Build your own Metal Shaper. Exotic is a mild adjective when applied to this shaper. It will cut splines, keyways, gears, sprockets, dovetail slides, flat and angular surfaces and irregular profiles. And all of these with a simple hand-ground lathe tool bit. Obsolete in modern industry, of course, because milling machines do the work much faster and cheaper. But you can’t beat a shaper for simplicity and economy in the home shop.The shaper has a 6" stroke and a mean capacity of 5" x 5", variable and adjustable stroke length, automatic variable cross feed and graduated collars. You will be proud to add this machine to your shop.

As the only comprehensive text focusing on metal shaping processes, which are still the most widely used processes in the manufacture of products and structures, Metal Shaping Processes carefully presents the fundamentals of metal shaping processes with their relevant applications. The treatment of the subject matter is adequately descriptive for those unfamiliar with the various processes and yet is sufficiently analytical for an introductory academic course in manufacturing. The text, as well as the numerous formulas and illustrations in each chapter, clearly show that shaping processes, as a part of manufacturing engineering, are a complex and interdisciplinary subject. The topics are organized and presented in such a manner that they motivate and challenge students to present technically and economically viable solutions to a wide variety of questions and problems, including product design. It is the perfect textbook for students in mechanical, industrial, and manufacturing engineering programs at both the Associate Degree and Bachelor Degree programs, as well a valuable reference for manufacturing engineers (those who design, execute and maintain the equipment and tools); process engineers (those who plan and engineer the manufacturing steps, equipment, and tooling needed in production); manufacturing managers and supervisors; product design engineers; and maintenance and reliability managers and technicians. Each chapter begins with a brief highlighted outline of the topics to be described. Carefully presents the fundamentals of the particular metal-shaping process with its relevant applications within each chapter, so that the student and teacher can clearly assess the capabilities, limitation, and potentials of the process and its competitive aspects. Features sections on product design considerations, which present guidelines on design for manufacturing in many of the chapters. Offers practical, understandable explanations, even for complex processes. Includes text entries that are coded as in an outline, with these numerical designations carried over the 320 related illustrations for easy cross-referencing. Provides a dual (ISO and USA) unit system. Contains end-of-chapter Review Questions. Includes a chapter on sheet metalworking covering cutting processes; bending process; tubes and pipe bending; deep drawing processes; other sheet metal forming process (stretch forming, spinning, rubber forming, and superplatic forming and diffusion bonding). Provides a useful die classification with 15 illustrations and description; presses for sheet metalworking; and high energy-rate forming processes. A chapter on nontraditional manufacturing process discusses such important processes as mechanical energy processes (ultrasonic machining, water jet cutting); electrochemical machining processes (electrochemical machining, electrochemical grinding); thermal energy processes (electric discharge processes, laser beam machining, electron beam machining); and chemical processes (chemical milling).

The Milling Machine is also known as book 4 from the best selling 7 book series, 'Build Your Own Metal Working Shop From Scrap'. Especially designed for the developing home shop. It’s a horizontal miller, but it has the full range of vertical mill capability when used with the angle plate on the work table. Extremely rigid and versatile. The work table is 2 3/8" x 12" with a 3/8" T-slot and it travels a full 12". Eight speeds from 43 rpm to 2430 rpm. The spindle raises as much as 6" above the work table and the transmission is designed to follow the vertical travel without straining the column or changing the belt tension. Accessories included in the project are angle plate, face plate, fly cutter, tail-stand and compound slide assembly with which you can do large swing lathe jobs. Still no need to look for outside help. It’s a miller and more, and you can build it your self.

A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives, and how we can shape the way they impact us Through the technology embedded in almost every major tech platform and every web-enabled device, algorithms and the artificial intelligence that underlies them make a staggering number of everyday decisions for us, from what products we buy, to where we decide to eat, to how we consume our news, to whom we date, and how we find a job. We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me. Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.

