NEWS
中文Feature Column
- Publish Date：2024-11-07
Smart Manufacturing and Management: The Future Path of AI, Digital Transformation, and Net-Zero Transition — Insights from Professor Chun-Cheng Lin, Department of Industrial Engineering and Management
Photo credit: Getty Images
By Professor Chun-Cheng Lin
Translated by Chance Lai
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Translated by Chance Lai
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Amid rising global raw material prices, tightening environmental regulations, and geopolitical tensions, smart manufacturing and management represent more than a technological upgrade; they signify a fundamental transformation of the entire industrial ecosystem. As a Department of Industrial Engineering and Management (IEM) professor at National Yang Ming Chiao Tung University (NYCU), I have witnessed and participated in every significant phase of this industrial shift.
Here, I share insights and experiences in this field, particularly the roles of artificial intelligence (AI), digital transformation, and net-zero initiatives in advancing smart manufacturing.
AI’s Role in Smart Manufacturing
The rise of AI has injected unprecedented vitality into smart manufacturing. Leveraging deep learning, computer vision, and generative AI, AI can extract valuable insights from vast data, optimizing production processes. In semiconductor manufacturing, numerous faculty members in our department have developed AI applications for defect detection, predictive maintenance, and production scheduling. For instance, I developed a computer vision and deep learning algorithm that detects high-precision machine errors and identifies product defects, reducing downtime and maintenance costs.
Additionally, AI plays a crucial role in dynamic production scheduling by utilizing real-time data and predictive models, enhancing scheduling accuracy, reducing manual intervention, lowering error rates, and shortening production cycles. AI’s impact extends beyond the technical domain, penetrating management-level decision-making processes. Corporate leaders can better predict market demand, optimize supply chain strategies, and achieve optimal resource allocation through data analysis and simulation-driven insights. These applications enable companies to remain agile and responsive in fast-changing market environments.
The Driving Force of Digital Transformation in Smart Manufacturing
Digital transformation is a significant driver of smart manufacturing, encompassing technological applications and comprehensive changes in corporate culture, processes, and organizational structure. Over the past decade, information and communication technologies have profoundly transformed traditional manufacturing models. The Internet of Things (IoT) enables tighter connectivity between devices, facilitating real-time data collection and analysis and enhancing system flexibility and responsiveness.
Cloud computing and big data analytics equip companies with robust data processing capabilities, supporting more precise business decisions and strategic planning. Through adaptive control and machine learning, advanced factory automation systems and smart manufacturing technologies allow for real-time adjustments and optimizations during production, greatly improving efficiency and product quality.
Here, I share insights and experiences in this field, particularly the roles of artificial intelligence (AI), digital transformation, and net-zero initiatives in advancing smart manufacturing.
AI’s Role in Smart Manufacturing
The rise of AI has injected unprecedented vitality into smart manufacturing. Leveraging deep learning, computer vision, and generative AI, AI can extract valuable insights from vast data, optimizing production processes. In semiconductor manufacturing, numerous faculty members in our department have developed AI applications for defect detection, predictive maintenance, and production scheduling. For instance, I developed a computer vision and deep learning algorithm that detects high-precision machine errors and identifies product defects, reducing downtime and maintenance costs.
Additionally, AI plays a crucial role in dynamic production scheduling by utilizing real-time data and predictive models, enhancing scheduling accuracy, reducing manual intervention, lowering error rates, and shortening production cycles. AI’s impact extends beyond the technical domain, penetrating management-level decision-making processes. Corporate leaders can better predict market demand, optimize supply chain strategies, and achieve optimal resource allocation through data analysis and simulation-driven insights. These applications enable companies to remain agile and responsive in fast-changing market environments.
The Driving Force of Digital Transformation in Smart Manufacturing
Digital transformation is a significant driver of smart manufacturing, encompassing technological applications and comprehensive changes in corporate culture, processes, and organizational structure. Over the past decade, information and communication technologies have profoundly transformed traditional manufacturing models. The Internet of Things (IoT) enables tighter connectivity between devices, facilitating real-time data collection and analysis and enhancing system flexibility and responsiveness.
Cloud computing and big data analytics equip companies with robust data processing capabilities, supporting more precise business decisions and strategic planning. Through adaptive control and machine learning, advanced factory automation systems and smart manufacturing technologies allow for real-time adjustments and optimizations during production, greatly improving efficiency and product quality.
In Taiwan, the drive for digital transformation is closely tied to the succession of family-owned businesses. The new generation of successors often has a strong digital mindset and innovative spirit, propelling digitalization and smart manufacturing breakthroughs. This transition enables digital transformation and facilitates the formation of digitalized teams, ensuring a smooth succession process.
Challenges and Opportunities in the Transition to Net-Zero
With climate change intensifying globally, the net-zero transition has become an inescapable trend in the manufacturing industry. The goal of achieving net-zero emissions requires companies to reduce their carbon footprint while maintaining competitiveness and profitability. In this endeavor, smart manufacturing technologies play an essential role. Companies can significantly reduce carbon emissions by adopting energy efficiency optimization technologies, renewable energy sources, and green materials.
For example, my research, published in top IEEE journals, utilizes deep reinforcement learning to optimize real-time charging schedules for AGVs (Automated Guided Vehicles) in smart factories, greatly increasing AGV uptime and production efficiency while lowering carbon emissions.
My research in the leading journal Energy also proposes a method for sharing renewable energy within communities through internet technology, achieving energy savings and revenue growth. These practical cases show that companies can monitor and manage their energy consumption in real time and predict future energy demand by combining AI, IoT, and edge computing. This dynamic adjustment minimizes waste, reduces costs, and realizes a win-win situation for both environmental and economic benefits.
Smart manufacturing and management are continuously evolving, integrating the latest trends in AI, digital transformation, and net-zero initiatives. The College of Management at NYCU, along with the Department of IEM, possesses significant expertise in these key areas, offering extensive professional knowledge and research resources while focusing on integrating advanced technology with practical experience.
Our academic team works closely with numerous companies (including TSMC, UMC, VIS, GlobalWafers, and Unimicron) and institutions (such as the Industrial Technology Research Institute, Institute for Information Industry, and Taiwan Semiconductor Research Institute) to explore innovative solutions.
We also offer cutting-edge courses and research programs that provide the latest technical trends to help businesses overcome the diverse challenges of digital and green transformation. We look forward to partnering with more industry players to drive the development of smart manufacturing and embrace the challenges and opportunities ahead.
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