Siemens Digital Industries Implements AI and Digital Tech to Debut High-Efficiency, High-Stability Functions, Driving the Revolution of Smart Manufacturing in Machine Tools
In the new era driven by AI, the requirements for machining precision, efficiency, and stability in the precision machinery industry continue to rise. Facing rapidly changing market challenges, the competitiveness of machine tools no longer depends solely on individual hardware, but rather on the overall performance of the control system in terms of efficiency, flexibility, and digital integration capabilities. At booth H0241 of the TMTS 2026 (Taiwan International Machine Tool Show), Siemens Digital Industries is showcasing the new generation digital CNC platform, SINUMERIK ONE. Featuring forward-looking functions that combine industrial-grade AI, digital twins, and intelligent control technologies, Siemens is creating diverse integration possibilities for the machine tool industry—assisting manufacturers and end-users in enhancing machining efficiency, shortening development cycles, and accelerating digital transformation.
 |
3D 掃描生成技術 縮短設計到生產準備時間
西門子 3D Scanner 技術透過 AI 自動辨識 3D 圖檔中的工件幾何特徵，並生成相應的加工工藝與加工程式，可大幅縮短從設計到生產之間的準備流程。該技術能提升工程師在工藝決策與程式生成上的效率與準確性，並降低人工操作所造成的錯誤風險。對工具機製造商而言，這項能力有助於加速機台應用驗證與交機流程；對終端用戶來說，則能在小量多樣或快速變動的生產環境中，更靈活地完成程式準備與調整，提升生產反應速度與整體產能。
SINUMERK Tuning Center 智慧調校中心 以機器學習突破調機門檻
西門子CNC工具機智慧調校軟體工具，協助客戶快速調校與最佳化機台軸向與動態性能，透過數據分析與引導式流程與機器學習技術，協助工程師快速找到最適合機台的控制參數，提升加工精度與動態性能。系統可利用大量歷史調校數據，自動推估適合機台的調校參數，減少傳統反覆試誤與高度依賴經驗的調機過程。即使非調機專業的工程師，也能透過AI 輔助功能，依據不同機型與加工需求快速完成軸向與運動特性的優化。此技術不僅能縮短機台開發與出廠前的調校時間，也能幫助終端用戶更快將設備調整至最佳運作狀態，提升品質、效率與加工穩定度。
自適應控制與監控 ACM 即時優化切削效能
Adaptive Control & Monitoring (ACM) 是西門子針對 CNC 加工優化所開發的自適應控制與刀具監控技術，系統根據實際加工過程自動調整進給速度，讓機台在不同材料硬度、切削深度或刀具狀態下，始終維持最佳加工效率。同時可即時監控刀具負載與切削行為，提前偵測刀具磨耗或異常情況，並有效降低刀具損壞風險並延長使用壽命。製造業者可在不改變既有加工程式的情況下提升生產、加工效率與穩定度，減少停機時間並維持加工品質。
數位雙生降低設備導入風險
西門子的數位雙生技術可在虛擬環境中完整重現機台結構與加工流程，讓設計、測試與優化工作提前於實體設備完成之前。工具機製造商可透過虛擬機台進行工程驗證、應用展示與操作訓練，加速設備上市與交付。終端用戶則能在設備到位前完成程式測試與人員培訓，縮短正式投產的準備時間。透過虛實整合的方式，企業可降低新設備與新製程導入風險，提升整體生產效率與製造彈性。
3D Scanning and Generation Technology: Shortening Design-to-Production Lead Times
Siemens' 3D Scanner technology utilizes AI to automatically identify the geometric features of workpieces in 3D files and generate corresponding machining processes and programs. This significantly shortens the preparation workflow from design to production. This technology improves the efficiency and accuracy of engineers in process decision-making and program generation while reducing the risk of errors caused by manual operations. For machine tool manufacturers, this capability helps accelerate machine application verification and delivery; for end-users, it allows for more flexible program preparation and adjustments in low-volume, high-mix, or fast-changing production environments, thereby increasing responsiveness and overall throughput.
SINUMERIK Tuning Center: Breaking Commissioning Barriers with Machine Learning
The SINUMERIK Tuning Center is an intelligent software tool for CNC machine tools that helps customers quickly tune and optimize axial and dynamic performance. Through data analysis, guided workflows, and machine learning, it assists engineers in rapidly finding the most suitable control parameters, enhancing machining precision and dynamic performance. The system leverages large volumes of historical tuning data to automatically estimate optimal parameters, reducing the traditional trial-and-error process that relies heavily on experience. Even engineers who are not specialized in tuning can use AI-assisted functions to quickly optimize axial and motion characteristics based on different machine models and machining requirements. This technology not only shortens development and pre-factory tuning time but also helps end-users bring equipment to an optimal operating state faster, improving quality, efficiency, and stability.
Adaptive Control & Monitoring (ACM): Real-Time Optimization of Cutting Performance
Adaptive Control & Monitoring (ACM) is an adaptive control and tool monitoring technology developed by Siemens for CNC machining optimization. The system automatically adjusts the feed rate based on the actual machining process, ensuring the machine maintains peak efficiency across varying material hardness, cutting depths, or tool conditions. Simultaneously, it provides real-time monitoring of tool load and cutting behavior, detecting tool wear or anomalies early to effectively reduce the risk of damage and extend tool life. Manufacturers can improve production efficiency and stability without changing existing programs, reducing downtime and maintaining consistent quality.
Digital Twins: Reducing Equipment Implementation Risks
Siemens' digital twin technology creates a complete virtual representation of machine structures and machining processes, allowing design, testing, and optimization to be completed before the physical equipment is even built. Machine tool manufacturers can use virtual machines for engineering verification, application demonstrations, and operator training, accelerating time-to-market. End-users can complete program testing and personnel training before the equipment arrives, shortening the preparation time for official production. Through this integrated cyber-physical approach, enterprises can reduce the risks of implementing new equipment and processes while enhancing overall production efficiency and manufacturing flexibility.
 |
Industrial Generative AI Assistant: Accelerating Engineering and Knowledge Transfer
The Industrial Copilot assists engineers in improving efficiency during machine tool development, control programming, and equipment tuning. By integrating with the SINUMERIK control system and the TIA (Totally Integrated Automation) portal, the AI understands CNC and automation logic, helping engineers quickly generate code, analyze equipment status, and provide tuning recommendations. Furthermore, the Industrial Copilot systemizes the expertise of senior engineers, helping companies build a sustainable engineering knowledge base. This lowers the barriers to talent training and technical inheritance in the machine tool industry while improving the efficiency of equipment development and implementation.
 |
