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Industrial Internet of Things (IIoT) and the Future of Manufacturing, Forecast to 2021
Industrial Internet of Things (IIoT) and the Future of Manufacturing, Forecast to 2021
IIoT Architecture Standardization to Create a $90 Billion Opportunity by 2021
26-Dec-2017
North America
$4,950.00
Special Price $3,712.50 save 25 %
Description
Industrial Internet of Things (IIoT) can be leveraged to transform the production aspect and future potential of the automotive manufacturing business. While evolving technologies play a key role in fostering the automotive business, it becomes crucial for automotive manufacturers to stay connected in order to amalgamate different technologies like machine learning, Big Data, sensor data, machine-to-machine communication, and automation. This will make the best use of IIoT, which would in turn result in gaining a competitive edge and open new revenue streams for the auto makers in the market.
Primary factors, like boosting operational efficiency, increasing productivity, and reducing the complexity of process in the industry plays a vital role in the adoption of IIoT by auto makers. Industrial Internet strives to create a connected enterprise by combining the information and operation department of the production facility. Cognitive systems and real-time analysis can interpret data from systems and components to valuable insights, with which automotive manufacturers can use it to improve the reliability of their output. This not only ensures quality but also improves overall efficiency while supporting manufacturers in introducing new value-added services to customers.
Automotive manufacturers are implementing IoT concepts to create automated and seamless transactions in their production process by deploying sensors, initiate communication with multiple devices, and implant advanced analytics solutions to derive actionable insights. Auto makers need to take multi pronged approach to create relevant business model that embraces IoT-enabled capabilities. Apart from this, maintaining and updating complex systems from in-house/remote locations, possible cyber attacks over the connected networks, adhering to standards of local networks for bandwidth and latency, maintaining process integrity and IP protection, and making immediate investments in evolving technologies are possible challenges to IIoT adoption in a manufacturing facility. However, continuous monitoring of transformation needs would help the auto maker develop a proactive approach to overcoming these challenges.
Key Issues Addressed
- What are the various IIoT initiatives and how are the functional requirements best understood to implement IIoT? What are the prevailing market trends for IIoT across vertical and horizontal market?
- What is the plausible future agenda of IIoT bodies? Who are the key participants and what are their IIoT platforms? What does their analysis reflect about their suitability for product manufacturing?
- What is the system architecture comprised of and what are these different layers? How can end-to-end industrial architecture for IIoT applications be conceptualized?
- What does the road map for cloud adoption in manufacturing look like? What are the stages of industrial cloud adoption? How is the IIoT market penetration set to grow during 2016 to 2021?
- Security concerns are the number one barriers to cloud adoption. How is the industry trying to overcome this? Which regions are expected to dominate IIoT adoption?
RESEARCH: INFOGRAPHIC
This infographic presents a brief overview of the research, and highlights the key topics discussed in it.Click image to view it in full size
Table of Contents
Executive Summary—Key Takeaways
Executive Summary—Emerging Opportunities Across IIoT Architecture
Executive Summary—Technology Metamorphosis Adoption Cycle
Executive Summary—Technology Perspective
Executive Summary—Regional Perspective
Executive Summary—Industrial Cybersecurity Market Outlook
Executive Summary—Industrial Cybersecurity Customer Perspective
Research Scope
Research Aims and Objectives
Key Questions this Study will Answer
Research Background
Research Methodology
Industrial Internet of Things—The 4 Functional Facets
Market Definitions—IIoT System Architecture
Market Definitions—Different Layers
Market Definitions
Segmentation
Platform Industry 4.0
Impelling Objectives of IIoT Bodies
Global Standards Body—Overview of Alliances Landscape
Industrial Internet Consortium (IIC)
Regional Snapshot—Made in China 2025
Future Agenda for IIoT Committees
IIoT—Four Core Components
IIoT—Computing Requirements
Exploring Tools and Skills to Navigate IIoT
Analyzing the Industry Needs
Examining Challenges in IIoT Adoption
Conceptualizing IIoT Computing Requirements
IIoT Design Principles
IIoT Design Approach
IIoT in Enterprise System Hierarchy
