The Dawn of Artificial Intelligence—Foreseeing Manufacturing in the Cognitive Era

The Dawn of Artificial Intelligence—Foreseeing Manufacturing in the Cognitive Era

Investigating Cognitive Technologies that will Reshape Manufacturing Value Chain in the Future

RELEASE DATE
12-Apr-2017
REGION
Global
Research Code: MCCC-01-00-00-00
SKU: IA01377-GL-MR_19892

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Description

The impact of information technology (IT) on the manufacturing industry has been tremendous in recent times. With an increasing number of machines being connected to the Internet, data are being generated in huge volumes. Advancements in real-time data processing and predictive analytics further help in discovering newer ways of utilising the data to generate insights for effective decision making. Today, The Internet of Things (IoT) and data analytics are the two main technologies that are driving the manufacturing space. Currently, most machines are embedded with low-level logical processors that demand a considerable amount of human intervention in making logical and reasonable decisions. Cognitive manufacturing is an evolutionary step in which machines would be able to detect changes in the manufacturing process and know-how to respond in real time to the constantly changing manufacturing scenario with minimal human intervention. The objective of this research service is to give a detailed account of cognitive computing and its application in manufacturing and to understand the competitive landscape. This research service will also look into how cognitive technologies would be the next step in the evolution of smart manufacturing and how this would benefit companies by helping them make smarter decisions on the factory floor. The study also throws light on what the market participants are currently doing in this space and provides proven use cases pertaining to how the market is likely to transform the manufacturing arena in the coming years, which could be helpful to the current set of participants in the market that are looking at understanding what their competitors are doing in the space. It can also serve as a useful point of reference for all other market participants that are not aware of the immense benefits of cognitive computing or are in the verge of making a move in the market.

Key Questions Answered in this Study:
1.     What are the evolving technologies that summarize the complex cognitive ecosystem in manufacturing?
2.     What is the value addition of cognitive technologies in manufacturing?
3.     What are the key trends that will shape the evolution of a cognitive factory?
4.     What are cognitive solution providers and adopters doing to enhance manufacturing?
5.     What are specific use cases illustrating the application of cognitive technologies in manufacturing?
6.     Where are the opportunities in this market and what are the strategies that manufacturers can adopt to accelerate growth?
7.     How will the adoption of cognitive affect manufacturing, human resources and economies?

Table of Contents

Key Findings

IIoT—Emerging Themes in the Industrial Environment

IIoT—Key Attributes of a Smart Factory

Frost & Sullivan’s Value Proposition in IIoT

Defining Cognitive Technologies in Manufacturing

Cognitive Technologies in Manufacturing

Evolution of Smart Industrial Machines

Cognitive Intelligence—Current possibilities and Gaps

Potential Applications of Cognitive in Manufacturing

Key Benefits and Future Potential of Cognitive Intelligence in Manufacturing

Early Entrants in the Cognitive Computing—A Market Snapshot

Industry Collaboration on AI

Use Case—IBM Super Charges Operations for Schaeffler

Use Case—Google Uses AI to Optimise Energy Savings

Use Case—FANUC to Build Futuristic Factory with NVIDIA’s AI Platform

Competitive Strategy—GE Taking Acquisition Route to Build AI Capabilities

Competitive Strategy—Microsoft and Jabil Usher in Factory Floor Cognizance

Use Case—Quality Control through Vision and Pattern Recognition

Value Chain Eco system for Cognitive Manufacturing

Trend1—Surge in Adoption of Autonomous Robots in Manufacturing

Trend2—AI Feeds on Data to Generate Cognitive Insights

Trend3—Machine Learning to Drive the Evolving Manufacturing Landscape

Trend4—Economic Growth Up, Human Employment Down with Advancing AI in Manufacturing

Challenge1—Impact on Factory Jobs of with AI in Shop Floors

Challenge2—Dealing with Inconsistent Data Format

Challenge3—Volatile Cognitive Landscape

Catalysing Change in the Way Manufacturing Works

Cognitive Manufacturing—SWOT Analysis

Market Strategies for AI Suppliers (based on SWOT)

