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

311 South Wacker Dr. Suite #1710, Chicago, IL 60606

TOLL FREE: 844.425.8425

Madison, Wisconsin

8401 Greenway Boulevard Suite #100
Middleton, WI 53562

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

Bangalore, India

GINSERV, CA Site No 1, HAL
3rd Stage Behind Hotel Leela Palace
Kodihalli, Bangalore - 560008 India

Why Small and Medium Manufacturers Should Adopt AI

Factory manager in AI-enabled warehouse

AI adoption by large enterprises has increased steadily for the last few years as business leaders look for ways to adapt to drive efficiency at optimal costs. The manufacturing sector particularly has seen the application of AI mostly in large enterprises. Small and medium manufacturers, however, can benefit just as much from AI. The hesitation of some SMBs may stem from the assumption that AI is expensive and difficult to implement. While this may have been true a few years ago, the rapid development in the field of AI is making it increasingly accessible to businesses of all sizes.  AI can be applied in small and medium enterprises, especially in the manufacturing sector, to improve productivity, reduce costs and increase operational efficiency and profitability.

Ways AI Improves Efficiency of Small and Medium Scale Manufacturers

Predictive Maintenance

AI monitoring of machinery helps reduce machine downtime by 30% to 50% and increases machine life by 20% to 40%."

- McKinsey

Machines fail all the time. Traditionally, the industry required experienced workers to monitor machines for signs of trouble and fix them before any disruption occurs. This was not an optimal approach and with new machinery, it is no longer even viable. Furthermore, manufacturers cannot afford downtime and decreased productivity. All manufacturers whether big or small, possess data that can be used to predict machinery breakdown and identify the cause proactively. The availability of AI computational power and advanced analytics at lower costs can help small manufacturers analyze multiple data points and historical data to anticipate machinery breakdown and enable maintenance before it happens.

Quality Assurance

Quality assurance is an integral part of the manufacturing industry. However, traditional quality assurance processes are not 100% accurate. A defective product delivered to the customer can negatively impact the brand image, moreover, detecting defects late in the production process can increase the production cost. AI-enabled visual inspection systems such as computer vision defect detection systems can ensure defects are detected and reported at the right time with accuracy. The computer vision system captures images of parts and products, the machine-learning algorithm compares these with predefined quality parameters, identifies the defective ones, and sends them for repair or discards them. The use of computer vision ensures a strong quality assurance at a much lower cost.

Stages of Quality Control in Manufacturing

  • Detect defects in raw material pre-production
  • Continuously monitor production line for defects
  • Final product QA check off
  • Detect defects in packaging

Yield Enhancement

Manufacturing equipment creates a lot of data, but manufacturing organizations don't use the data efficiently even if it is a well-known fact that big data can offer unique insights and intelligence. With AI engines, manufacturers can use data to gather insights and detect patterns to identify causes of low yields and areas that need attention. Based on this data, performing timely and optimal changes to production processes can increase yields.

Inventory Management

1/3 of Businesses

will miss a shipment deadline because they’ve sold an item that wasn’t actually in stock."

- Flexis

Assessing stock across manufacturing sites according to demand is a costly exercise that needs to be carried out continuously to ensure that there is no needless stockpiling at the wrong location or critical shortages of needed materials. Held up assets in the wrong location raises logistics costs. AI can forecast market and production demands and respond to them with agile and optimized supply chain management. Automated inventory management can alert managers in case there is a shortage. AI can not only reduce the cost of maintaining inventory but also ensure that the inventory is maintained in response to demand.

Employee Safety Management

In manufacturing, employees operate in sometimes hazardous conditions. Employees must adhere to safety standards. It is not possible to manually monitor if employees are following safety standards throughout the entire site 24/7. AI-powered computer vision systems can monitor employees while on the job site and send notifications to managers if any violation is observed.

Conclusion

AI has several more advantages in the manufacturing sector such as AI chatbots to support customer service and provide insights to the company’s sales and marketing teams. AI can transform and improve every department of an organization regardless of its size. In the manufacturing sector especially, AI offers enormous advantages. The Industry 4.0 revolution will not be complete without the adoption of AI.  

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Topics: AI, Manufacturing Industry, Computer Vision in Manufacturing, AI for Manufacturing

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