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.
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.
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.
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.
