Title:
Hyperautomation for next-generation industries
Author:
Dhanaraj, Rajesh Kumar, editor.
ISBN:
9781394186518
9781394186501
9781394186495
Physical Description:
1 online resource
Contents:
Cover -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Journey To Hyperautomation: The Pathway of Today's Industries to Next Generation Industries -- 1.1 Introduction: What is Hyperautomation (HA)? -- 1.1.1 What Makes Hyperautomation Quite Crucial? -- 1.1.2 Benefits of Hyperautomation for Employees and Businesses -- 1.1.3 How Does It Work? -- 1.2 Technologies Associated with HA -- 1.2.1 Robotic Process Automation (RPA) -- 1.2.2 Artificial Intelligence/Machine Learning (AI/ML) -- 1.2.3 Optical Character Recognition (OCR) -- 1.2.4 Natural Language Processing (NLP) -- 1.2.5 Digital Twin of an Organization (DTO) -- 1.2.6 Process Mining -- 1.2.7 RPA Bot Example -- 1.3 Potential Benefits/Abilities of HA -- 1.4 Challenges in Hyperautomation -- 1.5 Applications -- 1.6 Case Studies -- 1.6.1 Touchless Accounts Reconciliation -- 1.6.2 AI-Enabled Healthcare Claims Processing -- 1.6.3 Investment Consultant -- 1.6.4 AI-Enabled Vacation Rental Site -- 1.6.5 Detection of Forged Signatures -- 1.6.6 IT Automation -- 1.6.7 Customer Service Based on Social Media Marketing and Sentiment Analysis -- 1.6.8 Data Center Migration -- 1.7 Conclusion -- References -- Chapter 2 Software Robot for Next Generation Industries Using RPA -- 2.1 Introduction -- 2.2 Evolution of Industries -- 2.2.1 Industry 4.0 -- 2.2.2 Industry 5.0: The Future -- 2.2.2.1 What is the Purpose of Industry 5.0? -- 2.2.2.2 How to Make It Happen? -- 2.2.3 RPA and Industry 4.0 -- 2.2.4 RPA and Industry 5.0 -- 2.3 Robotic Process Automation -- 2.3.1 Features of Robotic Process Operation -- 2.3.2 Types of Robotic Process Automation -- 2.3.3 The Key Performance Indicators of RPA -- 2.3.4 Benefits of Robotic Process Automation -- 2.3.5 Business Automation Using RPA -- 2.3.6 Features and Capabilities of RPA -- 2.3.7 RPA: The Fastest Growing Enterprise Software in the World.
2.3.8 The Role of API Integration in Process Automation -- 2.4 Case Studies -- 2.4.1 Enhancing the Platform for End-to-End Automation -- 2.4.2 RPA for Finance and Accounting -- 2.4.3 Intelligent Document Processing -- 2.4.4 A Three-Way Model for Automation -- 2.4.5 A Three-Stage, Basic Model -- 2.4.6 The Essential Elements -- 2.5 Debunking RPA Rumors -- 2.6 Conclusion -- References -- Chapter 3 Artificial Intelligence-Based Hyperautomation for Smart Factory Process Automation -- 3.1 Introduction -- 3.1.1 Smart Factory -- 3.1.2 Advantages of Smart Factory -- 3.1.3 Smart Factory Levels -- 3.1.3.1 Simple Access to Information -- 3.1.3.2 Proactively Analyzing Data -- 3.1.3.3 Present Data -- 3.1.3.4 Actionable Information -- 3.1.4 Technologies Used in Smart Factory -- 3.1.4.1 Sensors -- 3.1.4.2 Cloud Computing -- 3.1.4.3 Big Data Analytics -- 3.1.4.4 Virtual and Augmented Reality -- 3.1.4.5 Digital Twins -- 3.1.4.6 IoTs -- 3.1.5 The Fundamentals of a Smart Factory -- 3.1.6 Challenges -- 3.1.7 Industry 5.0 -- 3.2 Hyperautomation -- 3.2.1 What is Hyperautomation? -- 3.2.2 Basic Components of Hyperautomation -- 3.2.3 RPA -- 3.2.3.1 Selecting the Appropriate Business Processes for Automation -- 3.2.3.2 Scaling Up Operations and Programs for Digital Process Automation -- 3.2.3.3 Considering Regulatory and Corporate Restrictions, i.e., Competing Initiatives -- 3.2.3.4 Controlling and Observing Automation in an Efficient Manner -- 3.2.3.5 Prior to Automating Business Processes, Improve Them -- 3.2.4 Hyperautomation's Emergence -- 3.2.5 Advanced Technologies -- 3.2.5.1 Artificial Intelligence (AI) -- 3.2.5.2 Advanced Analytics -- 3.2.5.3 Intelligent Automation -- 3.2.5.4 Administration of Information -- 3.2.6 Hyperautomation Advantages -- 3.2.6.1 Employee Empowerment -- 3.2.6.2 Employee Training -- 3.2.6.3 Integration of Systems -- 3.2.6.4 Digital Nimbleness.
