authors: Amit Sinha, Ednilson Bernardes, Rafael Calderon, Thorsten Wuest
about the book: No.1 New Release on Amazon in 5 categories
Deliver unprecedented customer value and seize your competitive edge with a transformative digital supply network
Digital tech has disrupted life and business as we know it, and supply chain management is no exception. But how exactly does digital transformation affect your business? What are the breakthrough technologies and their capabilities you need to know about? How will digital transformation impact skills requirements and work in general? Do you need to completely revamp your understanding of supply chain management? And most importantly: How do you get started?
Digital Supply Networks provides clear answers to these and many other questions. Written by an experienced team comprised of Deloitte consultants and leading problem-driven scholars from a premier research university, this expert guide leads you through the process of improving operations building supply networks, increasing revenue, reimagining business models, and providing added value to customers, stakeholders, and society. You’ll learn everything you need to know about:
- Stages of development, roles, capabilities, and the benefits of DSN
- Big data analytics including its attributes, security, and authority
- Machine learning, Artificial Intelligence, Blockchain, robotics, and the Internet of Things
- Synchronized planning, intelligent supply, and digital product development
- Vision, attributes, technology, and benefits of smart manufacturing, dynamic logistics, and fulfillment
- A playbook to guide the digital transformation journey
Drawing from real world-experience and problem-driven academic research, the authors provide an in-depth account of the transformation to digitally connected supply networks. They discuss the limitations of traditional supply chains and the underlying capabilities and potential of digitally-enabled supply flows. The chapters burst with expert insights and real-life use cases grounded in tomorrow’s industry needs.
Success in today’s hyper-competitive, fast-paced business landscape, characterized by the risk of black swan events, such as the 2020 COVID-19 global pandemic, requires the reimagination and the digitalization of complex demand-supply systems, more collaborative and connected processes, and smarter, more dynamic data-driven decision making―which can only be achieved through a fully integrated Digital Supply Network.
authors: Ramy Harik & Thorsten Wuest
about the book:
Introduction to Advanced Manufacturing was written by two experienced and passionate engineers whose mission is to make the subject of advanced manufacturing easy to understand and a practical solution to everyday problems. Harik, Ph.D. and Wuest, Ph.D., professors who have taught the subject for decades, combined their expertise to develop both an applied manual and a theoretical reference that addresses many different needs.
Introduction to Advanced Manufacturing covers the following topics in detail:
- Composites Manufacturing
- Smart Manufacturing
- Additive Manufacturing
- Computer Aided Manufacturing
- Polymers Manufacturing
- Assembly Processes
- Manufacturing Quality Control and Productivity
- Subtractive Manufacturing
- Deformative Manufacturing
Introduction to Advanced Manufacturing offers a new, refreshing way of studying how things are made in the digital age. With academics and industry professionals in mind, Introduction to Advanced Manufacturing paves the ground for those interested in the new opportunities of Industry 4.0.
author: Thorsten Wuest
about the book:
The book reports on a novel approach for holistically identifying the relevant state drivers of complex, multi-stage manufacturing systems. This approach is able to utilize complex, diverse and high-dimensional data sets, which often occur in manufacturing applications, and to integrate the important process intra- and interrelations. The approach has been evaluated using three scenarios from different manufacturing domains (aviation, chemical and semiconductor). The results, which are reported in detail in this book, confirmed that it is possible to incorporate implicit process intra- and interrelations on both a process and programme level by applying SVM-based feature ranking. In practice, this method can be used to identify the most important process parameters and state characteristics, the so-called state drivers, of a manufacturing system. Given the increasing availability of data and information, this selection support can be directly utilized in, e.g., quality monitoring and advanced process control. Importantly, the method is neither limited to specific products, manufacturing processes or systems, nor by specific quality concepts.