TY  - GEN
TI  - Operations management and data analytics modelling: : economic crises perspective
SN  - 9780367754518
U1  - 658.4033 
PY  - 2022///
CY  - Boca Raton
PB  - CRC Press
KW  - Production management - Statistical methods
KW  - Industrial management - Statistical methods
N1  - Table of Contents:  1.Measuring Banking Sector Efficiency: A Malmquist Approach 2.A Hybrid MCDM Model Combining Entropy Weight Method with Range of Value (ROV) Method and Evaluation Based on Distance from Average Solution (EDAS) Method for Supplier Selection in Supply Chain Management 3.Quality Loss function deployment in Fused Deposition Modelling 4.Effect of Physical Attributes of Coconut on Effective Husk Separation: A Review 5.Selection of Features and classifier for Controlling the Prosthetic Devices 6.An intelligent solution for e-waste collection: vehicle routing optimization 7.Identification of most significant parameter in estimating of solar irradiance at any location -A review 8.Assessment of Sustainable Product Returns and Recovery practices in Indian Textile Industries 9.Integrating reliability-based preventive maintenance in job shop scheduling; a simulation study 10.Prioritizing Circular Economy Performance Measures: A Case of Indian Rubber Industries 11.Fuzzy FMEA application in healthcare industry 12.Drivers of industry 4.0 in a circular economy initiative in the context of emerging market 13.Strategies to manage perishability in Perishable Food Supply Chain 14.Six Sigma: Integration with Lean and Green
N2  - The book covers operational management issues in key industries such as healthcare, energy management, and Industry 4.0. Recent developments and trends in developing data-driven operation management-based methodologies, big data analysis, application of computers in industrial engineering, optimization techniques, development of decision support systems for industrial operation, the role of a multiple-criteria decision-making (MCDM) approach in operation management, fuzzy set theory-based operation management modelling, and Lean Six Sigma are discussed. This book is intended for graduate students and experts in industrial and production engineering, mechanical engineering, and materials science
ER  -