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    Intelligent Manufacturing: Smart Choice
    Intelligent Manufacturing: Smart Choice
    Intelligent Manufacturing: Smart Choice
    Ebook180 pages1 hour

    Intelligent Manufacturing: Smart Choice

    By Sunil Kumar Wadhwa

    ()

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    About this ebook

    A comprehensive step-by-step approach for Manufacturing Professionals to Embark on a Digital Transformation journey to take on Competition and be Sustainable as part of your business strategy. With help of this book, one can relate easily the advance manufacturing techniques with conventional wisdom and practices to increase productivity, reduce

    LanguageEnglish
    PublisherSunil Wadhwa
    Release dateMar 13, 2023
    ISBN9781802279146
    Intelligent Manufacturing: Smart Choice

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      Book preview

      Intelligent Manufacturing - Sunil Kumar Wadhwa

      eBook

      Intelligent Manufacturing

      Intelligent Manufacturing

      A Smart Choice…

      Abstract

      This book contains general information only, and the author or contributors are not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. Your use of the book’s contents is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your finances or your business.

      Before making any decision or taking any action that may affect your finances or your business, you should consult a qualified professional. Author does not make representation or warranty, express or implied. Your use of the book’s contents is solely at your own risk. This book may contain links to third party content, which author does not warrant, endorse, or assume liability for.

      Sunil Kumar Wadhwa

      Swadhwa2097@gmail.com

      Copyright © 2023 by Sunil Wadhwa

      All rights reserved. No part of this book may be reproduced or used in any manner without written permission of the copyright owner except for the use of quotations in a book review. For more information, contact: Swadhwa2097@gmail.com

      First paperback edition 2023

      978-1-80227-915-3 (paperback)

      978-1-80227-914-6 (eBook)

      Acknowledgments

      I feel immense pleasure in writing my first book. Inspired by my beloved parents, family, teachers, colleagues, partners and students of all ages and groups. I was fortunate to travel to many countries in last 30+ years during my professional career and learn while working with professionals of Manufacturing, Industrial Automation, and IT systems. My sincere thanks to all who contributed to my work directly or indirectly and look forward to receiving your patronage and blessings in future as well.

      I have witnessed and experienced many changes in technology over past several decades, but nothing as compared to Industry 4.0 revolution. The enormity of impact and complexity has moved every pebble in Industrial world. Being in the middle of this exponential change, one of the greatest challenges is sharing the knowledge and learnings as we embrace the new technology. This book is my bit of contribution to be the bridge to connect among technical & industrial community. While I enjoyed writing this book, I hope this learning and sharing of knowledge will continue to grow with your valuable feedbacks and support.

      Contents

      Introduction

      Change is Imminent

      Industry 4.0 Challenges

      Who is Henrik von Scheel?

      The Journey so Far

      Key Pressure Points of Manufacturing

      Key Business Challenges addressed by Intelligent Manufacturing

      Primary Business Drivers of Industry 4.0

      Industry 4.0 Ecosystem (Overall)

      Industry 4.0 Ecosystem for Manufacturing

      Industry 4.0 and Intelligent Manufacturing Initiatives

      Skills and Education

      Big Data for Manufacturing

      Water Cycle Analogy of Data Cycle

      Fabric of Industry 4.0

      Five Layers of Automation Pyramid

      Level 0 – Field Level/Production Process

      Level 1 – Control Level/Sensing and Manipulation

      Level 2 – Supervisory Level/Monitoring and Supervising (SCADA)

      Level 3 – Execution and Operations Management

      Level 4 – Enterprise Level (Business Planning and Logistics)

      Level 5, 6 & 7 – Cloud layer

      Design Consideration for Cyber-Physical System

      Lifecycle Value Stream

      Hierarchy Levels

      Architecture Layer

      Core Design Principles

      Cloud-Native Architecture

      The Five Stages of Product Design Thinking

      Communication Protocols

      Proprietary Interfaces

      OPC Protocol

      OPC UA Protocol

      PLC4X

      MQTT & AMQP Protocols

      Apache Kafka

      Apache NiFi – S2S Protocol

      Manufacturing Execution System (MES/MOM) (Level-3)

      1. Production Management, Execution/Workflow

      2. In-Process Quality Management

      3. Data Management/Data Collection

      4. Regulatory Compliance/Track-Trace/Automated Routing

      5. Analytics/Reporting/Performance

      6. Production Equipment Integration

      7. Enterprise Integration Architecture

      8. Usability/User Experience

      9. Deployment Experience and Options

      10. Ease of System Upgrade

      11. MES/MOM Architectural Innovation

      Business Use Cases

      Productivity Suite

      Agile Production Planning and Scheduling

      Overall Equipment Effectiveness (OEE)