3.2.6.5 Return on Investment -- 3.2.7 Increasing Trends in Hyperautomation -- 3.2.8 Hyperautomation Roadmap -- 3.2.9 Hyperautomation Work Flow Methodology -- 3.3 Hyperautomation-Based Industrial Ecosystem -- 3.3.1 Robotic Process Automation -- 3.3.2 Process Mining -- 3.3.3 AI -- 3.3.4 iBPMSs -- 3.3.5 Advanced Analytics -- 3.3.6 Approach to Delivery for Hyperautomation -- 3.3.6.1 Imagine -- 3.3.6.2 Deliver -- 3.3.6.3 Run -- 3.3.6.4 Benefits of Delivery Approach for Hyperautomation -- 3.4 Artificial Intelligence -- 3.4.1 Concepts of Artificial Intelligence -- 3.4.2 Shallow Learning -- 3.4.2.1 Support Vector Machine (SVM) -- 3.4.2.2 Random Forest RF -- 3.4.2.3 KNN -- 3.4.3 Deep Learning -- 3.4.4 Deep Reinforcement Learning -- 3.4.5 NLP -- 3.4.5.1 Practical Applications for NLP in RPA -- 3.5 Hyperautomation Use Cases and Examples in Industry/ Factory Processes -- 3.5.1 Payables Accounts -- 3.5.2 Journey and Expense -- 3.5.3 Handling Claims -- 3.5.3.1 Insurance Occurrences -- 3.5.3.2 Occupational Claims -- 3.5.4 Cash Order (O2C) -- 3.5.5 Additional Document Handling -- 3.5.6 Operations for Customer Service -- 3.5.7 Obtaining Leads From Anonymous Website Visitors -- 3.5.8 Processing for Underwriting -- 3.5.9 Redaction to Protect Privacy -- 3.5.10 Anti-Money Laundering (AML) -- 3.5.11 Underwriting a Loan -- 3.5.12 Customer Onboarding for Banks -- 3.6 Artificial Intelligence-Based Hyperautomation for Smart Factory Process Automation -- 3.6.1 Industry 4.0 Intelligent Automation Solution Based on the IoTs and Machine Learning -- 3.6.2 Soft Sensors Powered by Deep Learning to Increase Industrial Automation's Adaptability -- 3.6.3 Analysis of Robot Control System Optimization Design Using Artificial Intelligence -- 3.6.4 Automation of the Power Distribution Network Using AI -- 3.6.5 Modular Deep RL and Policy Transfer Allow for Flexible Automation.
3.6.6 Hyperautomation in the Auto Industry -- 3.6.7 Hyperautomation in Transforming Under Writing Operation in the Life Insurance Industry -- 3.7 Conclusion -- References -- Chapter 4 Intelligent Assistants Using Natural Language Processing for Hyperautomation -- 4.1 Introduction -- 4.1.1 Hyperautomation -- 4.1.2 Automation vs Hyperautomation -- 4.1.3 Natural Language Processing (NLP) -- 4.1.4 Components of Natural Language Processing -- 4.1.4.1 Natural Language Generation (NLG) -- 4.1.4.2 Natural Language Understanding (NLU) -- 4.1.5 NLP in Intelligent Automation -- 4.1.6 NLP in Robotic Process Automation (RPA) -- 4.2 Phases of NLP -- 4.2.1 Morphological Analysis -- 4.2.2 Syntactic Analysis -- 4.2.2.1 Parsing -- 4.2.2.2 Derivation -- 4.2.3 Semantics Analysis -- 4.2.4 Discourse Integration -- 4.2.5 Pragmatic Analysis -- 4.3 NLP Application in Web/Android Services -- 4.3.1 Chatbox -- 4.3.2 AI Assistant -- 4.3.3 Search Result -- 4.3.4 Digital Phone Call -- 4.3.5 Machine Translation -- 4.4 Role of NLP in Internet Protocol -- 4.4.1 Market Intelligent -- 4.4.2 Text Analytics -- 4.4.2.1 Benefits of Text Analytics -- 4.4.3 Data Analysis -- 4.4.4 E-mail Analysis -- 4.4.4.1 Dataset -- 4.4.4.2 ETL Pipeline -- 4.4.4.3 AI Pipeline -- 4.4.5 Predictive Text -- 4.4.6 Auto Correct -- References -- Chapter 5 Digital Twins for Hyperautomation for Next Generation -- 5.1 Introduction -- 5.2 Hyperautomation Requirement -- 5.3 Literature Review -- 5.4 Hyperautomation Methodology -- 5.5 Background of Hyperautomation -- 5.6 Hyperautomation Enhancement -- 5.7 Association of Versatile Technologies with Hyperautomation -- 5.8 Hyperautomation Workflow -- 5.9 Hyperautomation Domains -- 5.10 Path to Hyperautomation -- 5.11 Automation Process Categories -- 5.12 Sophistication of the Automation -- 5.13 Technologies in Hyperautomation.
