Concerted efforts are being pursued by governments and economic institutions to promote the generation of startups, and copious documentation has been produced as guides for these emerging companies. However, little has been written on, e.g., the Operations and Supply Chain needs for Hardware Startups, and the development strategy of the required skills to build flexibility during the initial phases of startup development. This work proposes an initial road guide framework for hardware startups, resulting from the experiences of successful companies within the Robotics Cluster present in Massachusetts (either new ventures or spinoffs from existing companies). System Dynamics methodology is then used to capture causal loops, and to characterize the policies which would enable New Venture growth, so as to analyze the Supply Chain/Operations conditions for Hardware Startup Success. The work is presented in four main sections. The first section contains a bibliographic research to characterize the present conditions of Hardware Startups with special emphasis on the Massachusetts Robotics Cluster, providing an overview of the available resources for startups in terms of their skills development and especially with regard to their Operations/Supply Chain Skills development. A second section considered the directed interview of executives at existing robotics startups (Artaic LLC, Kiva Systems, Rethink Robotics and Boston Engineering) to obtain information regarding their strategic decisions in specific aspects of their Supply Chain and Operations. These interviews are reflected as case studies of these companies. The third phase is reflected as a proposal for a System Dynamics model, based on previous work in the area and complemented by aspects identified as relevant from the interviews. Lastly, the conclusions of this work will attempt to gather the main learnings from the analyzed cases, in terms of Operations/Supply Chain Skills development, laying down some directing guidelines for future Hardware Startup ventures.

Industrial revolutions have impacted both, manufacturing and service. From the steam engine to digital automated production, the industrial revolutions have conduced significant changes in operations and supply chain management (SCM) processes. Swift changes in manufacturing and service systems have led to phenomenal improvements in productivity. The fast-paced environment brings new challenges and opportunities for the companies that are associated with the adaptation to the new concepts such as Internet of Things (IoT) and Cyber Physical Systems, artificial intelligence (AI), robotics, cyber security, data analytics, block chain and cloud technology. These emerging technologies facilitated and expedited the birth of Logistics 4.0. Industrial Revolution 4.0 initiatives in SCM has attracted stakeholders’ attentions due to it is ability to empower using a set of technologies together that helps to execute more efficient production and distribution systems. This initiative has been called Logistics 4.0 of the fourth Industrial Revolution in SCM due to its high potential. Connecting entities, machines, physical items and enterprise resources to each other by using sensors, devices and the internet along the supply chains are the main attributes of Logistics 4.0. IoT enables customers to make more suitable and valuable decisions due to the data-driven structure of the Industry 4.0 paradigm. Besides that, the system’s ability of gathering and analyzing information about the environment at any given time and adapting itself to the rapid changes add significant value to the SCM processes. In this peer-reviewed book, experts from all over the world, in the field present a conceptual framework for Logistics 4.0 and provide examples for usage of Industry 4.0 tools in SCM. This book is a work that will be beneficial for both practitioners and students and academicians, as it covers the theoretical framework, on the one hand, and includes examples of practice and real world.

The third edition of this clearly structured case book has been expanded and updated, and includes an introduction to the analysis of operations management cases. Key areas of operations management are dealt with, including new areas such as operations strategy, performance measurement and TPM.

Global value chains (GVCs) powered the surge of international trade after 1990 and now account for almost half of all trade. This shift enabled an unprecedented economic convergence: poor countries grew rapidly and began to catch up with richer countries. Since the 2008 global financial crisis, however, the growth of trade has been sluggish and the expansion of GVCs has stalled. Meanwhile, serious threats have emerged to the model of trade-led growth. New technologies could draw production closer to the consumer and reduce the demand for labor. And trade conflicts among large countries could lead to a retrenchment or a segmentation of GVCs. World Development Report 2020: Trading for Development in the Age of Global Value Chains examines whether there is still a path to development through GVCs and trade. It concludes that technological change is, at this stage, more a boon than a curse. GVCs can continue to boost growth, create better jobs, and reduce poverty provided that developing countries implement deeper reforms to promote GVC participation; industrial countries pursue open, predictable policies; and all countries revive multilateral cooperation.

This book is written primarily for people who are creating the future high-tech world by designing, building, and marketing innovative products. More specifically, it is for all engineers, engineering managers, entrepreneurs and intapreneurs. The book provides insight into the problems entrepreneurs face and gives a model for successful startup companies in a formal checklist.

Research on the topic of clusters and industrial districts is very extensive. However, most of it has focused more on understanding the past than on trying to map out the future. The aim of this book is to fill this gap by identifying and discussing the main research topics that populate the current scientific debate and highlight the emergent lines of research that will constitute the future research agenda. It does so by drawing on the debate started with the "rethinking clusters" workshops, which in a short time have become a rich place for discussion among cluster scholars around the world. Rethinking Clusters: Towards a New Research Agenda for Cluster Research collects contributions from authoritative colleagues, who cover a number of relevant and timely issues, such as the territorial roots of radical innovation processes, new ways of understanding and measuring the role of place in economic development, path renewal, internationalization and entrepreneurship. The final section is devoted to the critical analysis of policies that support smart specialization. The chapters in this book were originally published as a special issue of the journal European Planning Studies.

This book is the first technical overview of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences of creating autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions about its actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, we are able to test new algorithms and update the HD map—plus, train better recognition, tracking, and decision models. This book consists of nine chapters. Chapter 1 provides an overview of autonomous vehicle systems; Chapter 2 focuses on localization technologies; Chapter 3 discusses traditional techniques used for perception; Chapter 4 discusses deep learning based techniques for perception; Chapter 5 introduces the planning and control sub-system, especially prediction and routing technologies; Chapter 6 focuses on motion planning and feedback control of the planning and control subsystem; Chapter 7 introduces reinforcement learning-based planning and control; Chapter 8 delves into the details of client systems design; and Chapter 9 provides the details of cloud platforms for autonomous driving. This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find plenty of references for an effective, deeper exploration of the various technologies.