Driven by multiple external factors such as the U.S.–China trade war and exchange rate fluctuations, Taiwan’s machine tool industry is facing unprecedented structural pressure. Traditional business models relying on cost advantages and contract manufacturing are no longer sufficient to sustain long-term competitiveness. The industry urgently needs to shift toward transformation pathways centered on enhancing product value-added and strengthening integrated service capabilities, evolving from a pure equipment supplier into a provider of intelligent manufacturing integrated solutions.

This article discusses the urgent need for Taiwan’s precision machining industry to transition into "Data-Driven Manufacturing Partners" amidst global supply chain shifts. Wollong Industrial CEO Yong-Run Zeng emphasizes that high-value sectors like aerospace and semiconductors demand "Zero Defect" quality and full traceability, positioning cutting force sensing technology as the cornerstone of "Digital Quality Certificates." By implementing sensing solutions from Germany’s Pro-micron, Switzerland’s Kistler, and Taiwan’s Wollong, manufacturers can monitor tool wear in real-time, optimize parameters, and reduce machining time (e.g., by 16.5% in Blisk machining). The technology effectively quantifies expert intuition and provides precise diagnostics for processing challenging materials like nickel-based alloys and alumina ceramics. Ultimately, cutting force monitoring is identified as the strategic driver for next-generation manufacturing, enabling Taiwanese firms to secure long-term competitive advantages through process assurance and intelligent optimization.

In recent years, the global manufacturing industry has faced severe disruptions caused by geopolitical tensions between the United States and China, supply chain shocks from the COVID-19 pandemic, and the energy crisis triggered by the Russia–Ukraine war. Under these pressures, Taiwan’s machine tool industry has encountered unprecedented challenges. This paper explores how smart and digital upgrading strategies, with a focus on customized development of high-end special-purpose machines, can strengthen the technological capabilities of Taiwan’s machine tool sector. The key technologies discussed include optimized design of transmission systems, lightweight structural design, and integrated response design of servo control and structural dynamics.

Taiwan's machine tool industry, impacted by the depreciation of the Japanese Yen, faces price competition from both Japan and China. To overcome these challenges, domestic manufacturers must enhance the added functionality of their equipment and boost market competitiveness. The escalating issue of global climate change is driving countries to pursue Net-Zero Emissions by 2050, forcing companies to demand carbon reduction efforts across their supply chains. This makes energy-saving technology a critical competitive factor. Reducing energy consumption has become a key objective in the metal processing sector, requiring machine tool suppliers to integrate add-on software to help customers achieve carbon reduction goals. Consequently, the development of energy-saving technologies specifically tailored for machine tools is vital for future competitiveness.

This article explores the growing importance of smart manufacturing amid pandemic and geopolitical shifts, highlighting the application of immersive interaction in remote collaborative engineering. By leveraging VR, AR, and Universal Scene Description (USD) technology integrated with IoT and engineering data, it enables real-time multi-user collaboration to reduce troubleshooting time for remote production lines and address carbon reduction and labor shortage challenges. ITRI has developed a task editor and immersive environments and will continue advancing digital transformation in smart manufacturing.

Witzig & Frank’s success lies in continuous technological innovation and long-term global partnerships, delivering efficient equipment and customized solutions, particularly in the automotive industry. Looking ahead, the company will focus on industrial automation and smart manufacturing, actively advancing Industry 4.0 technologies to strengthen its leadership in precision machining and automation. With over 150 years of history, Witzig & Frank has evolved from a local workshop into a globally renowned machine tool manufacturer, serving as a model of innovation and international collaboration in modern manufacturing.

This study addresses motor anomaly issues in manufacturing by developing a monitoring system based on the VMX platform and AI toolbox. It captures vibration signals, performs feature analysis and classification to provide early warnings, reducing downtime and waste. Using a bearing life dataset, the system applies time- and frequency-domain features to distinguish normal, abnormal, and failure states. A real-world case validates its benefits, including reduced labor and maintenance costs, lower energy consumption, and minimized defective products, ultimately enhancing intelligent machining efficiency.

This paper introduces a modular smart manufacturing service platform that integrates various APPs across five production stages. Through a service solution editor, XML Process Definition Language (XPDL), task dispatch processor, and standardized JSON data structures, the platform enables flexible data exchange and collaborative operations among APPs. Built on private cloud and NoSQL technologies, it reduces integration complexity and shortens implementation time from four weeks to one hour, accelerating smart manufacturing upgrades, increasing productivity, and driving industrial digital transformation.

This study addresses preload monitoring for ball screws by introducing a diagnostic approach based on small-sample data augmentation. Prolonged operation reduces preload, compromising positioning accuracy, while traditional methods struggle to collect sufficient data. We employ Generative Adversarial Networks (GAN) to augment vibration signals and mitigate data imbalance, comparing CNN, MLP, and XGBoost models. Results show GAN-generated data significantly improves prediction accuracy and generalization, offering an effective solution for industrial machinery health monitoring.

The article introduces a “Rapid Detection Technology for Feed System Rigidity Attenuation in Machine Tool Drive Systems.” It utilizes servo motor sine-wave sweep measurements to obtain the Frequency Response Function (FRF), converting resonance frequency and amplitude into data for comparison with a sensitivity database to assess screw preload conditions. By integrating a digital model database, the method predicts rigidity attenuation trends, with experimental verification showing less than 3% error compared to simulations. This approach enables early fault warnings, reduces downtime losses, and improves equipment utilization and maintenance efficiency. It is well-suited for automated production lines, offering low cost and high accuracy.

This study presents the development of an “Automated Welding Preheat Temperature Monitoring and Warning System,” jointly created by ITRI and China Steel Machinery to enhance welding quality and safety. The system integrates a thermal imaging sensor mounted on a six-axis robotic arm to monitor workpiece surface temperature in real time. When the temperature exceeds preset limits, the system issues alerts and ensures compliance with welding procedure specifications. A multi-angle batch temperature measurement interface enables rapid parameter switching for different workpieces, displaying average, maximum, and minimum temperatures. Additionally, the system supports three operational modes—manual, identity-authenticated, and remote control—meeting Industry 4.0 automation requirements. This solution improves efficiency, reduces human error, and minimizes operational risks in welding processes

This article explores the evolution of machine tools showcased at JIMTOF 2022, focusing on Process Integration and Factory Automation to address labor shortages and decarbonization. Key highlights include in-machine measurement, 5-axis multitasking, and the integration of special processes (e.g., AM and FSW) to achieve "Done-in-One" efficiency. Furthermore, advancements in AI vision, collaborative robots, and AMRs overcome obstacles in long-term unmanned operations. The article concludes that the synergy between hardware, software, and Digital Twin technology is the vital driver for the industry’s Digital and Green Transformation (DX/GX).