Cognitive Manufacturing—Market Penetration Analysis

Key Findings from Market Penetration Analysis

Growth Opportunity1—Partnerships and Collaborations

Growth Opportunity2—Data-driven intelligence

Strategic Imperatives for Success and Growth

Future Trajectory of Cognitive in Manufacturing

Cognitive Factories—The Road Ahead

Legal Disclaimer

Market Engineering Methodology

List of Figures
  • 1. Cognitive Manufacturing: Market Penetration Analysis, Global, 2017
  • 2. Cognitive Manufacturing : Evolution of Cognitive Technologies, Global, 2017
List of Charts
  • 1. Cognitive Manufacturing: Defining Cognitive Technologies, Global, 2017
  • 2. Market Opportunity Matrix—Cognitive Technologies in Manufacturing, 2017–2021
The impact of information technology (IT) on the manufacturing industry has been tremendous in recent times. With an increasing number of machines being connected to the Internet, data are being generated in huge volumes. Advancements in real-time data processing and predictive analytics further help in discovering newer ways of utilising the data to generate insights for effective decision making. Today, The Internet of Things (IoT) and data analytics are the two main technologies that are driving the manufacturing space. Currently, most machines are embedded with low-level logical processors that demand a considerable amount of human intervention in making logical and reasonable decisions. Cognitive manufacturing is an evolutionary step in which machines would be able to detect changes in the manufacturing process and know-how to respond in real time to the constantly changing manufacturing scenario with minimal human intervention. The objective of this research service is to give a detailed account of cognitive computing and its application in manufacturing and to understand the competitive landscape. This research service will also look into how cognitive technologies would be the next step in the evolution of smart manufacturing and how this would benefit companies by helping them make smarter decisions on the factory floor. The study also throws light on what the market participants are currently doing in this space and provides proven use cases pertaining to how the market is likely to transform the manufacturing arena in the coming years, which could be helpful to the current set of participants in the market that are looking at understanding what their competitors are doing in the space. It can also serve as a useful point of reference for all other market participants that are not aware of the immense benefits of cognitive computing or are in the verge of making a move in the market. Key Questions Answered in this Study: 1. What are the evolving technol
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Table of Contents | Executive Summary~ || Key Findings~ | Industrial Internet of Things (IIoT)—A Research Perspective~ || IIoT—Emerging Themes in the Industrial Environment~ || IIoT—Key Attributes of a Smart Factory~ || Frost & Sullivan’s Value Proposition in IIoT~ | Rise of Cognitive in Manufacturing~ || Defining Cognitive Technologies in Manufacturing~ || Cognitive Technologies in Manufacturing~ || Evolution of Smart Industrial Machines~ || Cognitive Intelligence—Current possibilities and Gaps~ || Potential Applications of Cognitive in Manufacturing~ || Key Benefits and Future Potential of Cognitive Intelligence in Manufacturing~ | Industry Landscape—Powerful Examples of Cognitive Intelligence in Manufacturing~ || Early Entrants in the Cognitive Computing—A Market Snapshot~ || Industry Collaboration on AI~ || Use Case—IBM Super Charges Operations for Schaeffler~ || Use Case—Google Uses AI to Optimise Energy Savings~ || Use Case—FANUC to Build Futuristic Factory with NVIDIA’s AI Platform~ || Competitive Strategy—GE Taking Acquisition Route to Build AI Capabilities~ || Competitive Strategy—Microsoft and Jabil Usher in Factory Floor Cognizance~ || Use Case—Quality Control through Vision and Pattern Recognition~ || Value Chain Eco system for Cognitive Manufacturing~ | Key Trends in Cognitive Manufacturing~ || Trend1—Surge in Adoption of Autonomous Robots in Manufacturing~ || Trend2—AI Feeds on Data to Generate Cognitive Insights~ || Trend3—Machine Learning to Drive the Evolving Manufacturing Landscape~ || Trend4—Economic Growth Up, Human Employment Down with Advancing AI in Manufacturing~ | Industry Challenges~ || Challenge1—Impact on Factory Jobs of with AI in Shop Floors~ || Challenge2—Dealing with Inconsistent Data Format~ || Challenge3—Volatile Cognitive Landscape~ || Catalysing Change in the Way Manufacturing Works~ | Growth Opportunities and Forecasts~ || Cognitive Manufacturing—SWOT Analysis~ || Market Strategies for AI Suppliers (based on SWOT)~ || Cognitive Manufacturing—Market Penetration Analysis~ || Key Findings from Market Penetration Analysis~ || Growth Opportunity1—Partnerships and Collaborations~ || Growth Opportunity2—Data-driven intelligence~ || Strategic Imperatives for Success and Growth~ | The Last Word~ || Future Trajectory of Cognitive in Manufacturing~ || Cognitive Factories—The Road Ahead~ || Legal Disclaimer~ | Appendix~ || Market Engineering Methodology~
List of Charts and Figures 1. Cognitive Manufacturing: Market Penetration Analysis, Global, 2017~ 2. Cognitive Manufacturing : Evolution of Cognitive Technologies, Global, 2017~| 1. Cognitive Manufacturing: Defining Cognitive Technologies, Global, 2017~ 2. Market Opportunity Matrix—Cognitive Technologies in Manufacturing, 2017–2021~
Author Nandini Natarajan
Industries Industrial Automation
WIP Number MCCC-01-00-00-00
Is Prebook No