| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA9911020262603321 |
|
|
Autore |
Singh Chandan Deep |
|
|
Titolo |
Digitization and Manufacturing Performance : An Environmental Perspective |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Newark : , : John Wiley & Sons, Incorporated, , 2026 |
|
©2025 |
|
|
|
|
|
|
|
|
|
ISBN |
|
1-394-19781-0 |
1-394-19782-9 |
|
|
|
|
|
|
|
|
Edizione |
[1st ed.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (227 pages) |
|
|
|
|
|
|
Altri autori (Persone) |
|
SinghTalwinder |
SinghDavinder |
|
|
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Manufacturing processes - Technological innovations |
Manufacturing processes - Environmental aspects |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di contenuto |
|
Cover -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Green Energy Technologies -- 1.1 Introduction -- 1.2 Industrial Processes -- 1.3 Overview of Renewable Energy Technologies -- 1.4 Dedicated Energy Crops -- 1.5 Agricultural Crop Residue -- 1.6 Forestry Residues -- 1.7 Algae -- 1.8 Wood Processing Residues -- 1.9 Sorted Municipal Waste -- 1.10 Wet Waste -- 1.11 What is Solar PV? -- 1.12 Solar Photovoltaic Energy Conversion -- 1.13 What is Waste to Energy? -- 1.14 Where are Nanomaterials Found? -- References -- Chapter 2 Recent Advances in Green Energy Materials: A Review -- 2.1 Introduction -- 2.2 Solar Energy Materials -- 2.3 Wind Energy Materials -- 2.4 Hydroelectric Energy Materials -- 2.4.1 Turbines and Generators -- 2.4.2 Penstocks and Pipelines -- 2.4.3 Dams -- 2.4.4 Roller Compacted Concrete -- 2.4.5 Geosynthetics -- 2.4.6 Bamboo -- 2.4.7 Recycled Materials -- 2.4.8 Transmission Lines -- 2.5 Geothermal Energy Materials -- 2.5.1 Drill Bits and Casing -- 2.5.2 Heat Exchangers -- 2.5.3 Turbines and Generators -- 2.5.4 Piping -- 2.5.5 Sealing Materials -- 2.6 Biomass Energy Materials -- 2.6.1 Combustion Chambers -- 2.6.2 Boilers and Heat Exchangers -- 2.6.3 Gas Cleaning Systems -- 2.6.4 Storage Systems -- 2.6.5 Fuel |
|
|
|
|
|
|
|
|
|
Handling Systems -- 2.7 Conclusion -- References -- Chapter 3 Green Computing Technologies: Toward Sustainable Computing -- 3.1 Introduction -- 3.1.1 Definition of Green Computing -- 3.1.2 Energy Efficient Computing -- 3.1.3 Low Power Processors and Devices -- 3.1.4 Dynamic Voltage and Frequency Scaling -- 3.1.5 Energy-Efficient Memory Systems with Citation -- 3.1.6 Power Management Techniques -- 3.2 Virtualization and Cloud Computing -- 3.2.1 Virtualization Techniques for Energy Savings -- 3.2.2 Green Cloud Computing -- 3.2.3 Energy-Efficient Data Centers. |
3.2.4 Cloud Computing and Carbon Footprint -- 3.2.5 Energy Harvesting and Energy-Neutral Computing -- 3.2.6 Hybrid Systems for Renewable Energy and Traditional Power Sources -- 3.3 Sustainable Computing Practices -- 3.3.1 Green Software Engineering Practices -- 3.3.2 Sustainable Data Management Practices -- 3.3.3 Sustainable Networking Practices -- 3.4 Green Computing in Industry and Society -- 3.4.1 Case Studies of Green Computing in Industry -- 3.4.2 Green Computing Initiatives by Governments and Non-Profits -- 3.4.3 The Role of Green Computing in Achieving Sustainable Development Goals -- 3.5 Challenges and Opportunities -- 3.5.1 Technological Challenges in Green Computing -- 3.5.2 Economic and Social Opportunities of Green Computing -- 3.5.3 Future Directions in Green Computing Research and Development -- 3.6 Conclusion -- References -- Chapter 4 Application of Machine Learning Techniques for Environmental Monitoring and Conservation: A Review -- 4.1 Introduction -- 4.1.1 Background of the Study -- 4.1.2 Machine Learning Techniques in Environmental Aspect -- 4.2 Machine Learning