      Throughput

      Cycle Time

      Changeover Time

      Takt Time

      Track and Trace

      Inventory Turns

      Return on Assets (ROA)

      Downtime to Operating Time

      Capacity Utilization

      First Pass Yield

      Predictive Production and Transparency in Delivery

      Intelligent Supply Chain

      Predictive and Prescriptive Analytics

      Predictive Maintenance

      Prescriptive Maintenance

      Predictive Quality

      Additive Manufacturing or 3D printing

      Digital Twin

      Component Twins/Parts Twins

      Asset Twins

      System or Unit Twins

      Process Twins

      Competitive Gains using Intelligent Manufacturing

      Glossary

      Testimonials

      References

      Table of Figures

      Figure 1: Industrial Smoke’s color reveals fuel type

      Figure 2: Industrial revolution at gigantic scale

      Figure 3: Survey on Top Challenges in Deploying IIoT Technology (Source: LNS Research)

      Figure 4: A history of Industrial Revolutions

      Figure 5: Paradigm Shift in Key Success Factor

      Figure 6: Digitally – Primary Business Drivers of Industry 4.0

      Figure 7: 17 Pillars of Fourth Industrial Revolution 4IR (Source: The Manufacturer)

      Figure 8: Overall Industry 4.0 Ecosystem

      Figure 9: Industry 4.0 Ecosystem

      Figure 10: IIoT Use cases (Source: Orange_5G_IIot_whitepaper_dec2018)

      Figure 11: Big data is World’s Natural Resource for next century

      Figure 12: Three Vs of Big Data

      Figure 13: Big Data Market CAGR figures (Source: Data Age 2025, by Seagate, Nov 2018)

      Figure 14: Hydrosphere and water cycle

      Figure 15: Manufacturing Data Cycle

      Figure 16: Data Lake Layers and Pipeline

      Figure 17: Classical Siloed System in an Enterprise

      Figure 18: Integrated and Connected Systems in manufacturing process

      Figure 19: Automation Pyramid and its Functional layers

      Figure 20: SCADA system at level-2

      Figure 21: Real Time Data from SCADA /MES sent to upper-level Business Applications

      Figure 22: Data Lake operational excellence

      Figure 23: Reshape the Automation Pyramid (Source: OPCFoundation.org webpage by SAP SE)

      Figure 24: The RAMI 4.0, Reference Architecture Model Industry 4.0 (Source: www.zvei.org)

      Figure 25: Design Thinking is a 5-Stage Process (Source: interaction-design.org)

      Figure 26: Connectivity Solution Diagram with an Enterprise (Source; Atos SE, 2021)

      Figure 27: Digital manufacturing proprietary network landscape

      Figure 28: OPC UA for Field Level Communication (Source: https://opcconnect.opcfoundation.org)

      Figure 29: End-to-end Kafka Data Pipeline (Source: www.instaclustr.com)

      Figure 30: Business Value of MES Implementation Survey (Source: MESA International/Gartner, 2017)

      Figure 31: Functional Definition of Production System and Data Flow (Source: www.isa.org)

      Figure 33: OEE Calculations demonstration

      Figure 34: Bottleneck Management Solution

      Figure 35: Advance Manufacturing value chain

      Figure 36: Typical ERP-MES Interface topics

      Figure 37: Intelligent Supply Chain Management solution

      Figure 38: Potential of three-dimensional printing for orthopaedic applications

      Figure 39: A Schematic Flow of creating three dimensional (3D) printed product

      Figure 40: K, Sreenivasulu Manager HR, HRBP at Mahindra & Mahindra (Sep 2022) after a session conducted on Advance Manufacturing for 100+ their employees.

      Figure 41: Hardikar, Saket (Sep 2022) wrote after conducting an interview on "Impact of Agile Manufacturing on production Planning and Sequencing on Automotive World.

      List of Tables

      Table 1: Common Terms and Definitions for Data operations

      Table 2: Characteristics of enabling technologies

      Introduction

      At times, white smoke can often mean that material is off-gassing moisture and water vapour, meaning the fire is just starting to consume the material. White smoke can also indicate light and flashy fuels such as grass or twigs.

      Smoke is made up of particulates, aerosols and gases, and identifying the characteristics of each in a given smoke plume can be helpful when fighting fires. Reading smoke can tell a firefighter what is currently happening with a fire as well as what might happen in the future. One particularly important factor in predicting fire behaviour is the colour of the smoke emitted.

      Smoke is the by-product of the fuels it is burning. The colour of the smoke indicates to firefighters the type and density of the fuels involved, all of which give hints as to what the fire might do next.

      Thick, black smoke indicates heavy fuels that are not being fully consumed. At times,

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