Exploring IIoT’s End-to-End Industrial Architecture
Plant of the Future—Industry 4.0 Ecosystem
Sensing Layer—Key Sensor Type Classification
Sensors Market—Revenue Analysis and Key Trends
Emerging Sensors—The New Age IIoT Sensors
Device Layer—Overview of Communication Hardware
Device Layer—Synopsis of IIoT Gateway Unit Shipments
Gateway Matrix—Common Types and Key Features
Gateway Matrix—Common Types and Key Features (continued)
Device Layer—End-user Expectations
Network Layer—Industrial Spectrum Preferences
IIoT Industrial Spectrum—Data Consumption Analysis
Wireless Network—The Diverse Operating Frequencies
LPWAN—A New Reality in Connected Manufacturing
5G Technology—Set to Revolutionize IIoT by 2021
IIoT Software Segmentation—Prevailing Market
Discerning the Distribution Channel
Regional and Industry Vertical—Software Segment Overview
Growth Curve Analysis—Software Segment Overview
Roadmap for Cloud Adoption in Manufacturing
Analyzing Cloud Computing Models in Manufacturing
Cloud-based Models—Acute Focus on Data Sensitivity
On-premise vs. Cloud Based—Choosing the Right Deployment Model
Manufacturing Cloud System in Factory Automation
Value Proposition of Cloud in IoT
Fading Relevance of ‘One Size Fits All’ in Industrial Cloud
Industry’s Shift in Focus to Data Driven Services
Security Concerns—Cloud Adoption
Insularity on Industrial Cloud
Skills Gaps From Evolving Manufacturing Technologies
Future Course of Industrial Cloud
Overview of Manufacturing vs. Other Sectors
Manufacturing Analytics—A Gold Mine of Opportunities
Risk Reward Matrices—Production Line and Plant Level
Maintenance Analytics—Increase Equipment Uptime
Era of Advanced Machine Learning—A Proactive Approach
Big Data in Manufacturing
Regional Outlook—Key Dynamics Across Global Hotspots
Vertical Market Analysis—Discrete vs. Process
New Emerging Markets—Manufacturing Pollution Control
Size of the Pie—Summary of Key Market Opportunities
Introduction—IIoT and Industrial Cyber Security (ICS)
Key Industrial Network Implications
Smart Devices and Cybersecurity
Endpoint Security Implications
Security Challenges in the Factory of the Future
Case Example—Automotive Industry
Case Example—Power Industry
Security Opportunities—Factories of the Future
IIoT Ecosystem
IIoT Ecosystem—Key Vendors
Category 1—Industrial Big Data Analytics
Category 2—IoT Logistics
Category 3—IoT Connected Cars
IIoT Ecosystem Thrives on Partnerships and Technologies
IIoT Ecosystem to Customize Flexible and Reliable Production Processes
Digitization in Manufacturing—Key Elements of Automotive I4.0* Approach
Benchmarking Criteria
Industry 4.0 Platform Benchmarking
Bosch Software Innovations (SI)—Key Highlights and Partnerships
Bosch SI-Leading User and Solution Provider
Bosch Industry 4.0—Readiness and Software Solutions
General Electric (GE)—Key Highlights and Opportunities
GE—IIoT Platform
GE Predix Architecture Overview
GE Predix Machine, Edge Connectivity, and Predix Cloud Overview
SAP Software Solutions Accelerating Digital Innovation
SAP Industry 4.0 Solution Packages
SAP Automotive Solutions—Key Partnerships and Opportunities
IBM Products and Watson IoT Platform—Overview
IBM Industry 4.0 and Connected Manufacturing Suite—Key Pillars
Cisco Automotive Solutions—Key Partnerships and Opportunities
Cisco Solutions
SAP Industry 4.0 Solution Packages
Cisco DNA and Cisco Connected Factory for Industry 4.0
BMW Approach for Digitalization of Production Facilities
BMW Smart Factory Technologies—Implementation
BMW Smart Factory Technologies—Business Impact
GM IIoT Initiatives—Pilot Project to Reduce Factory Downtime
Smart Factory
IIoT in the Era of Digital Engineering
Traditional Supply Chain Framework in Manufacturing
Supply Chain Participants vs. Core Competency
IIoT-enabled ERP Systems
IIoT-enabled ERP Systems (continued)
Predictive Maintenance Structural Outline
Operational Predictive Maintenance Forecast
Predictive Maintenance—Cost Saving Analysis Assumptions
Cost Savings—Product Revenue vs. Maintenance Frequency
IIoT Shifts Power to Automation Vendors
Franchisee Model of Service Supply Chain
Toyota Operations Technology (OT) for Efficiency
GE Analogy—Embracing Brilliant Factories & Digital Twin
Bosch Analogy—A Smart Watch Solution
Stanley Black & Decker—Virtual Warehouse and Connected Factory
Jeep Transforms its US Factory Realizing IIoT
IIoT Growth Opportunities
Strategic Imperatives
The 3 Big Predictions
Legal Disclaimer
The Frost & Sullivan Story
Value Proposition—Future of Your Company & Career
Global Perspective
Industry Convergence
360º Research Perspective
Implementation Excellence
Our Blue Ocean Strategy
Related Research
| No Index | No |
|---|---|
| Podcast | No |
| Author | Jagadeesh Chandran |
| Industries | Automotive |
| WIP Number | K172-01-00-00-00 |
| Is Prebook | No |
| GPS Codes | 9800-A6,9813-A6,9AA5-C1,9694,9968-A6,9AF6-A6,9B07-C1 |