TY  - CHAP
AU  - Mohammed Ziyan Sheriff
AU  - Nour Basha
AU  - Muhammad Nazmul Karim
AU  - Hazem Nounou
AU  - Mohamed Nounou
ED  - Fausto Pedro García Márquez
Y1  - 2019-08-07
PY  - 2019
T1  - Fault Detection of Single and Interval Valued Data Using Statistical Process Monitoring Techniques
N2  - This book presents the main concepts, state of the art, advances, and case studies of fault detection, diagnosis, and prognosis. This topic is a critical variable in industry to reach and maintain competitiveness. Therefore, proper management of the corrective, predictive, and preventive politics in any industry is required. This book complements other subdisciplines such as economics, finance, marketing, decision and risk analysis, engineering, etc. The book presents real case studies in multiple disciplines. It considers the main topics using prognostic and subdiscipline techniques. It is essential to link these topics with the areas of finance, scheduling, resources, downtime, etc. to increase productivity, profitability, maintainability, reliability, safety, and availability, and reduce costs and downtime. Advances in mathematics, modeling, computational techniques, dynamic analysis, etc. are employed analytically. Computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques are expertly blended to support the analysis of prognostic problems with defined constraints and requirements. The book is intended for graduate students and professionals in industrial engineering, business administration, industrial organization, operations management, applied microeconomics, and the decisions sciences, either studying maintenance or needing to solve large, specific, and complex maintenance management problems as part of their jobs. The work will also be of interest to researches from academia.
BT  - Fault Detection, Diagnosis and Prognosis
SP  - Ch. 6
UR  - https://doi.org/10.5772/intechopen.88217
DO  - 10.5772/intechopen.88217
SN  - 978-1-78984-214-2
PB  - IntechOpen
CY  - Rijeka
Y2  - 2024-04-20
ER  -