This book describes load modeling approaches for complex work pieces and batch forgings, and demonstrates analytical modeling and data-driven modeling approaches for known and unknown complex forging processes. It overcomes the current shortcomings of modeling, analysis and control approaches, presenting contributions in three major areas: In the first, several novel modeling approaches are proposed: a process/shape-decomposition modeling method to help estimate the deformation force; an online probabilistic learning machine for the modeling of batch forging processes; and several data-driven identification and modeling approaches for unknown forging processes under different work conditions. The second area develops model-based dynamic analysis methods to derive the conditions of stability and creep. Lastly, several novel intelligent control methods are proposed for complex forging processes. One of the most serious problems in forging forming involves the inaccurate forging conditions, velocity and position offered by the hydraulic actuator due to the complexity of both the deformation process of the metal work piece and the motion process of the hydraulic actuator. The book summarizes the current weaknesses of modeling, analysis and control approaches. are summarized as follows: a) With the current modeling approaches it is difficult to model complex forging processes with unknown parameters, as they only model the dynamics in local working areas but do not effectively model unknown nonlinear systems across multiple working areas; further, they do not take the batch forging process into account, let alone its distribution modeling. b) All previous dynamic analysis studies simplify the forging system to having a single-frequency pressure fluctuation and neglect the influences of non-linear load force. Further, they fail to take the flow equation in both valves and cylinders into account. c) Conventional control approaches only consider the linear deformation force and pay no attention to sudden changes and the motion synchronization for the multi-cylinder system, making them less effective for complex, nonlinear time-varying forging processes subject to sudden changes.

This is an essential resource for managers and scholars interested in services marketing. It covers the topic comprehensively and in novel ways. All the luminaries in the field are represented. Buy this book and you will be up to date on the field.' - Valarie Zeithaml, UNC Kenan-Flagler Business School, USThe Handbook of Service Marketing Research brings together an all-star team of leading researchers in service marketing to explore many of the hottest topics in service marketing today. Cutting-edge topics include: customer relationships and loyalty, customer-centered metrics, managing customer contacts, product and pricing, digital service marketing, rethinking the marketing function, and service for society. This book, which includes authors from both academia and industry, will provide academics with an invaluable current view of the field and practitioners with a window into the latest academic thinking. With chapters from internationally renowned contributors, this comprehensive yet concise Handbook will appeal to service marketing academics, researchers and service practitioners. Contributors: M. Archpru Akaka, L. Aksoy, L. Anderson, T.W. Andreassen, S.F.M. Beckers, M.J. Bitner, R.N. Bolton, A. Buoye, J.W. Choi, R.M. Christopher, T.S. Chung, T.S. Dagger, P.S. Danaher, A. De Keyser, C. Dev, B. Edvardsson, S. Fay, R.P. Fisk, C. Frennea, A. Gustafsson, M.-H. Huang, C. Ishida, P.K. Kannan, T.L. Keiningham, P. Kristensson, V. Kumar, S.K. Kwan, T. van Laer, B. Lariviere, R.F. Lusch, D. Mathras, H. Melton, V. Mittal, R.L. Oliver, A.L. Ostrom, P. Patterson, W. Reinartz, H. Risselada, R.T. Rust, K. de Ruyter, C. Schulze, S.M. Shugan, B. Skiera, J. Spohrer, S. Streukens, S.A. Taylor, B. Tronvoll, W. Ulaga, N. Umashankar, S.L. Vargo, P.C. Verhoef, H.S. Wang, M. Wedel, R.A. Westbrook, L. Williams, L. Witell, J. Xie, T. Yu

This book describes load modeling approaches for complex work pieces and batch forgings, and demonstrates analytical modeling and data-driven modeling approaches for known and unknown complex forging processes. It overcomes the current shortcomings of modeling, analysis and control approaches, presenting contributions in three major areas: In the first, several novel modeling approaches are proposed: a process/shape-decomposition modeling method to help estimate the deformation force; an online probabilistic learning machine for the modeling of batch forging processes; and several data-driven identification and modeling approaches for unknown forging processes under different work conditions. The second area develops model-based dynamic analysis methods to derive the conditions of stability and creep. Lastly, several novel intelligent control methods are proposed for complex forging processes. One of the most serious problems in forging forming involves the inaccurate forging conditions, velocity and position offered by the hydraulic actuator due to the complexity of both the deformation process of the metal work piece and the motion process of the hydraulic actuator. The book summarizes the current weaknesses of modeling, analysis and control approaches. are summarized as follows: a) With the current modeling approaches it is difficult to model complex forging processes with unknown parameters, as they only model the dynamics in local working areas but do not effectively model unknown nonlinear systems across multiple working areas; further, they do not take the batch forging process into account, let alone its distribution modeling. b) All previous dynamic analysis studies simplify the forging system to having a single-frequency pressure fluctuation and neglect the influences of non-linear load force. Further, they fail to take the flow equation in both valves and cylinders into account. c) Conventional control approaches only consider the linear deformation force and pay no attention to sudden changes and the motion synchronization for the multi-cylinder system, making them less effective for complex, nonlinear time-varying forging processes subject to sudden changes.

As machines are trained to "think," many tasks that previously required human intelligence are becoming automated through artificial intelligence. However, it is more difficult to automate emotional intelligence, and this is where the human worker's competitive advantage over machines currently lies. This book explores the impact of AI on everyday life, looking into workers' adaptation to these changes, the ways in which managers can change the nature of jobs in light of AI developments, and the potential for humans and AI to continue working together. The book argues that AI is rapidly assuming a larger share of thinking tasks, leaving human intelligence to focus on feeling. The result is the "Feeling Economy," in which both employees and consumers emphasize feeling to an unprecedented extent, with thinking tasks largely delegated to AI. The book shows both theoretical and empirical evidence that this shift is well underway. Further, it explores the effect of the Feeling Economy on our everyday lives in the areas such as shopping, politics, and education. Specifically, it argues that in this new economy, through empathy and people skills, women may gain an unprecedented degree of power and influence. This book will appeal to readers across disciplines interested in understanding the impact of AI on business and our daily lives. It represents a bold, potentially controversial attempt to gauge the direction in which society is heading.