Computational Intelligence In Manufacturing Handbook: A Comprehensive Guide for Mechanical Engineers
The manufacturing industry is undergoing a significant transformation, driven by the rapid advancement of computational intelligence (CI) technologies. CI, a subfield of artificial intelligence, encompasses a wide range of techniques, including machine learning, artificial neural networks, fuzzy logic, and evolutionary computation. These techniques have the potential to revolutionize manufacturing processes, improving efficiency, quality, and productivity.
The Computational Intelligence In Manufacturing Handbook is a comprehensive guide to the application of CI technologies in manufacturing. Written by a team of experts from both academia and industry, the handbook provides a detailed overview of the latest developments in CI and their applications in various manufacturing domains.
The Computational Intelligence In Manufacturing Handbook offers the following key features:
5 out of 5
Language | : | English |
File size | : | 13847 KB |
Print length | : | 576 pages |
- Comprehensive coverage: The handbook covers a wide range of topics, including machine learning, artificial neural networks, fuzzy logic, evolutionary computation, and their applications in manufacturing.
- In-depth analysis: Each chapter provides a detailed analysis of a specific CI technique, including its advantages, disadvantages, and potential applications in manufacturing.
- Case studies: The handbook includes numerous case studies that demonstrate the successful application of CI technologies in real-world manufacturing environments.
- Expert contributors: The handbook is written by a team of experts from both academia and industry, ensuring that the content is both authoritative and practical.
The Computational Intelligence In Manufacturing Handbook offers the following benefits:
- Increased efficiency: CI technologies can help manufacturers to improve efficiency by automating tasks, optimizing processes, and reducing downtime.
- Improved quality: CI technologies can help manufacturers to improve quality by detecting defects, predicting failures, and ensuring that products meet specifications.
- Increased productivity: CI technologies can help manufacturers to increase productivity by reducing lead times, improving throughput, and maximizing resource utilization.
- Competitive advantage: CI technologies can give manufacturers a competitive advantage by enabling them to develop innovative products and processes, improve customer service, and reduce costs.
Applications
CI technologies have a wide range of applications in manufacturing, including:
- Process control: CI technologies can be used to control manufacturing processes, ensuring that products meet specifications and quality standards.
- Predictive maintenance: CI technologies can be used to predict equipment failures, enabling manufacturers to schedule maintenance activities before problems occur.
- Quality inspection: CI technologies can be used to inspect products for defects, ensuring that only high-quality products are shipped to customers.
- Product design: CI technologies can be used to design new products, optimizing performance and manufacturability.
- Supply chain management: CI technologies can be used to manage supply chains, optimizing inventory levels, reducing lead times, and improving customer service.
The Computational Intelligence In Manufacturing Handbook is an essential resource for mechanical engineers who want to learn about the latest developments in CI and how these technologies can be applied to improve manufacturing processes. The handbook provides a comprehensive overview of the field, in-depth analysis of specific CI techniques, and numerous case studies that demonstrate the successful application of CI technologies in real-world manufacturing environments.
5 out of 5
Language | : | English |
File size | : | 13847 KB |
Print length | : | 576 pages |
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5 out of 5
Language | : | English |
File size | : | 13847 KB |
Print length | : | 576 pages |