Techniques -- 4.3 Applications of Machine Learning in Environmental Aspect -- 4.3.1 Air Quality Monitoring and Prediction -- 4.3.2 Water Quality Monitoring and Prediction -- 4.3.3 Climate Change Analysis and Prediction -- 4.4 Natural Resource Management and Conservation -- 4.5 Biodiversity Conservation -- 4.6 Waste Management and Recycling -- 4.7 Challenges and Opportunities -- 4.8 Opportunities for the Advancement of Machine Learning in Environmental Aspect -- 4.9 Ethics, Transparency, and Fairness in Machine Learning for Environmental Aspect -- 4.10 Real-World Applications of Machine Learning in Environmental Aspect -- 4.11 Case Studies -- 4.12 Success Stories and Best Practices -- 4.13 Conclusion and Recommendations -- References -- Chapter 5 Green Engineering in IoT. |
5.1 Introduction -- 5.2 IoT Data Types -- 5.2.1 IoT Data Value -- 5.3 What is Green IoT? -- 5.4 Benefits of Adopting Green IoT -- 5.4.1 Important Benefits of Adopting Green IoT are Highlighted Below -- 5.5 Green IoT Components -- 5.5.1 Green Wireless Sensor Network (WSN) -- 5.5.2 Green Machine to Machine (M2M) -- 5.5.3 Green Data Center (DC) -- 5.5.3.1 Ways to Achieve a Greener Data Center -- 5.5.4 Green Cloud Computing (CC) -- 5.5.4.1 Green Cloud Computing Objectives -- 5.5.4.2 Green Cloud Computing Benefits -- 5.5.5 Green Radio-Frequency Identification (RFID) -- 5.6 Recommendations for Raising Awareness and Future Research Directions -- References -- Chapter 6 Green Engineering in Product Development -- 6.1 Introduction and Meaning -- 6.2 Principles of Green Engineering -- 6.3 Benefits of Green Engineering -- 6.4 Promoting Green Engineering Through Green Chemistry -- 6.5 Sustainability and Green Engineering Innovations That Might Just Change the World -- 6.6 Conclusion -- References -- Chapter 7 Green Policies in Education: Fostering Environmental Stewardship and Sustainable Practices -- 7.1 Introduction -- 7.1.1 Importance and Relevance of Green Policies in the Education Sector -- 7.1.2 Objectives of the Research -- 7.1.3 Significance of the Study -- 7.2 Theoretical Framework -- 7.2.1 Place-Based Education -- 7.2.2 |
|
|
|
|
|
|
|
Addressing Environmental Challenges -- 7.3 Policy Development and Implementation -- 7.3.1 Policy Implementation -- 7.3.2 Case Studies of Successful Policy Implementation in Different Educational Settings -- 7.4 Curriculum Integration and Pedagogy -- 7.5 Infrastructure and Facilities -- 7.5.1 Waste Management and Recycling Initiatives in Educational Institutions -- 7.5.2 Case Studies Showcasing Exemplary Green Infrastructure Projects in Education -- 7.6 Student Engagement and Participation. |
7.6.1 Student-Led Initiatives and Organizations Promoting Environmental Awareness and Action -- 7.7 Collaboration and Partnerships -- 7.8 Monitoring, Evaluation, and Reporting -- 7.8.1 Importance of Monitoring and Evaluating the Implementation and Impact of Green Policies -- 7.8.2 Key Indicators and Evaluation Frameworks for Assessing Sustainability in Education -- 7.8.3 Reporting Mechanisms and Accountability in Relation to Green Policies -- 7.9 Challenges and Future Directions -- 7.9.1 Exploration of Potential Solutions and Strategies to Address These Challenges -- 7.9.2 Emerging Trends and Innovations in the Field of Green Policies in Education -- 7.9.3 Summary of the Main Findings and Insights From the Research -- 7.9.4 Contributions of the Study to the Field of Green Policies in Education -- 7.9.5 Implications for Policy, Practice, and Further Research -- 7.9.6 Further Research Implications -- 7.10 Conclusion -- References -- Chapter 8 Green Engineering in Automobile Sector -- 8.1 Introduction -- 8.2 Green Engineering in Automobile Design -- 8.2.1 