Friday, March 5, 2021
  • Setup menu at Appearance » Menus and assign menu to Top Bar Navigation
Advertisement
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
No Result
View All Result
Home Data Science

The Role of Artificial Intelligence in Manufacturing: 15 High Impact AI Use Cases

March 1, 2019
in Data Science
585
SHARES
3.3k
VIEWS
Share on FacebookShare on Twitter

Credit: Data Science Central

According to the World Economic Forum, the global manufacturing sector could be one of the sectors most influenced by the latest technological trends like AI, machine learning and IoT – collectively termed Industry 4.0 – with great potential for disruption and transformation if these technologies are employed intelligently.

You might also like

A Plethora of Machine Learning Articles: Part 2

The Effect IoT Has Had on Software Testing

Why Cloud Data Discovery Matters for Your Business

While AI has proven to be one of the most broadly disruptive technologies of the digital revolution, it best maximizes its potential when deployed in conjunction with two augmentative domains – robotics and Internet of Everything (IoE).

Robotics has become an integral part of the manufacturing sector over the past two decades and the finesse, complexity, and sophistication of robotic tasks have been significantly enhanced via AI. Tasks which were previously relegated to the human domain due to complexity and labor constraints are now routinely completed by robots.

As for IOE, the ease of deployment and advanced capabilities of sensors allow for the universalization of AI in the manufacturing sector. Because sensors collect data continuously and can be placed nearly anywhere, manufacturers can expect to increase productivity, connectivity, and scalability as IOE becomes more engrained in the sector.

The question for manufacturers remains, wherein the operation is AI most applicable? We will outline a list of 15 use cases across seven segments.

Predictive and Preventive Maintenance

A top area in maintenance is the area of data-driven maintenance enabling the transformation of maintenance in manufacturing from reactive to preventive maintenance powered by AI enabled predictive capability. A whopping $647 billion is lost globally each year in industrial asset downtime, per the International Society of Automation (Source: https://www.isa.org/standards-publications/isa-publications/intech-… ). Role of sensors and IOT enabled devices to enable real-time information feed to AI engines is key. IOT when applied as sensors in an industrial setting often termed as IIOT Industrial IOT. This works in conjunction with AI to achieve the desired results.

AI has the potential to drive the regime towards enhanced uptime reducing downtime via different possibilities:

Use Case 1:  Real-Time Alert of Wear, Tear, Fault, or Breakdown – Warning signals of potential breakdown by AI, it could even look ahead for fatigue

Use Case 2: Lifetime Prediction: Using AI to accurately predict Time to Live for Assets like Machinery improving overall life of machinery and assets

Use Case 3: AI to enable more informed asset maintenance schedule triggering a focused repair and MRO schedule optimizing overall effort, cost, and quality across assets.

Enhancing Robots Effectiveness

While currently, robots are quite mainstream in automating manufacturing shop floors presence of AI can enhance the role of robots by better task handling

Use Case 4: Enhanced effectiveness of robots in form of powerful software to enable robots to take on complex tasks. Not just complexity but also the versatility of tasks enhanced by AI

Use Case 5: Role of AI in better human-robot interaction to enable more effective utilization of robots is key. Cobots are emerging as potential enablers in this area.

Manufacturing supply chain

The overall manufacturing industry is heavily dependent upon the accompanying supply chain effectiveness for overall productivity and efficiency. AI combined with IOT has tremendous potential

Some identifiable use cases are as below:

Use Case 6:  Real-time tracking of supply vehicles helps in better utilization of logistics fleet thereby optimizing overall production schedule

Use case 7: Better data-driven AI-based approach to analyzing inventory and thereby using it to lower inventory costs can be a great cost saver for manufacturers.

Use case 8: Shipping and Delivery Lead Time can not only be accurately predicted, but it is also optimized via application of AI algorithms

Design Disruption

AI has an element of technology which has enabled take on roles of creative tasks like art music etc. A related use case in the context of manufacturing is appearing more and more real.

Use Case 9. Use of AI-based generative design is being used by large design houses like auto manufacturers. airplane manufacturers etc enabling creative machine or part or asset designs not limited by human designers.

Quality Management and Improvement

Several data-driven initiatives are now becoming mainstream in manufacturing processes, most prominent of them being in the area of quality management and improvement.

Use Case 10. Quality process improvement. AI can enable understand limitations, shortcomings, or deficiencies of current as manufacturing quality processes and using AI applied on quality data several improvement opportunities can be harnessed.

Use Case 11: Using complex AI like computer vision to explore defects in produced items can be a great way to ensure product quality.

