Week 12 | Session 2: Industry 4.0 Pillars 1–3: IoT, Cloud Computing & H/V System Integration
Course: Supply Chain Digitization — Module 4: Digital Infrastructure
Session Agenda
Section titled “Session Agenda”Pillar 1 — IoT (Internet of Things)
Section titled “Pillar 1 — IoT (Internet of Things)”1. What is IoT?
Section titled “1. What is IoT?”
Definition: a network of interconnected physical devices, vehicles, buildings and other objects embedded with sensors, actuators and connectivity.
- Role: collects data from the physical world and exchanges it — enabling digital representation of real-world events.
- Bridges the gap between the physical world and the digital world.
- Supports real-time insights and automation without human intervention.
RFID & GPS — Key IoT-Adjacent Technologies:
- RFID: tracks and manages inventory and assets using embedded chips and readers.
- GPS: determines location of shipments and vehicles in real time.
- Both serve the IoT data-collection purpose — integral to IoT ecosystems.
2. How IoT Works — 4-Step Sequence
Section titled “2. How IoT Works — 4-Step Sequence”- Collect: Devices, sensors (temperature, pressure, vibration), RFID and GPS capture data from the physical world. Select technology based on what you need to measure.
- Communicate: Captured data is sent to a central system over the internet. Protocols must be followed for secure transmission. Channels: Wi-Fi, Bluetooth, LPWAN, or direct internet connection.
- Analyze: Data is processed and analyzed — in cloud or at the edge. Visualization, outlier detection, anomaly identification. Critical conditions trigger alerts.
- Act: Based on analysis, automated or manual actions are initiated. Forms: alerts, emails, notifications, automated control signals. Closes the loop: physical event → digital capture → decision → physical response.
3. Three Types of IoT
Section titled “3. Three Types of IoT”| Type | Usage, Data Volume & Examples |
|---|---|
| IIoT — Industrial IoT | Used in industrial and manufacturing environments — MES (Manufacturing Execution Systems). Enables machine-to-machine (M2M) communication. Generates large volumes of high-frequency process data. Example: predictive maintenance sensors on factory equipment. |
| CIoT — Consumer IoT | Used by individuals in everyday life. Wearables, smart home appliances, personal monitoring devices. Small data volume — connects to mobile apps. Example: fitness tracker sending health data to a phone app. |
| CmIoT — Commercial IoT | Used in commercial premises — offices, supermarkets, hotels, hospitals. Applications: environmental monitoring, lighting control, asset tracking. Data collected to centralized cloud → analytics. |
4. IoT Applications in Supply Chain
Section titled “4. IoT Applications in Supply Chain”| SC Application | How IoT Helps |
|---|---|
| Real-time inventory & resource tracking | Visibility of inventory location and quantity at all SC nodes |
| Predictive maintenance | Sensors analyze equipment condition → anticipate failure → minimize downtime before breakdown |
| Inventory optimization | Tracking data feeds inventory decisions → reduces excess inventory and stockouts |
| Improved decision-making | Data captured and analyzed → better planning insights → smarter SC decisions |
5. IoT — Implementation Challenges
Section titled “5. IoT — Implementation Challenges”| Challenge | Explanation |
|---|---|
| Investment Cost | Heavy upfront investment required — infrastructure, devices, connectivity |
| Security & Privacy | Critical data captured at multiple points must be secured and kept private |
| Scalability | IoT system must handle growing data volume as more SC partners join |
| Integration | Compatibility between new IoT systems and existing legacy systems is a major technical challenge |
| Human Behaviour | Management resistance and change aversion are common barriers |
6. Emerging Trends in IoT for Supply Chain
Section titled “6. Emerging Trends in IoT for Supply Chain”- Edge Computing: process data closer to the source (at the device/sensor level) → faster decisions, lower latency.
- Blockchain Integration: ensures transparency and traceability of data collected via IoT — prevents record tampering.
- AI/ML Integration: apply predictive analytics on IoT-collected data → forecast failures, optimize routes, adjust inventory.