Green Engineering in Automobile Manufacturing -- 8.2.2 Green Engineering in Automobile Operations -- 8.2.3 Green Engineering in Automobile End-of-Life -- 8.2.4 Case Studies -- 8.3 Conclusion -- References -- Chapter 9 Towards Sustainable Manufacturing: Integrating Digital Technologies on the Green Path -- 9.1 Introduction -- 9.1.1 Sustainable Manufacturing -- 9.1.2 Importance of Sustainable Manufacturing -- 9.1.3 Challenges to Achieving Sustainable Manufacturing -- 9.1.4 Digital Technologies for Sustainable Manufacturing -- 9.1.5 Advantages of Digital Technologies for Sustainable Manufacturing -- 9.2 Digital Technologies for Sustainable Manufacturing with Internet of Things (IoT) -- 9.3 Digital Technologies for Sustainable Manufacturing with Artificial Intelligence. |
9.4 Digital Technologies for Sustainable Manufacturing with Digital Twins -- 9.5 Digital Technologies for Sustainable Manufacturing with Additive Manufacturing (3D Printing) -- 9.6 Digital Technologies for Sustainable Manufacturing with Augmented Reality (AR) -- 9.7 Green Path for Sustainable Manufacturing -- 9.8 Introduction to Green Manufacturing -- 9.8.1 Benefits of Green Manufacturing -- 9.8.2 Green Manufacturing Practices with Lean Manufacturing -- 9.8.3 Green Manufacturing Practices with Energy Efficiency -- 9.8.4 Green Manufacturing Practices with Waste Reduction and Recycling -- 9.8.5 Green Manufacturing Practices with Sustainable Supply Chain Management -- 9.8.6 Integration of Digital Technologies on the Green Path -- 9.8.7 Importance of Integrating Digital Technologies and Green Manufacturing Practices -- 9.8.8 Challenges to Integrating Digital Technologies and Green Manufacturing Practices -- 9.8.9 Case Studies of Successful Integration of Digital Technologies and Green Manufacturing Practices -- 9.9 Future Trends in Sustainable Manufacturing -- 9.10 Emerging Digital Technologies for Sustainable Manufacturing -- 9.11 New Trends in Green Manufacturing Practices -- 9.12 Future Directions for Sustainable Manufacturing -- 9.13 Conclusion -- 9.14 Future Scope -- References -- Chapter 10 Smart Manufacturing for a Sustainable Future: A Review -- 10.1 Introduction -- 10.1.1 Smart Manufacturing for a Green Future -- 10.1.2 Green |
|
|
|
|
|
|
|
|
|
Supply Chain Management -- 10.1.3 Waste Reduction -- 10.1.4 Renewable Energy Integration -- 10.1.5 Green Product Design -- 10.1.6 Circular Economy -- 10.1.7 Water Conservation -- 10.2 Smart Manufacturing for Green Future -- 10.2.1 Energy-Efficient Equipment and Machinery -- 10.2.2 Process Optimization -- 10.2.3 Energy Management Practices -- 10.2.4 Renewable Energy Sources -- 10.3 Green Supply Chain Management. |
10.4 Waste Reduction. |
|
|
|
|
|
|
Sommario/riassunto |
|
The book provides valuable insights into how modern production strategies can enhance quality, efficiency, and environmental sustainability, ultimately driving profit and competitive advantage in today's high-tech industry. Today, production strategies are influenced by quality, cost, delivery, innovation, and responsiveness. Firms have traditionally pursued these goals through the adoption of production practices, such as simultaneous engineering, increasing efficiency through the elimination of defects, setup reduction, and worker empowerment. However, recent developments in industry suggest that industry regulators and professional bodies must encourage innovation in a broad range of high-tech production facilities with the environment in mind. The success of the industry depends on production facilities and the competitive advantage that the industry gains due to better quality and reliability. This advantage leads to an increase in sales and the creation of