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Intelligent engineering and management for Industry 4.0

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Intelligent engineering and management for Industry 4.0edited by Yong-Hong Kuo ... [et al.].
其他作者:	Kuo, Yong-Hong.
出版者:	Cham :Springer International Publishing :2022.
面頁冊數:	viii, 186 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Industry 4.0.
電子資源:	https://doi.org/10.1007/978-3-030-94683-8
ISBN:	9783030946838$q(electronic bk.)

Intelligent engineering and management for Industry 4.0
Intelligent engineering and management for Industry 4.0[electronic resource] /edited by Yong-Hong Kuo ... [et al.]. - Cham :Springer International Publishing :2022. - viii, 186 p. :ill. (some col.), digital ;24 cm.

Chapter 1: A Batch Scheduling Model for a Three-Stage Flowshop With Batch Processor and Heterogeneous Job Processor to Minimize Total Actual Flowtime -- Chapter 2: Batch scheduling of unique and common components for a three-stage hybrid flow shop processing different product types with multiple due dates to minimize total actual flow time -- Chapter 3: Interactive scheduling for a dual resource constrained job shop with manual and automated work units -- Chapter 4: Big Data-Based Similarity Network Model for Cloud Manufacturing Services -- Chapter 5: Evaluation methods for the reliability of a linear connected-(1, 2)-or-(2, 1)-out-of-(m, n):F lattice system -- Chapter 6: Exact Solution Method for Balancing of a Self-Balancing Production Line with Worker- and Station-Dependent Speed -- Chapter 7: A Novel Bi-Encoded NSGA-II for A DRC Scheduling Problem to Minimize the Makespan and Unbalanced Workload -- Chapter 8: A Study on Optimal Limit Order Strategy using Multi-Period Stochastic Programming considering Nonexecution Risk -- Chapter 9: Banking the Unbanked: The Fintech Revolution -- Chapter 10: Adaptive Intelligent Redeployment Strategy for Service Parts Inventory Management: A Case Study of a High-tech Company -- Chapter 11: Rehabilitation Staff Scheduling Problem Considering Mental Workload in Elderly Daytime Care Facility -- Chapter 12: Knowledge Management and Open Innovation for Improving Social Performance of Small and Medium Industry: A Pilot Study -- Chapter 13: A Design Method of the Joint Venture Formation in EPC Projects -- Chapter 14: The Importance of Information Sharing in Blanket Order: Case Studies of System Dynamics Simulation -- Chapter 15: Multi-objective Robust Optimization for the Design of Biomass Co-firing Networks -- Chapter 16: Co-Evolution Theory Based Collaborative Conceptual-Embodiment CAD System.

Industry 4.0 is changing how we manage operations to drive systems more intelligently. Technologies and applications are rapidly evolving. Disruptive technologies, such as artificial intelligence, big data, cloud computing and digital twin, are shaking up different industries and have motivated us to revisit engineering and management tools for improving system design, efficiency, effectiveness, reliability, and responsiveness. While these emerging technologies have powered new applications, novel industrial engineering methodologies are required to achieve the goals. Industrial Engineering was sprouted from major engineering disciplines that called for better professional understanding of industrialization. Ever since, the discipline of Industrial Engineering has been the star role player in confronting emerging industries; be it manufacturing, service, high tech products, outer space technology, information technology, industrial policy, ergonomics, and now the world's greatest concern, sustainable development. This book presents the state-of-the-art in industrial engineering research from different countries and cities around the globe. The book covers a wide range of topics in industrial engineering, including: Demand Chain Management, E-business / Information Technology, Evolutionary Algorithm, Green Manufacturing/Management, Health Care Systems and more.

ISBN: 9783030946838$q(electronic bk.)

Standard No.: 10.1007/978-3-030-94683-8doiSubjects--Topical Terms:

884221
Industry 4.0.

LC Class. No.: T59.6 / .I57 2022

Dewey Class. No.: 670

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505 0 $a Chapter 1: A Batch Scheduling Model for a Three-Stage Flowshop With Batch Processor and Heterogeneous Job Processor to Minimize Total Actual Flowtime -- Chapter 2: Batch scheduling of unique and common components for a three-stage hybrid flow shop processing different product types with multiple due dates to minimize total actual flow time -- Chapter 3: Interactive scheduling for a dual resource constrained job shop with manual and automated work units -- Chapter 4: Big Data-Based Similarity Network Model for Cloud Manufacturing Services -- Chapter 5: Evaluation methods for the reliability of a linear connected-(1, 2)-or-(2, 1)-out-of-(m, n):F lattice system -- Chapter 6: Exact Solution Method for Balancing of a Self-Balancing Production Line with Worker- and Station-Dependent Speed -- Chapter 7: A Novel Bi-Encoded NSGA-II for A DRC Scheduling Problem to Minimize the Makespan and Unbalanced Workload -- Chapter 8: A Study on Optimal Limit Order Strategy using Multi-Period Stochastic Programming considering Nonexecution Risk -- Chapter 9: Banking the Unbanked: The Fintech Revolution -- Chapter 10: Adaptive Intelligent Redeployment Strategy for Service Parts Inventory Management: A Case Study of a High-tech Company -- Chapter 11: Rehabilitation Staff Scheduling Problem Considering Mental Workload in Elderly Daytime Care Facility -- Chapter 12: Knowledge Management and Open Innovation for Improving Social Performance of Small and Medium Industry: A Pilot Study -- Chapter 13: A Design Method of the Joint Venture Formation in EPC Projects -- Chapter 14: The Importance of Information Sharing in Blanket Order: Case Studies of System Dynamics Simulation -- Chapter 15: Multi-objective Robust Optimization for the Design of Biomass Co-firing Networks -- Chapter 16: Co-Evolution Theory Based Collaborative Conceptual-Embodiment CAD System.
520 $a Industry 4.0 is changing how we manage operations to drive systems more intelligently. Technologies and applications are rapidly evolving. Disruptive technologies, such as artificial intelligence, big data, cloud computing and digital twin, are shaking up different industries and have motivated us to revisit engineering and management tools for improving system design, efficiency, effectiveness, reliability, and responsiveness. While these emerging technologies have powered new applications, novel industrial engineering methodologies are required to achieve the goals. Industrial Engineering was sprouted from major engineering disciplines that called for better professional understanding of industrialization. Ever since, the discipline of Industrial Engineering has been the star role player in confronting emerging industries; be it manufacturing, service, high tech products, outer space technology, information technology, industrial policy, ergonomics, and now the world's greatest concern, sustainable development. This book presents the state-of-the-art in industrial engineering research from different countries and cities around the globe. The book covers a wide range of topics in industrial engineering, including: Demand Chain Management, E-business / Information Technology, Evolutionary Algorithm, Green Manufacturing/Management, Health Care Systems and more.
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