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001476047 001__ 1476047
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001476047 019__ $$a1394114372
001476047 020__ $$a9789819948505$$q(electronic bk.)
001476047 020__ $$a9819948509$$q(electronic bk.)
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001476047 0247_ $$a10.1007/978-981-99-4850-5$$2doi
001476047 035__ $$aSP(OCoLC)1394118219
001476047 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE$$dYDX$$dOCLCO
001476047 049__ $$aISEA
001476047 050_4 $$aTJ145
001476047 08204 $$a621$$223/eng/20230825
001476047 1001_ $$aMahalle, Parikshit N.
001476047 24510 $$aPredictive analytics for mechanical engineering :$$ba beginner's guide /$$cParikshit N. Mahalle, Pravin P. Hujare, Gitanjali Rahul Shinde.
001476047 260__ $$aSingapore :$$bSpringer,$$c2023.
001476047 300__ $$a1 online resource (107 p.).
001476047 4901_ $$aSpringerBriefs in applied sciences and technology, Computational intelligence
001476047 504__ $$aIncludes bibliographical references.
001476047 5050_ $$aIntro -- Preface -- Contents -- About the Authors -- 1 Introduction to Predictive Analytics -- 1.1 Data Analytics -- 1.2 Type of Data Analytics -- 1.2.1 Descriptive Analytics -- 1.2.2 Diagnostic Analytics -- 1.2.3 Predictive Analytics -- 1.2.4 Prescriptive Analytics -- 1.3 Techniques of Data Analytics -- 1.4 Predictive Analytics and Data Science -- 1.4.1 Predictive Analytics Process -- 1.5 Applications of Predictive Analytics -- 1.6 Summary -- References -- 2 Data Acquisition and Preparation -- 2.1 Exploratory Data Analysis -- 2.2 Types of Dataset -- 2.2.1 Categorization Based on Data Formats
001476047 5058_ $$a2.2.2 Categorization Based on Data Source -- 2.2.3 Categorization Based on Perspective of Data Generation -- 2.3 Data Preprocessing -- 2.3.1 Data Cleaning -- 2.3.2 Data Transformation -- 2.3.3 Data Reduction -- 2.4 Tools -- 2.5 Summary -- References -- 3 Intelligent Approaches -- 3.1 Overview -- 3.2 Conventional Learning Techniques -- 3.3 Deep Learning -- 3.4 Deep Neural Networks -- 3.5 Applications -- 3.6 Popular Techniques -- 3.7 Summary -- References -- 4 Predictive Maintenance -- 4.1 Overview -- 4.2 Predictive Maintenance and Machine Learning -- 4.3 Predictive Maintenance Model
001476047 5058_ $$a4.4 Implementation of Predictive Maintenance -- 4.5 Summary -- References -- 5 Predictive Maintenance for Mechanical Design System -- 5.1 Overview -- 5.2 Design Issues -- 5.2.1 Perception of Diagnostics and Prognostics -- 5.2.2 ML Algorithms for Fault Detection -- 5.2.3 Machine Learning-Based Bearing and Gear Health Indicators -- 5.2.4 AI for Condition-Based Monitoring and Fault Detection Diagnosis -- 5.3 Case Study -- 5.3.1 Predictive Analysis for the Useful Life of Bearing -- 5.3.2 Predictive Analysis for Gear Tooth Failure -- 5.4 Summary -- References
001476047 5058_ $$a6 Predictive Maintenance for Manufacturing -- 6.1 Overview -- 6.2 Design Issues -- 6.3 Case Studies -- 6.3.1 Predictive Analysis for Sound Absorption of Acoustic Material -- 6.4 Summary -- References -- 7 Conclusions -- 7.1 Summary -- 7.2 Research Opening -- 7.3 Future Outlook
001476047 506__ $$aAccess limited to authorized users.
001476047 520__ $$aThis book focus on key component required for building predictive maintenance model. The current trend of Maintenance 4.0 leans towards the preventive mechanism enabled by predictive approach and condition-based smart maintenance. The intelligent decision support, earlier detection of spare part failure, fatigue detection is the main slices of intelligent and predictive maintenance system (PMS) leading towards Maintenance 4.0 This book presents prominent use cases of mechanical engineering using PMS along with the benefits. Basic understanding of data preparation is required for development of any AI application; in view of this, the types of the data and data preparation processes, and tools are also presented in this book.
001476047 650_0 $$aMechanical engineering.
001476047 650_0 $$aMaintenance.
001476047 650_0 $$aPredictive analytics.
001476047 650_0 $$aIndustry 4.0.
001476047 650_6 $$aGénie mécanique.
001476047 650_6 $$aEntretien.
001476047 650_6 $$aIndustrie 4.0.
001476047 655_0 $$aElectronic books.
001476047 7001_ $$aHujare, Pravin P.
001476047 7001_ $$aShinde, Gitanjali Rahul,$$d1983-
001476047 77608 $$iPrint version:$$aMahalle, Parikshit N.$$tPredictive Analytics for Mechanical Engineering: a Beginners Guide$$dSingapore : Springer Singapore Pte. Limited,c2023$$z9789819948499
001476047 830_0 $$aSpringerBriefs in applied sciences and technology.$$pComputational intelligence.
001476047 852__ $$bebk
001476047 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-4850-5$$zOnline Access$$91397441.1
001476047 909CO $$ooai:library.usi.edu:1476047$$pGLOBAL_SET
001476047 980__ $$aBIB
001476047 980__ $$aEBOOK
001476047 982__ $$aEbook
001476047 983__ $$aOnline
001476047 994__ $$a92$$bISE