This article analyzes entries submitted to the AI Enablement Certification Program organized by the Taiwan Machine Tool & Accessory Builders’ Association (TMBA). It reviews AI applications in Taiwan’s machine tool industry, including intelligent machining, predictive maintenance, knowledge management, and digital twins, while identifying challenges related to model drift, real-world validation, cybersecurity, and data governance. With reference to ISO/IEC 42001 and the EU AI Act, it proposes governance measures such as model monitoring, human-in-the-loop controls, version traceability, and data compartmentalization to support reliable, secure, and sustainable AI deployment across the industry.

Embodied AI is driving humanoid robots from demonstration prototypes toward practical factory applications. Their commercialization depends not only on AI, but also on joint modules with high power density, precision, low energy consumption, and manufacturability. Linear actuators, rotary actuators, and dexterous hands account for more than 70% of total system costs, involving ball screws, planetary roller screws, reducers, motors, bearings, and precision machining—key strengths of Taiwan’s machinery industry. This article examines how machine tool builders, component suppliers, and automation companies can move into joint modules, process equipment, and production validation to capture new high-value manufacturing opportunities.

AMTEX 2026 highlights India’s dual-track machine tool development: continued expansion of basic equipment alongside rapid advancement in high-end smart manufacturing. Local builders are increasingly integrating automation, machine connectivity, production management, and condition monitoring into complete solutions. Taiwanese suppliers can capitalize on this transformation by providing high-precision core components, smart sensing technologies, and application services. A phased market-entry strategy—beginning with local agents, system integrators, technical validation, service hubs, and spare-parts support, followed by local assembly or manufacturing—can help reduce price competition and entry risks while creating sustainable opportunities within India’s expanding manufacturing ecosystem.

The EU Machinery Regulation (MR) and Cyber Resilience Act (CRA) are reshaping the concept of modern machinery safety. As smart manufacturing, industrial IoT and remote maintenance become more common, machinery is no longer an isolated system, and cybersecurity incidents may directly compromise control logic and safety functions. This article emphasizes that future machinery safety will rely on three interconnected pillars: machine safety, functional safety and cybersecurity. Manufacturers should adopt Safety & Security by Design, establish integrated safety engineering processes and lifecycle management, and build a more reliable foundation for next-generation intelligent machinery.

Amid the global shift toward net-zero carbon emissions and smart manufacturing, the machine tool industry is accelerating its transition toward higher efficiency, lower energy consumption, and greater intelligence. This article highlights ITRI’s green machine tool technologies, focusing on two key directions: advanced materials and digital twin optimization. Carbon-fiber composites and mineral casting are applied to improve lightweight design, damping performance, thermal stability, and energy efficiency. Meanwhile, a collaborative digital twin platform integrates AI analysis, process simulation, and energy optimization to reduce trial cutting, shorten development time, and improve machining performance. By combining advanced materials, AI, and digital twins, these technologies support the industry’s move toward higher-value, low-carbon, and sustainable manufacturing.

This article examines how agentic AI is enabling small and medium-sized manufacturers to move from automation toward autonomy. With capabilities in perception, reasoning, planning and action, agentic AI can support real-time production scheduling, predictive maintenance, energy optimization, quality improvement and operational resilience. As the global market expands rapidly, leading industrial players are applying agentic AI in machine tools, robotics and digital twins. For Taiwan’s SMEs, agentic AI is more than an efficiency-enhancing tool; it is a strategic technology for addressing labor shortages, net-zero pressures and supply chain volatility while accelerating both digital and green transformation.

This article received the Special Award in the Machine Tool category at the 22nd HIWIN Master’s Thesis Award. The research primarily addressed the need for tool monitoring in multi-condition cutting environments by integrating vibration signals, machining parameters, tool wear images, and surface roughness data to establish models for critical tool life monitoring, remaining useful life prediction, and surface roughness prediction. The study further incorporated GAN-based data augmentation, transfer learning, and a hybrid AI architecture to improve model accuracy and generalization under different working conditions, and finally integrated these models into an intelligent system with real-time monitoring and warning functions.

This study develops an automated geometric error measurement and compensation system for the dual rotary axes (A- and B-axes) of a horizontal five-axis machining center in accordance with ISO 230 standards. A single-point touch probe, homogeneous transformation matrices, and a two-stage batch analysis strategy are employed to identify location and motion-dependent errors. The system integrates OPC UA communication to automatically generate and import volumetric compensation data into the CNC controller. Experimental results and NAS979 cutting tests confirm that the proposed approach significantly improves rotary-axis accuracy and overall volumetric precision.