This book provides readers with the fundamental, analytical, and quantitative knowledge of machining process planning and optimization based on advanced and practical understanding of machinery, mechanics, accuracy, dynamics, monitoring techniques, and control strategies that they need to understanding machining and machine tools. It is written for first-year graduate students in mechanical engineering, and is also appropriate for use as a reference book by practicing engineers. It covers topics such as single and multiple point cutting processes; grinding processes; machine tool components, accuracy, and metrology; shear stress in cutting, cutting temperature and thermal analysis, and machine tool chatter. The second section of the book is devoted to “Non-Traditional Machining,” where readers can find chapters on electrical discharge machining, electrochemical machining, laser and electron beam machining, and biomedical machining. Examples of realistic problems that engineers are likely to face in the field are included, along with solutions and explanations that foster a didactic learning experience.

foreword by Lashon Booker To program an autonomous robot to act reliably in a dynamic environment is a complex task. The dynamics of the environment are unpredictable, and the robots' sensors provide noisy input. A learning autonomous robot, one that can acquire knowledge through interaction with its environment and then adapt its behavior, greatly simplifies the designer's work. A learning robot need not be given all of the details of its environment, and its sensors and actuators need not be finely tuned. Robot Shaping is about designing and building learning autonomous robots. The term "shaping" comes from experimental psychology, where it describes the incremental training of animals. The authors propose a new engineering discipline, "behavior engineering," to provide the methodologies and tools for creating autonomous robots. Their techniques are based on classifier systems, a reinforcement learning architecture originated by John Holland, to which they have added several new ideas, such as "mutespec," classifier system "energy,"and dynamic population size. In the book they present Behavior Analysis and Training (BAT) as an example of a behavior engineering methodology.

A jaw-dropping exploration of everything that goes wrong when we build AI systems and the movement to fix them. Today’s “machine-learning” systems, trained by data, are so effective that we’ve invited them to see and hear for us—and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potentially existential risks emerge. Researchers call this the alignment problem. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole—and appear to assess Black and White defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And as autonomous vehicles share our streets, we are increasingly putting our lives in their hands. The mathematical and computational models driving these changes range in complexity from something that can fit on a spreadsheet to a complex system that might credibly be called “artificial intelligence.” They are steadily replacing both human judgment and explicitly programmed software. In best-selling author Brian Christian’s riveting account, we meet the alignment problem’s “first-responders,” and learn their ambitious plan to solve it before our hands are completely off the wheel. In a masterful blend of history and on-the ground reporting, Christian traces the explosive growth in the field of machine learning and surveys its current, sprawling frontier. Readers encounter a discipline finding its legs amid exhilarating and sometimes terrifying progress. Whether they—and we—succeed or fail in solving the alignment problem will be a defining human story. The Alignment Problem offers an unflinching reckoning with humanity’s biases and blind spots, our own unstated assumptions and often contradictory goals. A dazzlingly interdisciplinary work, it takes a hard look not only at our technology but at our culture—and finds a story by turns harrowing and hopeful.

How ed tech was born: Twentieth-century teaching machines--from Sidney Pressey's mechanized test-giver to B. F. Skinner's behaviorist bell-ringing box. Contrary to popular belief, ed tech did not begin with videos on the internet. The idea of technology that would allow students to "go at their own pace" did not originate in Silicon Valley. In Teaching Machines, education writer Audrey Watters offers a lively history of predigital educational technology, from Sidney Pressey's mechanized positive-reinforcement provider to B. F. Skinner's behaviorist bell-ringing box. Watters shows that these machines and the pedagogy that accompanied them sprang from ideas--bite-sized content, individualized instruction--that had legs and were later picked up by textbook publishers and early advocates for computerized learning. Watters pays particular attention to the role of the media--newspapers, magazines, television, and film--in shaping people's perceptions of teaching machines as well as the psychological theories underpinning them. She considers these machines in the context of education reform, the political reverberations of Sputnik, and the rise of the testing and textbook industries. She chronicles Skinner's attempts to bring his teaching machines to market, culminating in the famous behaviorist's efforts to launch Didak 101, the "pre-verbal" machine that taught spelling. (Alternate names proposed by Skinner include "Autodidak," "Instructomat," and "Autostructor.") Telling these somewhat cautionary tales, Watters challenges what she calls "the teleology of ed tech"--the idea that not only is computerized education inevitable, but technological progress is the sole driver of events.