Book Image

Industrial Digital Transformation

By : Shyam Varan Nath, Ann Dunkin, Mahesh Chowdhary, Nital Patel
Book Image

Industrial Digital Transformation

By: Shyam Varan Nath, Ann Dunkin, Mahesh Chowdhary, Nital Patel

Overview of this book

Digital transformation requires the ability to identify opportunities across industries and apply the right technologies and tools to achieve results. This book is divided into two parts with the first covering what digital transformation is and why it is important. The second part focuses on how digital transformation works. After an introduction to digital transformation, you will explore the transformation journey in logical steps and understand how to build business cases and create productivity benefit statements. Next, you’ll delve into advanced topics relating to overcoming various challenges. Later, the book will take you through case studies in both private and public sector organizations. You’ll explore private sector organizations such as industrial and hi-tech manufacturing in detail and get to grips with public sector organizations by learning how transformation can be achieved on a global scale and how the resident experience can be improved. In addition to this, you will understand the role of artificial intelligence, machine learning and deep learning in digital transformation. Finally, you’ll discover how to create a playbook that can ensure success in digital transformation. By the end of this book, you’ll be well-versed with industrial digital transformation and be able to apply your skills in the real world.
Table of Contents (15 chapters)
Section 1: The "Why" of Digital Transformation
Section 2: The "How" of Digital Transformation

Applications of AI in industry

Let's explore how AI is being applied in areas such as manufacturing facilities, quality control and inspection, and predictive maintenance.

AI in factories

AI can enable the digital transformation of manufacturing and factories in many ways. Applications of AI increase productivity in the manufacturing process, improve the quality of products, optimize the use of warehouses, and allow predictive maintenance for many functions in the factory. A sensor is the first key enabling component for AI implementation in a factory. Data can also be available from Programmable Logic Controllers (PLCs), SCADA systems that monitor and control processes/equipment, quality monitoring systems, alarm systems, and even Enterprise Resource Planning (ERP) systems. There is a wide array of sensors available to collect data at every stage of production in the factory. These sensors can measure many important parameters, such as temperature, vibration, acoustic...