Sridhar Yendamuri | Smart Factories And Businesses with AI | Streamlining Supply Chains for Greater Business Agility

Sridhar Yendamuri, often referred to as Sridhar Prahasith Yendamuri, has built a distinguished career centered around energy, sustainability, and finance. After beginning his career in manufacturing, he transitioned into finance, specializing in project finance and carbon markets. Sridhar’s passion for sustainable business practices has positioned him as a leading voice in the industry, advocating for responsible growth. Through his expertise in project finance modeling, he helps businesses achieve their sustainability goals while navigating the complexities of the carbon market.He holds an MBA from Columbia Business School, New York, and provides guidance to students on navigating the Ivy League and other leading graduate program admissions processes.

Coming from a background in manufacturing and supply chain, Sridhar Yendamuri always wondered: what’s the best way to speed up processes and reduce costs? Every business, regardless of its size, strives to stay competitive, constantly searching for ways to cut costs while maintaining quality and service. In this relentless pursuit, disruptions often lead to groundbreaking innovations in products and services.

But for many businesses, particularly smaller ones, the pressing question remains: How can we innovate further? Could AI be the solution for cutting costs and optimizing operations?

Its no longer just the big players

Large companies like GE and BMW are using AI to monitor their equipment or defects at speed and accuracy on their production lines. Siemens is using AI to optimize their supply chains.

AI is not only transforming large-scale manufacturing and enterprise operations but is also making significant ways into small factories, restaurants, and bakeries. These smaller establishments can leverage AI to enhance efficiency, reduce costs, improve customer experiences, and foster innovation, revolutionizing the way these businesses operate.

Imagine a Furniture workshop integrating an AI camera system to inspect wooden panels for cracks and knots in real time. Bagel production line implements AI - powered inventory management system to predict ingredient usage, preventing overstocking and minimizing waste. This means bakers don’t have to worry about running out of flour or ordering too much, resulting in smarter, cost-effective operations.  Take a Restaurant in Italy that uses an AI-powered app to personalize customer experiences. The app analyzes individual preferences and suggests dishes, creating a bespoke dining experience for every guest. Not only does this improve customer satisfaction, but it also drives repeat business by fostering a more personalized connection with diners.

AI in manufacturing is using machine learning solutions and deep learning process to optimize the supply chain and manufacturing process with enhanced decision making.

Companies in China are speeding up the process of robot manufacturing and automation to perform repetitive works across pharma, restaurants or manufacturing factories.

As exciting as the future of AI is, we’re still in the early stages of its full integration. However, that doesn’t mean businesses should wait to start thinking about how to implement these technologies. For small factories, restaurants, and bakeries, AI is already proving to be a tool for cost savings, faster production, and improved customer experiences.

By embracing AI now, even in small ways, businesses can stay ahead of the curve, ensuring they remain competitive in a world that’s quickly becoming more automated and data-driven.

The question isn’t whether AI will take over, but how soon we’ll see it fully integrated into every facet of manufacturing, supply chains, and food services.

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