5.14 Technological Ecosystem of Hyperautomation -- 5.15 Future Scope of Hyperautomation -- 5.16 Conclusion -- References -- Chapter 6 IQ Bot for Intelligent Document Process and Mail Processing -- 6.1 Introduction to IQ Bot -- 6.2 Understanding the Internal Operations of the IQ Bot -- References -- Chapter 7 Bot-Based Process Triggering by Incoming E-mails and Documents -- 7.1 Introduction of Bot -- 7.1.1 What are Bots? -- 7.1.2 Chat Bots and their Influence in the Industry -- 7.1.3 Bot Based on RPA -- 7.2 Bot Triggering by Incoming E-mail and Incoming Document -- 7.2.1 The Technologies Behind E-mail Bots -- 7.2.2 E-mail Bots and Other Systems -- 7.2.3 E-mail Bot Expected Results -- 7.2.4 Automate Handling of Incoming Documents with Documentbot -- 7.3 Types of Bots -- 7.3.1 Malicious and Non-Malicious Bot Activity -- 7.3.2 Scraper Bots -- 7.3.3 Spam Bots -- 7.3.4 Social Media Bots -- 7.3.5 Spider Bots -- 7.3.6 Ticketing Bots -- 7.3.7 Download Bots -- 7.4 Various Other Bot Triggers -- 7.4.1 Add a Hotkey Trigger -- 7.4.2 Add an Interface Trigger -- 7.4.3 Add a Process Trigger -- 7.4.4 Add a Service Trigger -- 7.5 Applications of Bot Trigger -- 7.5.1 Software Application for Particular Task-Performance -- 7.5.2 Instant Messenger Applications -- 7.5.3 Bots Used on Applications -- References -- Chapter 8 Hyperautomation for Automating the Customer Service Operations -- 8.1 Introduction -- 8.2 Advantages of Hyperautomation -- 8.3 Issues With Hyperautomation -- 8.4 Use Cases of Hyperautomation -- 8.5 Customer Service Hyperautomation -- 8.6 Customer Support Hyperautomation: Where We are Now and Where We are Headed -- 8.7 Benefits of Customer Service Hyperautomation -- 8.8 Reforming the Future of Customer Service Operation through Hyperautomation -- 8.9 Case Study: Hyperautomation in Customer Onboarding -- 8.10 Conclusion -- References.
Abstract:
This book is essential for anyone looking to understand how hyperautomation can revolutionize businesses by simplifying operations, reducing errors, and creating more intelligent and adaptable workplaces through the use of automation technologies such as artificial intelligence, machine learning, and robotic process automation. The use of automation technologies to simplify any and every activity conceivable in a business, allowing repeated operations to operate without manual intervention, is known as hyperautomation. Hyperautomation transforms current and old processes and equipment by utilizing artificial intelligence, machine learning, and robotic process automation. This digital transformation may assist a business in gaining cost and resource efficiency, allowing it to prosper in a more competitive environment. With the advancement of automation technologies, hyperautomation is becoming more prevalent. Companies are shifting their methods to create more human-centered and intelligent workplaces. This change has ushered in a new era for organizations that rely on technology and automation tools to stay competitive. Businesses may move beyond technology's distinct advantages to genuine digital agility and scale adaptability when all forms of automation operate together in close partnership. Automation tools must be simple to incorporate into the current technological stack while not requiring too much effort from IT. A platform must be able to plug and play with a wide range of technologies to achieve hyperautomation. The interdependence of automation technologies is a property that is connected to hyperautomation. Hyperautomation saves individuals time and money by reducing errors. Hyperautomation has the potential to create a workplace that is intelligent, adaptable, and capable of making quick, accurate decisions based on data and insights. Model recognition is used to determine what to do next and to optimize processes with the least amount of human engagement possible.
Local Note:
John Wiley and Sons
Genre:
Added Author:
Electronic Access:
https://onlinelibrary.wiley.com/doi/book/10.1002/9781394186518Copies:
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