Machine learning and artificial intelligence (AI) are transforming the manufacturing industry in some pretty dramatic ways, from boosting efficiency, increasing defect detection rates and reducing scrap waste to improving sales forecasts and even giving company leaders the insights they need to revamp business models.


Manufacturing can involve some very inefficient processes, which tend to require continual refinement and adjustment. But that’s precisely why we’re seeing such a dramatic rise in the number of machine learning and artificial intelligence applications in manufacturing. So how can you harness the power of AI to improve your company’s profits and bottom line?

Using Artificial Intelligence Applications to Improve Machine Calibration and Defect Detection

In many manufacturing plants, tolerances totaling thousandths of an inch can mean the difference between a usable end product and defective scrap. This is where machine learning and artificial intelligence technology can be extraordinarily useful, as sensors, lasers and scanning devices can be connected to an AI platform that analyzes items as they move along the manufacturing line.

This technology can be used to detect defects in real time. If multiple items show the same defect or flaw, real-time adjustments can be made to correct the problem. This can save tremendous time and money, as this responsive technology will limit the amount of defect-related waste without requiring human intervention. If a machine’s settings are off slightly, you can identify and correct this problem almost immediately, which means you can produce high-quality items with extreme efficiency.

A well-crafted AI and machine learning interface is also far more effective at detecting defects than a human, especially when you’re dealing with extremely precise tolerances. The end result is less waste, improved efficiency and production lines that will achieve their output goals with much greater speed.

Improving Supply Chain Forecasting is a Top Artificial Intelligence Application in Manufacturing

Supply chain forecasting is a difficult yet essential element of the manufacturing process, as it allows companies to plan production line runs, predict demand and order raw materials well in advance. But getting these forecasts right is a challenge and an inaccurate prediction can result in some significant financial losses and delays.

Supply chain forecasts can fluctuate based on a wide variety of factors, which can be fairly challenging for humans to account for properly. A well-crafted artificial intelligence and machine learning algorithm can take an infinite number of influencing factors into consideration, rendering a highly accurate prediction. The more accurate your predictions, the better your bottom line. In fact, according to one estimate by, this technology can reduce supply chain errors by as much as 50%, while slashing lost sales by 65%.

Helping Companies Establish New Business Models

Machine learning, Predictive Analytics and AI technology can generate useful data that allows business leaders to create new, comprehensive business models and protocols. This technology is very effective at spotting trends and patterns that may not be overly apparent to the average person. AI can generate data that allows you to make sound business decisions with a factual and data-driven focus. Relying upon these technologies can also help to eliminate human bias from the equation, providing a more accurate picture in many cases.

A platform that uses AI and machine learning technology can be used to collect data from a vast range of different sources; then, that data can be used to identify different areas of improvement, expansion, and even new business opportunities. What’s more, this technology can collect, process, and interpret data in a very expedient manner, saving lots of time and effort for company leaders and supporting team members.

These are just three of the many ways in which companies are using artificial intelligence applications in manufacturing. The possibilities are truly limitless, as companies are devising new methods for leveraging this innovative technology in ways that will improve their bottom line.

At SevenTablets, we’re adept at working with companies to fully understand their needs and pain points. Then, we’ll craft a customized mobile app or software that leverages technology such as AI, Augmented Reality, Predictive Analytics and more. We also specialize in areas such as creative UI/UX design, app testing and mobile security.

SevenTablets is based in Dallas, with regional offices in Austin and Houston. If you’re ready to get started with a new app or software development project, contact the team at SevenTablets.

Reach out to our team today!

Venkatesh Kalluru

Venkatesh Kalluru

Chief Technologist, Head of Engineering at SevenTablets
Venkatesh “VK” Kalluru is a technology and business expert with executive and hands-on experience in automating multi-million dollar enterprises and a strong record of success in creating robust information technology architectures and infrastructures. VK brings proven ability in using IT to solve business issues to the SevenTablets team.

VK studied computer science at Jawaharlal Nehru Technological University in Hyderabad, India and earned a Master’s Degree in computer science at George Mason University.
Venkatesh Kalluru