P. K. Kapur – författare

This book explores how transformative changes driven by the new-age economy can bring about improvements in a company''s engineering and manufacturing capabilities.

The new-age economy is driven by advanced engineering and manufacturing practices, processes, and technologies, including the Internet of Things (IoT), Cloud Computing, Blockchain, Artificial Intelligence, Robotics, Cyber-Physical Systems (CPS), and Internet-enabled systems to automate industrial processes.

Today''s business dynamics are governed by uncertainties, disruptions, complexities, and ambiguities that demand quicker and more intelligent decisions. These changes could relate a renaissance in the company''s engineering and manufacturing capabilities. To sustain these volatile and ever-changing business dynamics, Industry 4.0 and 5.0 have revolutionized how organizations operate and make intelligent business decisions. Moreover, the extensive role of business analytics has overcome the limitations ofclassical computing through new technologies and intelligent computing methodologies.

Over the past few years, much emphasis has been given to investing in developing hardware and programming frameworks for achieving computational intelligence using fuzzy logic, evolutionary computation, neural networks, probabilistic methods, and learning theory. Within this frame of reference, the reliability, quality, and maintenance of complex industrial and manufacturing systems are essential for organizations to utilize them successfully for informed decisions.

This book presents a range of qualitative and quantitative analyses in areas such as cybersecurity, sustainability, multivariate analysis, customer satisfaction, parametric programming, software reliability growth modeling, and blockchain technology, to name but a few. It also highlights integrated methods and practices in the areas of machine learning and genetic algorithms. After discussing applications in supply chains and logistics, cloud computing, six sigma, production management, big data analysis, satellite imaging, game theory, biometric systems, quality, and system performance, the book examines the latest developments and breakthroughs in the field of science and technology, and provides novel problem-solving methods.

The themes discussed in the book link contributions by researchers and practitioners from different branches of engineering and management, and hailing from around the globe. These contributions provide scholars with aplatform to derive maximum utility in the area of analytics by subscribing to the idea of managing business through system sciences, operations, and management. Managers and decision-makers can learn a great deal from the respective chapters, which will help them devise their own business strategies and find real-world solutions to complex industrial problems.

This book systematically examines and quantifies industrial problems by assessing the complexity and safety of large systems. It includes chapters on system performance management, software reliability assessment, testing, quality management, analysis using soft computing techniques, management analytics, and business analytics, with a clear focus on exploring real-world business issues. Through contributions from researchers working in the area of performance, management, and business analytics, it explores the development of new methods and approaches to improve business by gaining knowledge from bulk data. With system performance analytics, companies are now able to drive performance and provide actionable insights for each level and for every role using key indicators, generate mobile-enabled scorecards, time series-based analysis using charts, and dashboards.