. Moving forward, you will gain an understanding of how to conduct market research to identify business opportunities for quantum computing products and services. The authors then guide you through the process of developing a quantum roadmap and integrating quantum computing into an existing system. This is concluded by a demonstration of how to manage quantum computing projects and how to address their risks and challenges. After reading this book, you will understand quantum computing and how it can be applied to real-world business problems. What You Will Learn Identify business use cases for quantum computing and understand the potential benefits and risks of quantum applicationsDesign and develop quantum products and services by identifying quantum algorithms, programming in quantum languages, and leveraging quantum simulators and hardwareIntegrate quantum computing into existing systemsIntegrate quantum algorithms with classical algorithms Who This Book Is For Product managers, developers, and entrepreneurs who wish to use the potential of quantum computing for their businesses.
Produkt-Service Systeme
by Jan C. Aurich Michael H. ClementBisher haben sich produzierende Unternehmen auf Entwicklung, Produktion und Vertrieb von Sachprodukten konzentriert, inzwischen fragen Kunden jedoch zunehmend komplette Problemlösungen nach. Unternehmen stehen vor der Herausforderung, den Wandel zum Full-Service Provider zu vollziehen. In dem Band wird ein Managementsystem zur Unterstützung von Planung, Entwicklung, Konfiguration und Realisierung von Produkt-Service Systemen (PSS) im erweiterten Wertschöpfungsnetzwerk vorgestellt und Methoden zur Organisation sowie zum Kompetenzerwerb aufgezeigt.
Produktdatenmanagement – Anforderungen und Lösungen: Konzeption, Auswahl, Installation und Administration von PDM-Systemen
by Thomas MechlinskiProduktdatenmanagement (PDM) ist ein umfassendes, in seiner Ganzheit schwer zu überblickendes Thema. Bei der Betrachtung gängiger PDM-Systeme stellt sich oft die Frage, warum bestimmte Funktionen und Eigenschaften existieren und wie sich damit typische Fragestellungen des Produktentstehungsprozesses (PEP) lösen lassen. Dieses Buch formuliert Anforderungen, die die heute am Markt erhältlichen PDM-Systeme abdecken und erklärt, auf welche Weise die Anforderungen erfüllt werden können. Der Katalog an Anforderungen ist auf die industrielle Praxis im Umfeld der Serienfertigung von Produkten zugeschnitten und kann auch als Basis für die Einführung von PDM-Systemen genutzt werden.Das Buch richtet sich an IT-Verantwortliche, die sich mit der Einführung oder dem Ausbau von PDM-Systemen beschäftigen. Es ist solchermaßen detailliert, dass die Anforderungen und Lösungen in Bezug auf einen konkreten Einsatz beurteilt werden können. Die beschriebenen Lösungsansätze können für die Implementierung in einem Unternehmen übernommen und bedarfsgerecht verändert oder ausgebaut werden. Der Ansatz ist so gewählt, dass dieses Buch auch für Studierende als Basis für das Verständnis von PDM-Systemen dienen kann.