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Geographer Dodd examines the process of forming policy concerning the siting of commercial nuclear power plants in the Soviet Union, and how and why it has changed over the years. He analyzes which societal groups influenced siting policy, and of those, which worked through established institutions and which did not, and how all of that may affect the future of the industry. He also compares the experience with that in capitalist countries. Annotation copyright by Book News, Inc., Portland, OR
Overcoming technical risks requires demonstrating the soundness of a technical concept in a controlled setting and readying the product technology for the market. Topics include the extent to which purely technical risk is separable from market risk, how industrial managers make decisions on funding early-stage, high-risk technology projects, and how the government can and should act to reduce the technical risks so that firms will invest in them.
This book discusses management decision-making under accident conditions as a vehicle to confirm the importance of clear decision-making guided by a systems approach on how an organization functions related to the role of managers, operators, and the operation of the plant. The book shows how to effectively assess the reliability of an organization particularly those organizations responsible for critical infrastructure. The authors have used Stafford Beer’s cybernetic model as a basis to model the behavior and reliability of such organizations. A series of case studies are used to draw conclusions not only how training, experience, and education can improve the strategy and response of management to reduce the probability of an economic or social disaster, but also draw attention to the fact that managers need to be made aware of the consequences of their decisions. Poor management decisions made under stress conditions can lead to the collapse of an organization together with its underlying business, possibly linked to a social disaster with loss of life. Some technology-ignorant management decisions even under non-stress conditions can lead to dangerous situations, which can increase the economic burden placed on an organization. This book describes such situations in order to promote improvement in organizational preparedness by training, experience, and education to reduce safety and economic risks. This book offers: • Case studies of accidents that have affected different HROs (high-risk organizations) and others, due to poor decision-making by management • Training methods (advocated by Admiral Hyman Rickover, adopted by military bodies and others) to prepare staff to make critical decisions under difficult conditions and examine their applicability to training managers of high-risk facilities • Documentation on how making decisions in difficult situations have psychological constraints related to the degree of preparedness and the tools available to aid the decision maker(s) • Studies on the key actions taken before, during, and after accidents and how these management decisions can affect accident propagation, and how one could improve management decision-making by the use of training in decision-making and an understanding of Ross Ashby’s Law of Requisite Variety. • Simulation techniques to improve training of front-line operators and management • Consideration of cost and investment evaluations and how they can distort the selection of tactics and measures that ensure successful operations and avoidance of accidents
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
Originally published in 1997 this book examines the unique nature and characteristics of Silicon Valley and looks at the factors that led to the economic and competitiveness problems of the 1980s. The research concluded that the information revolution caused a complex set of events that had global ramifications. Silicon Valley was no longer operating as a driver of this revolution, but it was facing the onslaught of the global competitiveness it had unleashed.
The world progresses toward Industry 4.0, and manufacturers are challenged to successfully navigate this unique digital journey. To some, digitalization is a golden opportunity; to others, it is a necessary evil. But to optimist and pessimist alike, there is a widespread puzzlement over the practical details of digitalization. To many manufacturers, digital transformation is a vague and confusing concept they nevertheless must grapple with in order to survive the Fourth Industrial Revolution. The proliferation of digital manufacturing technologies adds to the confusion, leaving many manufacturers perplexed and unprepared, with little real insight into how emerging technologies can help them sustain a competitive edge in their markets. This book effectively conveys Siemens's knowledge and experience through a concept called "Smart Digital Manufacturing," a stepwise approach to realizing the promise of the Fourth Industrial Revolution. The Smart Digital Manufacturing roadmap provides guidance and enables low-risk, high-reward adoption of new manufacturing software technologies through a series of tipping-point investment decisions that result in optimized manufacturing performance. The book provides readers with a clear understanding of what digital technology has to offer them, and how and when to invest in these essential components of tomorrow?s factories. René Wolf is Senior Vice President of Manufacturing Operations Management Software for Siemens Digital Industries Software, a business unit of the Siemens Digital Factory Division. Raffaello Lepratti is Vice President of Business Development and Marketing for Siemens Digital Industries Software.
Nowadays, the latest technologies can be found not only in healthcare and space application but also in hybrid supercars. Supercars and hypercars require high-performance materials with high strength, high stiffness, and light weight. For higher performance, car engines now become stronger but smaller and with lower fuel consumption (with cleaner exhaust). Currently, the automotive industry involves batch production, but in the near future, personalized and individualized automobiles with low and limited quantities can be fabricated in smart factories, which integrate all companies working in the supply chain, from manufacturing to marketing and services. In this regard, future automobiles in smart cities become more personalized (single user, limited version, personal spare parts), safer, and smarter. Blockchain technology is the key to these future perspectives toward intelligent automobiles without any risk of safety, accident, security, theft, or traffic jam. In the current industry, blockchain technology can explore the interconnection of blockchain with other innovative technologies and trends, such as the Internet of Things (IoT) and artificial intelligence (AI), and analyzes the potential to transform business processes and whole industries if these innovations are applied jointly. In the case of the manufacturing sector, manufacturing can provide a high return on investment. It was reported that $1 of investment in manufacturing can create ~$2.5 of economic activity. In addition, smart products should be fabricated from smart materials via the intelligent manufacturing system framework. In smart production, if the products and machines are integrated, embedded, or otherwise equipped with smart sensors and devices, the system can immediately collect the current operating parameters and predict the product quality and then communicate the optimal parameters to machines in the production line. For smart city applications, the global smart cities market size is expected to grow from USD 410.8 billion in 2020 to USD 820.7 billion by 2025 at a compound annual growth rate (CAGR) of 14.8%. For smart city applications, blockchain technology can build on decentralization, immutability, and consensus characteristics. Additionally, intelligent wireless sensor networks can provide big information to monitor and manage the city’s regular operations and services, including traffic and transportation systems, street lighting systems, power plants, water supply networks, waste management, libraries, hospitals, schools, universities, etc. A blockchain-based distributed framework can be used for automobiles in the smart city. This framework can include a novel miner node selection algorithm for the blockchain-based distributed network architecture. This book explores how blockchain technology can be used in the automotive industry from smart manufacturing to the smart city.