LOUISVILLE, KENTUCKY
ATLANTA, GEORGIA
CHICAGO, ILLINOIS
CINCINNATI, OHIO
DENVER, COLORADO
MADISON, WISCONSIN
RARITAN, NEW JERSEY
TORONTO, ONTARIO
NOIDA, INDIA
HYDERABAD, INDIA

V-Soft's Corporate Headquarters

101 Bullitt Lane, Suite #205
Louisville, KY 40222

502.425.8425
TOLL FREE: 844.425.8425
FAX: 502.412.5869

Denver, Colorado

6400 South Fiddlers Green Circle Suite #1150
Greenwood Village, CO 80111

TOLL FREE: 844.425.8425

Chicago, Illinois

208 N. Green Street, #302, Chicago, IL 60607

TOLL FREE: 844.425.8425

Madison, Wisconsin

2810 Crossroads Drive, Ste. 4000
Madison, WI 53718

TOLL FREE: 844.425.8425

Atlanta, Georgia

1255 Peachtree Parkway Suite #4201
Cumming, GA 30041

TOLL FREE: 844.425.8425

Cincinnati, Ohio

Spectrum Office Tower 11260
Chester Road Suite 350
Cincinnati, OH 45246

Phone: 513.771.0050

Raritan, New Jersey

216 Route 206 Suite 22 Hillsborough Raritan, NJ 08844

Phone: 513.771.0050

Toronto, Canada

1 St. Clair Ave W Suite #902, Toronto, Ontario, M4V 1K6

Phone: 416.663.0900

Hyderabad, India

Incor 9, 3rd Floor, Kavuri Hills
Madhapur, Hyderabad – 500033 India

PHONE: 040-48482789

Noida, India

H-110 - Sector 63 ,
NOIDA , Gautham Budh Nagar ,
UP – 201301

The Future of AI Manufacturing – Panel Discussion

The manufacturing industry thrives on disruptive technologies. Modern technologies present opportunities for manufacturers to automate tasks and processes that were once heavily manual. But it’s not just about automating human labor, it’s about augmenting the way humans perform tasks. Artificial intelligence (AI) is widely used in manufacturing, and the technology will continue to transform the manufacturing industry.

Yet, some businesses are still reluctant to adopt AI. In the recent AI Manufacturing Conference, a panel of experts discussed the challenges, future, and execution of AI in manufacturing. VP of IoT, Analytics and AI, Konrad Konarski moderated the panel. You can watch the recording of the panel discussion above or review the recap below.

Panelists:

  • Konrad Konarski – V-Soft Digital
  • Chris Andraka – Goodman Manufacturing
  • Elias Brown – Vallourec Star
  • David Crawely – University of Houston
  • Justin Kubu – Inland Pipe Rehabilitation

Challenges in Adopting AI in Manufacturing Application

One of the biggest challenges that companies face today is how to effectively integrate AI into their businesses. While the technology is transforming businesses, there are some challenges that companies need to overcome.

  • Reliability of AI
  • Lack of information and knowledge
  • Lack of resources
  • Inability to adopt, change and be innovative
  • Lack of Quality Data
  • Vague idea about executing technology

How to Overcome These Challenges

  • Start implementing AI on a small scale. For example, deploy AI in a single process or a machine
  • Build AI frameworks with best practices
  • Feed AI the required data to support predictive analytics
  • Create use cases of AI to prove its efficiency to the business owners

There is a high probability of adopting technology when it is proven successful. Before transforming an entire business, the adoption should start on a small scale. For example, start implementing AI in a single process or machine. Use these cases to prove the efficiency of AI and how it can improve the business.

The-Future-of-AI-Manufacturing-2-1024x439

Benefits of AI

  • Decreases downtime
  • Reduces time of production
  • Improves performance and accuracy
  • Relieves human laborers of tedious tasks

The biggest myth about AI is that it replaces human working labor. But they should note that AI can only augment the human workforce and eliminate their errors. This way, it improves performance and accuracy. It also decreases downtime and costs of production.

The Future of AI in Manufacturing In the future, manufacturing factories will be completely automated. More organizations will understand the benefits of AI and integrate it into their processes. AI systems use predictive analysis and collaborate with human intelligence to predict the demand for products. AI’s high potential is also used to detect defects in machines and products before they turn into an irreversible error.

Topics: AI, AI for Manufacturing

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