Industrial IoT (Internet of Things) for Manufacturing Professionals

Purpose:

Unlike other technologies, IoT is far more complex encompassing almost every branch of core Engineering-Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics and Mobile. For each of its engineering layers, there are aspects of economics, standards, regulations and evolving state of the art. This is for the firs time, a modest course is offered to cover all of these critical aspects of IoT Engineering. For manufacturing professional, most critical aspect is to understand the advancement in the area of Industrial Internet of things, which includes predictive and preventative maintenance, condition based monitoring of the machines, production optimization, energy optimization, supply-chain optimization and uptime of manufacturing utilities etc.

Summary:

  • An advanced training program covering the current state of the art in Internet of Things in Smart Factories.
  • Cuts across multiple technology domains to develop awareness of an IoT system and its components and how it can help manufacturing managerial professionals.
  • Live demo of model IIoT applications for smart factories.
  • Target Audience:

  • Managers responsible for business and operational processes within their respective manufacturing organizations and want to know how to harness IoT to make their systems and processes more efficient.
  • Duration:    3 Days ( 8 hours / day).


    Prerequisites:

  • Basic knowledge of business operation, devices, electronics systems and data systems.
  • Basic understanding of software and systems.
  • Basic understanding of Statistics (in Excel levels).

  • Overview:

    Estimates for Internet of Things or IoT market value are massive, since by definition the IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly huge number of connections: 1.9 billion devices today, and 9 billion by 2018. That year, it will be roughly equal to the number of smartphones, smart TVs, tablets, wearable computers, and PCs combined.

    In the consumer space, many products and services have already crossed over into the IoT, including kitchen and home appliances, parking, RFID, lighting and heating products, and a number of applications in Industrial Internet.

    However the underlying technologies of IoT are nothing new as M2M communication existed since the birth of Internet. However what changed in last couple of years is the emergence of number of inexpensive wireless technologies added by overwhelming adaptation of smart phones and Tablet in every home. Explosive growth of mobile devices led to present demand of IoT.

    Industrial IoT, or IIoT for manufacturing has been widely in use since 2014 and since then a large number of IIoT innovations have taken place. This course will introduce all the important aspects of innovations in Industrial IoT area.

    This training is intended for a technology and business review of an emerging industry so that IoT enthusiasts/entrepreneurs can grasp the basics of IoT technology and business.


    Course Objective:

    Main objective of the course is to introduce emerging technological options, platforms and case studies of IoT implementation in smart factories for manufacturing sectors.

    1. Basic introduction of all the elements of IoT-Mechanical, Electronics/sensor platform, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data-analytics and Total control plane.

    2. M2M Wireless protocols for IoT- WiFi, LoPan, BLE, Ethernet, Ethercat, PLC : When and where to use which one.?

    3. Mobile/Desktop/Web app- for registration, data acquisition and control.

    4. Security issues and security solutions for IIoT.

    5. Open source/commercial electronics platform for IoT-Raspberry Pi, Arduino , ArmMbedLPC etc.

    6. Open source /commercial enterprise cloud platform for AWS-IoT apps, Azure -IOT, Watson-IOT, Mindsphere IIoT cloud in addition to other minor IoT clouds

    7. Studies of business and technology of some of the common IIoT platform like Siemens MindSphere and Azure IoT.

    Course Outline:


