Future of AI in Manufacturing Industry

AI technology will revolutionize manufacturing by enabling self-optimizing factories through data analysis and real-time decision-making.

### The Future of AI in Manufacturing: Insights from Industry Leaders
* 🤖 Today at the AI Future Forum, I am joined by two industry leaders, Park Jin-woo from RTM and Choi Joong-ki from Daedong AI, to discuss the **impact of AI on the manufacturing sector**.
* 🏭 Park Jin-woo, who co-founded RTM, has been focused on **AI innovation in manufacturing** since 2018, primarily in **semiconductor and advanced manufacturing industries**.
* 📊 He emphasizes that manufacturing is undergoing **significant transformation**, driven by innovations in technology, with products like **smartphones and electric vehicles** showcasing this evolution.
* 💡 According to Park, the critical functions in manufacturing include technology development, product design, and production, with a special focus on **optimizing production efficiency and product quality**.
* 🔍 He highlights the challenges in achieving **high yield rates** in semiconductor manufacturing, where complex processes require **precise control** to meet market demands.
* 📈 Park notes that the manufacturing sector generates the **most data among all industries**, making AI essential for **real-time analysis and optimization of production processes**.
* 🤝 He proposes a three-step AI solution to optimize manufacturing processes, which includes **identifying issues**, **analyzing causes**, and **implementing self-optimizing controls**.
* 🚀 Park concludes that while AI adoption in manufacturing is still at about **30% success**, the potential for growth is immense as AI technologies evolve and become **more accessible to engineers on the ground**.

### The Future of AI in Collaborative Work and Agriculture
* 🤖 In the evolving landscape of work, artificial intelligence (AI) is expected to **facilitate collaboration within larger organizational units**, enhancing **efficiency and productivity**.
* 🌐 AI's ability to learn and process information will enable it to work alongside humans, leading to **optimized systems that mirror the advancements in human capabilities**.
* 📊 As AI technology progresses, companies are urged to **prioritize the accumulation of meaningful data** over merely developing AI models or infrastructure.
* 💡 The semiconductor industry exemplifies the competitive race for **data ownership**, with companies like Samsung and TSMC actively **securing data for research and operational excellence**.
* 📈 In manufacturing, firms with strong operational excellence will benefit from AI by **accelerating growth**, while those lacking this foundation may **struggle to keep pace**.
* 🌱 The agricultural sector, represented by companies like Daedong, is leveraging AI for **precision farming and autonomous machinery**, aiming to **reduce labor and enhance productivity**.
* 🚜 Daedong's focus on AI-driven solutions, such as **autonomous tractors** and **data collection technologies**, highlights the importance of **integrating AI into traditional farming practices** for improved efficiency.
* 🎥 A notable example of AI's potential is illustrated in a video from Rolls-Royce, showcasing how AI can **enhance decision-making in maritime operations**, reflecting a broader trend toward **automation in various industries**.

### Advancements in Agricultural Robotics and Precision Farming
* 🤖 Agricultural robots, such as autonomous tractors and small farming robots, are becoming **essential in modern farming practices**, especially in environments where traditional machinery **cannot operate effectively**.
* 🌾 In South Korea, rice paddies have achieved a mechanization rate of **93.6%** due to the Saemaul Movement, while orchards still have a mechanization rate of only **60%**, indicating the **need for robotic assistance** in these areas.
* 🚜 The development of a mechatronic platform that supports **autonomous operation** can facilitate the integration of robots for tasks like **pesticide spraying and crop management**, enhancing **efficiency in challenging environments**.
* 🌱 Precision agriculture, or "precision farming," is gaining traction globally, with the U.S. agriculture sector growing **nearly 10% annually** and **27% of U.S. farms** adopting precision techniques to improve **productivity and sustainability**.
* 📊 In South Korea, the agricultural area has decreased by **1% since 2010**, while the population has also declined by **3%**, leading to a pressing need for **innovative solutions to maintain agricultural productivity and farmer incomes**.
* 💡 A recent pilot project demonstrated that precision farming techniques could **reduce fertilizer usage by 7%** while **increasing crop yields by 7%**, showcasing the potential for enhanced agricultural practices.
* 🌍 As the agricultural landscape evolves, the integration of **AI and data-driven decision-making** is crucial for optimizing farming operations and ensuring food security, particularly in light of **declining labor forces and rising costs**.
* 📈 The future of agriculture hinges on **collaboration among stakeholders**, including farmers, technology providers, and researchers, to leverage advancements in **robotics and AI** for **sustainable farming solutions**.

