Although there are many Bayesian statistical books that focus on biostatistics and economics, there are few that address the problems faced by engineers. Bayesian Process Monitoring, Control and Optimization resolves this need, showing you how to oversee, adjust, and optimize industrial processes.
Injection Molding. Process Control, Monitoring, and Optimization
β Scribed by Y. Yang, X. Chen, N. Lu, F. Gao
- Publisher
- Hanser Publications
- Year
- 2016
- Tongue
- English
- Leaves
- 405
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Improvement of injection molding processes remains a topic of great interest in both industry and research institutions. This book introduces the analysis of the molding process from a systems technology point of view. It is divided into four parts: the first part provides general background to introduce the injection molding process, the second covers the control of the process, the third is on the monitoring technology, and the fourth is concerned with the optimization of the process. Most the results within are from real engineering implementations and experimental tests
β¦ Table of Contents
Content:
Injection Molding Process Control, Monitoring, and OptimizationEntitled to full text1 - Injection Molding: Background, Pages 1-37
2 - Feedback Control Algorithms Developed for Continuous Processes, Pages 39-81
3 - Learning Type Control for the Injection Molding Process, Pages 83-107
4 - Two-Dimensional Control Algorithms, Pages 109-148
5 - Statistical Process Monitoring (SPM) of Injection Molding: Basics, Pages 149-171
6 - Phase-Based SPM Strategies, Pages 173-211
7 - Phase-Based Quality Improvement Strategies, Pages 213-250
8 - In-Mold Capacitive Transducer for Injection Molding Process, Pages 251-293
9 - Profile Setting of Injection Velocity, Pages 295-328
10 - Profile Setting of Packing Pressure, Pages 329-370
11 - Parameter Setting for the Plastication Stage, Pages 371-389
Subject Index, Pages 391-397
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