- Environmental Impact Reduction: IoT-enabled monitoring supports sustainability goals — track emissions, energy use, waste.
Pillar 2 — Cloud Computing
Section titled “Pillar 2 — Cloud Computing”7. What is Cloud Computing?
Section titled “7. What is Cloud Computing?”Definition: delivery of computing services — servers, storage, software, databases, networking — over the internet.
- Economy of scale for the provider → no upfront capex for the user.
- Enables: data storage, processing, collaboration, and running AI/ML — all at scale, accessible from anywhere.
- Classified in two independent ways: by deployment model AND by service model.
8. Cloud Deployment Types
Section titled “8. Cloud Deployment Types”| Type | Who Uses It | Security | Examples |
|---|---|---|---|
| Public | Shared infrastructure; accessible to all; low cost | Low | Google Apps, AWS |
| Private | Dedicated to single org; org owns and manages infra | Highest | HPE, Dell, IBM |
| Community | Shared by multiple orgs with similar needs (e.g., govt agencies, universities) | Moderate | Cisco Community Cloud |
| Hybrid | Combination of public + private (public for web, private for customer DB) | Mixed | Azure, IBM |
Selection rule: choose based on cost vs security trade-off and whether data is sensitive. Hybrid is most flexible.
9. Cloud Service Models (IaaS / PaaS / SaaS)
Section titled “9. Cloud Service Models (IaaS / PaaS / SaaS)”| Model | What is Provided | User Control | Example |
|---|---|---|---|
| IaaS — Infrastructure as a Service | Access to hardware: storage, network, OS, virtual servers. User manages above the infrastructure layer. | Highest flexibility + control | Amazon Web Services (AWS) |
| PaaS — Platform as a Service | Platform for app development: OS, database, programming environment, web server. User manages apps + data. | High — manages resources clearly | Microsoft Azure |
| SaaS — Software as a Service | Access to software applications on pay-per-use basis. Most convenient — user just uses the application. | Lowest — just access the app | Gmail, Google Docs, Office 365 |
Pillar 3 — Horizontal & Vertical System Integration
Section titled “Pillar 3 — Horizontal & Vertical System Integration”10. H/V Integration
Section titled “10. H/V Integration”This is a strategy rather than a standalone technology — it defines HOW IoT, cloud, and analytics are deployed.
| Type | Definition, Purpose & Example |
|---|---|
| Horizontal Integration | Connects activities operating at the same level — within or across organizations. Purpose: coordination and synchronization of similar functions. Example: integrating production planning + scheduling + MES across multiple factories within the same company. |
| Vertical Integration | Connects players in sequence — upstream ↔ downstream across the SC. Purpose: end-to-end visibility, control, and optimization across the chain. Example: integrating PLM → MES → ERP → SC. |
Decision: Which Type to Use?
Section titled “Decision: Which Type to Use?”| Problem | Solution |
|---|---|
| Same-level coordination problem (e.g., factories not synchronized) | Horizontal integration |
| End-to-end visibility problem (e.g., no traceability from design to delivery) | Vertical integration |
| Large organizations often need both simultaneously | Both H + V |
Session Summary
Section titled “Session Summary”- IoT: network of connected devices that collect + communicate + analyze + act on data. Bridges physical and digital worlds without human intervention.
- IoT 4 steps: Collect (sensors, RFID, GPS) → Communicate (Wi-Fi, Bluetooth, LPWAN) → Analyze (cloud/edge, outlier detection) → Act (alerts, auto-control).
- 3 IoT types: IIoT (industrial, high volume, M2M) | CIoT (consumer, low volume, personal) | CmIoT (commercial, offices, hospitals).
- Cloud deployment: Public / Private / Community / Hybrid — chosen based on cost vs security.
- Cloud service models: IaaS (infrastructure, most control) | PaaS (platform, app dev) | SaaS (software, most convenient).
- H/V Integration: Horizontal = same-level coordination. Vertical = sequential upstream-downstream linkage.