### AI Integration in Agriculture and Manufacturing: Challenges and Future Prospects
* 🌱 The discussion highlighted the **increasing interest of younger generations** in the agricultural sector, especially in **advanced technologies like AI and robotics**.
* 💡 Daedong is investing in internal R&D to develop its tractor products, while also considering **external investments to enhance its technological capabilities**.
* 🤖 The company is focusing on hiring **AI engineers and robotics experts** to build a robust team, aiming to **internalize knowledge that competitors may not prioritize**.
* 📊 Despite the challenges faced in software development, such as slow initial progress, once a certain level of expertise is reached, the **pace of updates and improvements can significantly increase**.
* 🔍 The need for **better data sharing and collaboration** in manufacturing and agriculture was emphasized, as many companies are hesitant to share data due to **security concerns**.
* 🚧 Both industry leaders acknowledged that overcoming barriers to AI adoption requires a **shift in mindset** among players in the market to encourage **more trials and innovations**.
* 🧑 The importance of demonstrating tangible benefits to farmers was discussed, suggesting that **showing real results is crucial for gaining trust and acceptance of new technologies**.
* 📈 AI agents are envisioned to assist in precision agriculture by providing insights and automating tasks, ultimately **enhancing productivity and efficiency** in farming practices.

[과실연] AI 토크콘서트: 인공지능과 산업의 미래 (산업 AI)

과실연 AI 정책연구소에서 운영하는 AI 미래포럼입니다.
AI 미래포럼 16인 공동의장단과 함께하는 시민사회속으로

과실연 AI 미래포럼

Introducing the head of LG's AI research group, Plaid AI Research, and his role as co-chair of the Future Forum for Supervised AI

Inviting two leaders to talk about the AI industry

Introducing Jinwoo Park, Vice President of RTM and Joongki Choi, CEO of Daedong AI

Jinwoo Park talks about his role at RTM and his efforts to transform AI in manufacturing.

Choi Jung-ki introduces his career as head of KT's AI business and the establishment of Daedong AI Lab

Presentation by Jinwoo Park: Future Industries with Artificial Intelligence

What the future of manufacturing will look like with artificial intelligence

Introducing RTM and its commitment to transforming AI in manufacturing

Activities in various manufacturing industries, including semiconductors, secondary cells, displays, etc.

Demonstrate the difference between the negative perception of traditional manufacturing and the reality of innovative product production

Emphasize the importance of the manufacturing value chain and manufacturing functions

Manufacturing well: balancing productivity and quality

Explain the limits of productivity and quality and the difficulties of managing the high process complexity and yield in the semiconductor industry

Increasing data and the need for artificial intelligence

Envision a factory of the future that optimizes itself (self-optimizing)

The difficulty and low success rate of adopting AI technology (~30% success)

RTM's 3-Step Solution Proposal for AI Adoption Challenges

Step 1: Find the problem (defect, failure, etc.)

Step 3: Control changes and self-optimization

Implementation examples of solutions at each stage (PCB inspection, semiconductor equipment anomaly detection, food bakery line control)

Analyze differences in AI solution adoption by manufacturing sector (semiconductor, automotive, battery, etc.)

The future of manufacturing and its challenges

Where we are: CEO leadership drives AI adoption, specialized talent is scarce

Next steps: Increase engineer-driven AI utilization, improve ease of use

Next steps: Collaborating with AI, building AI-powered teams

How companies can adopt AI and gain competitive advantage (emphasizing the importance of data acquisition)

The future of precision agriculture with AI

CEO Choi Jung-ki introduces Daedong Group's AI utilization and discusses the company's current AI efforts.

Introducing the history and business areas of Daedong Group

Daedong Group's four platforms (Smart Farming, AI, Autonomous Work, Precision Farming)

Daedong's AI Goals: Easily Specialize in Agriculture, Accelerate Digital Transformation

The importance of embracing AI: Minimizing cost versus customer value

Explain the context and impact of introducing self-driving tractors

Vision-based autonomous driving technology development plan

Data collection and utilization (image, video data acquisition)

Plans to develop agricultural robots in various environments, including orchards

Developing a mechatronics-based autonomous driving platform

Explain the concept and global trends of precision agriculture

Introducing the current status of precision agriculture in Korea and Daedong's demonstration project

State of AI decision system development for precision agriculture

Ask Jinwoo Park about creating AI transformation value through collaboration with enterprises

We asked Choi about Daedong's preparation and strategy for AI adoption.

Common questions to both representatives about the challenges and solutions to spreading AI technology

Ask Choi about challenges and solutions to farmers' adoption of AI technology

We asked Park about how to overcome the reluctance of companies to adopt AI technology.

We asked Choi about the future of AI agents in agriculture.