Machine Tool Reliability
One Line Description
|By Bhupesh Kumar Lad,Divya Shrivastava and Makarand S. Kulkarni|
Series: Performability Engineering Series
Copyright: 2016 | Status: Published
ISBN: 9781119038603 | Hardcover |
325 pages | 31 illustrations
Price: $195 USD
This book explores the domain of reliability engineering for machine tools, both from manufacturer and users' point of view.
The volume is a useful resource for both academicians as well practitioners in the field of machine tool design, reliability engineering, maintenance planning and industrial engineering. The book can also be used as a post-graduate level textbook in these subjects.
DescriptionMachine Tool Reliability
explores the domain of reliability engineering in the context of machine tools. Failures of machine tools not only jeopardize users’ ability to meet their due date commitments but also lead to poor quality of products, slower production, down time losses etc. Poor reliability and improper maintenance of a machine tool greatly increases the life cycle cost to the user. Thus, the application area of the present book, i.e. machine tools, will be equally appealing to machine tool designers, production engineers and maintenance managers. The book will serve as a consolidated volume on various dimensions of machine tool reliability and its implications from manufacturers and users point of view.
From the manufacturers’ point of view, it discusses various approaches for reliability and maintenance based design of machine tools. In specific, it discusses optimal reliability design, maintenance optimization, and cost based FMEA.
From the users’ point of view, it explores the role of machine tool reliability in shop floor level decision-making. In specific, it shows how to model the interactions of machine tool reliability with production scheduling, maintenance scheduling and process quality control.Back to Top
Author / Editor DetailsBhupesh Kumar Lad
is currently an Assistant Professor in the Discipline of Mechanical Engineering at the Indian Institute of Technology Indore. He graduated in Mechanical Engineering from Govt. Engineering College Bilaspur (GEC Bilaspur) and later did his masters in Industrial Engineering and Management from Govt. Engineering College Ujjain (UEC Ujjain). Subsequently, he completed his Ph.D. in the area of Reliability Engineering from the Department of Mechanical Engineering at the Indian Institute of Technology Delhi (IITD).
Divya Shrivastava is currently an Assistant Professor in the Discipline of Mechanical Engineering at the Shiv Nadar University, India. She graduated in Mechanical Engineering from H.C.E.T, Jabalpur, India and later did her masters in Industrial Engineering and Management from Govt. Engineering College Ujjain (UEC Ujjain). Subsequently, she completed her Ph.D. in the area of industrial engineering from the Department of Mechanical Engineering at the Indian Institute of Technology Delhi (IITD). Before joining Shiv Nadar University she was working with NIT Hamirpur (H.P).
Makarand S. Kulkarni is currently a Professor in the Department of Mechanical Engineering at the Indian Institute of Technology Bombay (IIT Bombay). He is associated with the Manufacturing Engineering group of the Department. He graduated in Production Engineering and later did his masters in Materials Technology from the Department of Metallurgical Engineering and Materials Science at IIT Bombay. Subsequently, he completed his Ph.D. in the area of Manufacturing Engineering from the Department of Mechanical Engineering at IIT Bombay.Back to Top
Table of Contents
2 Basic Reliability Mathematics
3 Machine Tool Performance Measures
4 Expert Judgement Based Parameter Estimation Method
for Machine Tool Reliability Analysis
5 Machine Tool Maintenance Scenarios, Models
6 Reliability and Maintenance Based Design of Machine Tools
7 Machine Tool Maintenance and Process Quality Control
8 Joint Optimization of Integrated Maintenance Scheduling
and Quality Control Policy with Production Scheduling
9 Machine Tool Reliability: Future Research Directions
Appendix A1: Java Code for Estimating Expected Number
Appendix A2: ‘MATLAB’ Genetic Algorithm Code for Joint
Optimization of Production Scheduling and
Index Back to Top