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In a radical departure from the dozens of other quality books, this one makes the case that the traditional TQM procedures used in the electronics assembly field are not only ineffective-they contribute to many failures. The only book to focus exclusively on quality in electronics manufacturing-& to propose a measurable cost/benefit methodology-this provocative volume shows what's lacking in current quality programs, & how fresh approaches can yet avoid a quality "catastrophe" in the electronics industry. Along the way, numerous quality myths are exploded, hidden issues are confronted, & an array of electronics specific solutions are offered.
In a radical departure from the dozens of other quality books, this one makes the case that the traditional TQM procedures used in the electronics assembly field are not only ineffective-they contribute to many failures. The only book to focus exclusively on quality in electronics manufacturing-& to propose a measurable cost/benefit methodology-this provocative volume shows what's lacking in current quality programs, & how fresh approaches can yet avoid a quality "catastrophe" in the electronics industry. Along the way, numerous quality myths are exploded, hidden issues are confronted, & an array of electronics specific solutions are offered.
This book brings together innovative modelling, simulation and design techniques in CMOS, SOI, GaAs and BJT to achieve successful high-yield manufacture for low-power, high-speed and reliable-by-design analogue and mixed-mode integrated systems.
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.
A "skillful and lucid" (The Wall Street Journal) way of thinking about efficiency, challenging our obsession with it—and offering a new understanding of how to benefit from the powerful potential of serendipity. Algorithms, multitasking, the sharing economy, life hacks: our culture can't get enough of efficiency. One of the great promises of the Internet and big data revolutions is the idea that we can improve the processes and routines of our work and personal lives to get more done in less time than we ever have before. There is no doubt that we're performing at higher levels and moving at unprecedented speed, but what if we're headed in the wrong direction? Melding the long-term history of technology with the latest headlines and findings of computer science and social science, The Efficiency Paradox questions our ingrained assumptions about efficiency, persuasively showing how relying on the algorithms of digital platforms can in fact lead to wasted efforts, missed opportunities, and, above all, an inability to break out of established patterns. Edward Tenner reveals what we and our institutions, when equipped with an astute combination of artificial intelligence and trained intuition, can learn from the random and unexpected.
This book contains the most sustained and serious attack on mainstream, neoclassical economics in more than forty years. Nelson and Winter focus their critique on the basic question of how firms and industries change overtime. They marshal significant objections to the fundamental neoclassical assumptions of profit maximization and market equilibrium, which they find ineffective in the analysis of technological innovation and the dynamics of competition among firms. To replace these assumptions, they borrow from biology the concept of natural selection to construct a precise and detailed evolutionary theory of business behavior. They grant that films are motivated by profit and engage in search for ways of improving profits, but they do not consider them to be profit maximizing. Likewise, they emphasize the tendency for the more profitable firms to drive the less profitable ones out of business, but they do not focus their analysis on hypothetical states of industry equilibrium. The results of their new paradigm and analytical framework are impressive. Not only have they been able to develop more coherent and powerful models of competitive firm dynamics under conditions of growth and technological change, but their approach is compatible with findings in psychology and other social sciences. Finally, their work has important implications for welfare economics and for government policy toward industry.
Master scheduling is an essential planning tool that helps manufacturers synchronize their production cycle with actual market demand. The third edition of this easy-to-follow handbook helps you understand the basic and more advanced concepts of master scheduling, from implementation to capacity planning to final assembly techniques. Packed with handy checklists and examples, Master Scheduling, Third Edition delivers guidelines and techniques for a world-class master schedule.