Ebook: Computer-aided Maintenance: Methodologies and Practices

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.

---

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.

---

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.
Content:
Front Matter....Pages i-xiii
Front Matter....Pages 1-1
Fundamentals of maintenance....Pages 3-18
Fundamentals of sensory systems for maintenance engineering....Pages 19-40
Related work on machine monitoring and diagnostics....Pages 41-58
Parametric modeling methods: theory and a case study....Pages 59-85
Machine performance estimation and reliability modeling....Pages 86-116
Design methodology for self-maintenance machines....Pages 117-135
Integrated prognostics, maintenance and life-extending control of continuous-time production processes....Pages 136-169
An integrated automated root cause identification fuzzy neural network reasoning for quality control....Pages 170-180
Maintenance using activity-based costing (ABC)....Pages 181-208
Life cycle maintenance management....Pages 209-230
Life extension of operating machinery using the National Information Infrastructure (NII)....Pages 231-260
Front Matter....Pages 261-261
Case Example 1: Motor incipient fault detection using artificial neural network and fuzzy logic technologies....Pages 263-280
Case Example 2: Data analysis for diagnostics and process monitoring of automotive engines....Pages 281-301
Case Example 3: Measurement of machine performance degradation using a neural network model....Pages 302-317
Case Example 4: Detection and isolation of faults in the stamping process using the Haar transform....Pages 318-338
Case Example 5: Fault monitoring in manufacturing systems using template models....Pages 339-355
Case Example 6: In-process diagnosis of tool failures in milling....Pages 356-378
Case Example 7: Monitoring and predicting surface roughness and bore tolerance in end-milling....Pages 379-406
Back Matter....Pages 407-409

---

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.
Content:
Front Matter....Pages i-xiii
Front Matter....Pages 1-1
Fundamentals of maintenance....Pages 3-18
Fundamentals of sensory systems for maintenance engineering....Pages 19-40
Related work on machine monitoring and diagnostics....Pages 41-58
Parametric modeling methods: theory and a case study....Pages 59-85
Machine performance estimation and reliability modeling....Pages 86-116
Design methodology for self-maintenance machines....Pages 117-135
Integrated prognostics, maintenance and life-extending control of continuous-time production processes....Pages 136-169
An integrated automated root cause identification fuzzy neural network reasoning for quality control....Pages 170-180
Maintenance using activity-based costing (ABC)....Pages 181-208
Life cycle maintenance management....Pages 209-230
Life extension of operating machinery using the National Information Infrastructure (NII)....Pages 231-260
Front Matter....Pages 261-261
Case Example 1: Motor incipient fault detection using artificial neural network and fuzzy logic technologies....Pages 263-280
Case Example 2: Data analysis for diagnostics and process monitoring of automotive engines....Pages 281-301
Case Example 3: Measurement of machine performance degradation using a neural network model....Pages 302-317
Case Example 4: Detection and isolation of faults in the stamping process using the Haar transform....Pages 318-338
Case Example 5: Fault monitoring in manufacturing systems using template models....Pages 339-355
Case Example 6: In-process diagnosis of tool failures in milling....Pages 356-378
Case Example 7: Monitoring and predicting surface roughness and bore tolerance in end-milling....Pages 379-406
Back Matter....Pages 407-409
....