a sound customer base for greater market share, which eventually leads to more profit, growth, and expansion. A firm's processes must possess operating advantages in the form of competitive priorities to outperform its competitors, keeping in mind its influence on the environment. Digitization and Manufacturing Performance: An Environmental Perspective presents the expectations of industrialists, policymakers, and academics by evaluating the impact of production facilities. Readers will find the book: - Discusses emerging technologies and their role in environmental aspects in detail; - Provides a comprehensive overview of the latest existing and emerging technologies and their environmental aspects; - Justifies social, economic, and technical considerations of these technologies; - Explores the relationship between advanced technologies and the environment through in-depth studies. Audience Researchers, scholars, faculty, professionals in research and development, and industrialists in the industrial, production, mechanical, and electronics sectors. |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2. |
Record Nr. |
UNINA9911020425303321 |
|
|
Autore |
Gibson Justin W |
|
|
Titolo |
Opponent Process Theory : Neurophysiological Foundations and Clinical Applications / / by Justin W. Gibson, Brett A. Pearce, Robert C. Thomas, Steven D. Thurber |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Edizione |
[1st ed. 2025.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (130 pages) |
|
|
|
|
|
|
Altri autori (Persone) |
|
PearceBrett A |
ThomasRobert C |
ThurberSteven D |
|
|
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Psychiatry |
Clinical psychology |
Medicine and psychology |
Clinical Psychology |
Behavioral Medicine |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di contenuto |
|
Chapter 1. Historical Precursors -- Chapter 2. Neurophysiological Underpinnings -- Chapter 3. Substance Usage -- Chapter 4. Commonplace Behaviors with Opponent Process Foundations -- Chapter 5. Criminology and Risk Motivation -- Chapter 6. Pain Relief, Self-inflicted Injuries, and Acupuncture -- Chapter 7. Learning, Motivation, and Opponent Process Theory -- Chapter 8. Practical Implications -- Chapter 9. Epilogue. |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
This book discusses the role of the opponent processes across disparate areas ranging from psychiatric disorders to altruistic behaviors such as blood donation. Opponent process theory unites data from neurophysiology and behavioral science and connects seemingly unrelated phenomena, such as bulimia and the afterimages one can see after staring at an object. Information in this book will help demystify certain disorders and will facilitate patient understanding, a precursor for effective interventions. This volume’s opening chapter relates a brief history of the antecedents of opponent process theory, |
|
|
|
|
|
|
|
|
|
|
including homeostasis and motivation. After a discussion of the fundamentals of opponent process theory, acquired motivation, and the neurological underpinnings of opponent processes, the book moves on to examine different situations where we can see opponent process theory at work. These chapters discuss topics such as learning, substance use disorder, food addiction, pain, acupuncture, and self-inflicted injury. Finally, the authors outline treatment modalities with opponent process-learning theory foundations and propose a discussion of opponent processes in the DSM-5. Opponent Process Theory: Neurophysiological Foundations and Clinical Applications will be of great interest to psychiatrists, psychologists, social workers, and counselors. |
|
|
|
|
|
| |