Manufacturing Systems Engineering

Methodologies and Practices

By: Jay Lee (Editor), Ben Wang (Editor)

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Hardcover | 31 January 1999

At a Glance

Hardcover
428 Pages

Dimensions(cm)
23.39 x 15.6 x 2.39

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In today's business environment, reliability and maintenance drastically affect the three key elements of competitiveness - quality, cost, and product lead time. Well-maintained machines hold tolerances better, help reduce scrap and rework, and raise consistency and quality of the part in addition to cutting total production costs. Today, many factories are still performing maintenance on equipment in a reactive manner due to a lack of understanding about machine performance behaviour. To improve production efficiency, computer-aided maintenance and diagnostic methodology must be applied effectively in manufacturing. This book focuses on the fundamental principles of predictive maintenance and diagnostic engineering. In addition to covering the relevant theory, techniques and methodologies in maintenance engineering, the book also provides numerous case studies and examples illustrating the successful application of the principles and techniques outlined.

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You Can Find This Book In

Non-Fiction Computing & I.T.Graphical & Digital Media Applications Engineering & Technology Mechanical Engineering & Materials Mechanical Engineering Technology in General Engineering in General Business & Management Management & Management Techniques Management of Specific Areas Production of Quality Control Management

List of contributors
Preface
Methodologies
Fundamentals of maintenance
Fundamentals of sensory systems for maintenance engineering
Related work on machine monitoring and diagnostics
Parametric modeling methods: theory and a case study
Machine performance estimation and reliability modeling
Design methodology for self-maintenance machines
Integrated prognostics, maintenance, and life extending control of continuous-time production processes
Integrated automated root cause identification fuzzy neural network reasoning for quality control
Activity-based costing (ABC)
Life cycle maintenance management
Life extension of operating machinery using the National Information Infrastructure (NII)
Case Examples
Case Example 1: Motor incipient fault detection using artificial neural network and fuzzy logic technologies
Case Example 2: Data analysis for diagnostics and process monitoring of automotive engines
Case Example 3: Measurement of machine performance degradation using a neural network model
Case Example 4: Detection and isolation of faults in the stamping process using the Haar transform
Case Example 5: Fault monitoring in manufacturing systems using template models
Case Example 6: In-process diagnostics of tool failure in milling
Case Example 7: Monitoring and predicting surface roughness and bore tolerance in end-milling
Index
Table of Contents provided by Publisher. All Rights Reserved.

Manufacturing Systems Engineering

Methodologies and Practices

At a Glance

Hardcover

Shipping

How to return your order

Defective items

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