Digital Twin

A recent initiative spanning several sectors of manufacturing is the idea of digital twin where there is an equivalent mapped equivalent of a process in reality.  AI role is such a digital twin areas below.

Use Case 12: Idea of such a digital twin is to understand and simulate how the process flows occur and identify what if scenarios via AI. AI thus enables the realization of potential implications of the process

Use Case 13: Exception Management: In conventional workflows, exceptions are usually routed to humans to take care of the same. In an AI wired process such processes could be automated and straight through actions could be taken by programs rather than humans

Use Case 14: Testing of design and manufacturing feasibility of items can be carried out intelligent simulations.

Mass Customization and N=1

In the world of data driven product management, a key application of AI will be in terms of understanding customers closely.

Use Case 15: Understanding customers closely and designing, manufacturing and testing products with a high level of customization. This leads to change of models of design and manufacturing also to include flexible ways of catering to all diverse products. Example of BTO models falls in this.

So we can safely now say AI is here to disrupt the manufacturing industry in conjunction with Robotics and IOT like technologies ushering in the broadly accepted term of Industry 4.0


Credit: Data Science Central By: Mahesh Kumar CV

Previous Post

Looking Beyond the Hype -- Security Today

Next Post

19-year-old makes millions from ethical hacking

Related Posts

A Plethora of Machine Learning Articles: Part 2
Data Science

A Plethora of Machine Learning Articles: Part 2

March 4, 2021
The Effect IoT Has Had on Software Testing
Data Science

The Effect IoT Has Had on Software Testing

March 3, 2021
Why Cloud Data Discovery Matters for Your Business
Data Science

Why Cloud Data Discovery Matters for Your Business

March 2, 2021
DSC Weekly Digest 01 March 2021
Data Science

DSC Weekly Digest 01 March 2021

March 2, 2021
Companies in the Global Data Science Platforms Resorting to Product Innovation to Stay Ahead in the Game
Data Science

Companies in the Global Data Science Platforms Resorting to Product Innovation to Stay Ahead in the Game

March 2, 2021
Next Post
19-year-old makes millions from ethical hacking

19-year-old makes millions from ethical hacking

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Recommended

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

January 6, 2019
Microsoft, Google Use Artificial Intelligence to Fight Hackers

Microsoft, Google Use Artificial Intelligence to Fight Hackers

January 6, 2019

Categories

  • Artificial Intelligence
  • Big Data
  • Blockchain
  • Crypto News
  • Data Science
  • Digital Marketing
  • Internet Privacy
  • Internet Security
  • Learn to Code
  • Machine Learning
  • Marketing Technology
  • Neural Networks
  • Technology Companies

Don't miss it

Comprehensive Report on Machine Learning Market 2021 | Size, Growth, Demand, Opportunities & Forecast To 2027
Machine Learning

Comprehensive Report on Machine Learning Market 2021 | Size, Growth, Demand, Opportunities & Forecast To 2027

March 5, 2021
GAO report finds DOD’s weapons programs lack clear cybersecurity guidelines
Internet Security

GAO report finds DOD’s weapons programs lack clear cybersecurity guidelines

March 5, 2021
Convergence of AI, 5G and Augmented Reality Poses New Security Risks 
Artificial Intelligence

Convergence of AI, 5G and Augmented Reality Poses New Security Risks 

March 5, 2021
2021 Gartner Magic Quadrant for Data Science and Machine Learning Platforms
Machine Learning

2021 Gartner Magic Quadrant for Data Science and Machine Learning Platforms

March 5, 2021
With its acquisition of Auth0, Okta goes all in on CIAM
Internet Security

With its acquisition of Auth0, Okta goes all in on CIAM

March 5, 2021
Survey Finds Many Companies Do Little or No Management of Cloud Spending  
Artificial Intelligence

Survey Finds Many Companies Do Little or No Management of Cloud Spending  

March 5, 2021
NikolaNews

NikolaNews.com is an online News Portal which aims to share news about blockchain, AI, Big Data, and Data Privacy and more!

What’s New Here?

  • Comprehensive Report on Machine Learning Market 2021 | Size, Growth, Demand, Opportunities & Forecast To 2027 March 5, 2021
  • GAO report finds DOD’s weapons programs lack clear cybersecurity guidelines March 5, 2021
  • Convergence of AI, 5G and Augmented Reality Poses New Security Risks  March 5, 2021
  • 2021 Gartner Magic Quadrant for Data Science and Machine Learning Platforms March 5, 2021

Subscribe to get more!

© 2019 NikolaNews.com - Global Tech Updates

No Result
View All Result
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News

© 2019 NikolaNews.com - Global Tech Updates