    Session 1: Business Overview of Why IoT is So Important
  • Case Studies from Nest, CISCO and top industries
  • IoT adaptation rate in North American & and how they are aligning their future business model and operation around IoT
  • Broad Scale Application Area
  • Smart Factory of 2020
  • Industrial Internet
  • Energy and cost optimization of manufacturing plants
  • Business Rule Generation for IoT
  • 3 layered architecture of Big Data — Physical (Sensors), Communication, and Data Intelligence
  • Session 2: Introduction to IoT : All About Sensors
  • Basic function and architecture of a sensor — sensor body, sensor mechanism, sensor calibration, sensor maintenance, cost and pricing structure, legacy and modern sensor network — all the basics about the sensors
  • Development of sensor electronics — IoT vs legacy, and open source vs traditional PCB design style
  • Development of sensor communication protocols — history to modern days. Legacy protocols like Modbus, relay, HART to modern day Zigbee, Zwave, X10,Bluetooth, ANT, etc.
  • SigFox, LoRA and other LPWAN
  • Business driver for sensor deployment — FDA/EPA regulation, fraud/tempering detection, supervision, quality control and process management
  • Different Kind of Calibration Techniques — manual, automation, infield, primary and
  • secondary calibration — and their implication in IoT
  • Powering options for sensors — battery, solar, Witricity, Mobile and PoE
  • Hands on training with single silicon and other sensors like temperature, pressure, vibration, magnetic field, power factor etc.
  • : Logging data from a temperature sensor
    Session 3: Fundamentals of M2M Communication : Sensor Network and Wireless Protocols
  • What is a sensor network? What is ad-hoc network?
  • Wireless vs. Wireline network
  • WiFi- 802.11 families: N to S — application of standards and common vendors.
  • SigFox, LoRA and other LPWAN
  • Zigbee and Zwave — advantage of low power mesh networking. Long distance Zigbee. Introduction to different Zigbee chips.
  • Bluetooth/BLE: Low power vs high power, speed of detection, class of BLE. Introduction of Bluetooth vendors & their review.
  • Creating network with Wireless protocols such as Piconet by BLE
  • Protocol stacks and packet structure for BLE and Zigbee
  • Other long distance RF communication link
  • LOS vs NLOS links
  • Capacity and throughput calculation
  • Application issues in wireless protocols — power consumption, reliability, PER, QoS, LOS
  • Sensor networks for WAN deployment using LPWAN. Comparison of various emerging protocols such as LoRaWAN, NB-IoT etc.
  • Sensor networks for WAN deployment using LPWAN. Comparison of various emerging protocols such as LoRaWAN, NB-IoT etc.
  • Demo : Device control using BLE
    Session 4: Review of Electronics Platform, Production and Cost Projections
  • PCB vs FPGA vs ASIC design-how to take decision
  • Prototyping electronics vs Production electronics
  • QA certificate for IoT- CE/CSA/UL/IEC/RoHS/IP65: What are those and when needed?
  • Basic introduction of multi-layer PCB design and its workflow
  • Electronics reliability-basic concept of FIT and early mortality rate
  • Environmental and reliability testing-basic concepts
  • Basic Open source platforms: Arduino, Raspberry Pi, Beaglebone, when needed?
  • Session 5: Hardware/Protocol Elements of IIOT for manufacturing
  • State of the present art and review of existing technology in the market place
  • PLC – architecture
  • Cloud integration of PLC data
  • Visualization of PLC data
  • Digital Twin
  • PLC protocols ( Modbus, Field bus, Profibus) and its integration with Cloud
  • Concept of Industrial Gatway
  • Session 6: Introduction to Mobile App Platform for IoT
  • Protocol stack of Mobile app for IoT
  • Mobile to server integration –what are the factors to look out
  • What are the intelligent layer that can be introduced at Mobile app level ?
  • iBeacon in IoS
  • Window Azure
  • Amazon AWS-IoT
  • Web Interfaces for Mobile Apps ( REST/WebSockets)
  • IoT Application layer protocols (MQTT/CoAP)
  • Security for IoT middleware- Keys, Token and random password generation for authentication of the gateway devices.
  • Demo : Mobile app for tracking IoT enabled trash cans
    Session 7: Machine Learning for Intelligent IIoT
  • Introduction to Machine learning
  • Signal processing of Vibration and Current signals
  • Application of ML in predictive maintenance
  • Learning classification techniques
  • Bayesian Prediction-preparing training file
  • Support Vector Machine
  • Predicting failure of the machines -vibrational analysis
  • Current signature analysis
  • Time series data and prediction
  • Demo : Vibration analysis of a Motor
    Session 8: Analytic Engine for IIoT
  • Insight analytic – example from Energy analytics
  • Visualization analytic-example from Machine health
  • Structured predictive analytic
  • Unstructured predictive analytic
  • Recommendation Engine
  • Pattern detection
  • Root cause discovery for electrical failures in factory
  • Root cause of machine failure
  • Logistic supply chain analysis for manufacturing
  • Demo : Visualization of IoT data for Machine health
    Session 9: Security in IoT Implementation
  • Why security is absolutely essential for IoT
  • Mechanism of security breach in IOT layer
  • Privacy enhancing technologies
  • Encryption and cryptography implementation for IoT data
  • Security standard for available platform
  • European legislation for security in IoT platform
  • Secure booting
  • Device authentication
  • Firewalling and IPS
  • Updates and patches
  • Session 10: IAAS/PAAS Azure/AWS/Google/Siemens platform for IoT
  • Iaas : Infrastructure as a service-evolving models
  • Mechanism of security breach in IOT layer for Iaas
  • Middleware for Iaas business implementation in healthcare, homeautomation and farming
  • Iaas case study for vehicular information for Auto-insurance and Agriculture
  • Paas: Platform as a service in IoT. Case studies of some of the IoT middleware
  • Saas : Software/System as service for IoT business models
  • European and American (NIST) legislation for security in IoT platform
  • Firewalling and IPS
  • Updates and patches via web-OTA mechanism
  • Microsoft IoT Central as an example of PaaS platform
  • Google IoT, AWS IoT PaaS platform
  • Demo: Azure IoT central system for IIoT
    Session 11: A few Common IIoT Systems for manufacturing
  • Energy Optimization in Manufacturing
  • Vibration analysis to build predictive maintenance
  • Power Quality analysis to build Prevetative maintenance
  • Recommendation system for logistic supply chain
  • IIoT system for Industrial Safety
  • IIoT system asset identification
  • IIoT system for Utilities in Manufaturing plants ( Chiller, Aircompressor, HVAC)
  • Demo: Industrial Use case for IoT
    Session 12: More detailed case studies in IIoT
  • Energy Optimization in Manufacturing
  • Upgrading bare analog sensors to IoT system
  • Predictive maintenance of an induction motor
  • Predictive maintenance of a Pump
  • Structural Health Monitoring ( SHM) / Bridge monitoring using sensors
  • Industrial safety and IoT
  • Public safety and IoT
  • Smart City examples
  • Waste water management using IoT
  • Demo: Industrial Use Cases for IoT


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