Item functions as originally intended, shows signs of normal wear.
Technical Description
The DN SOLUTIONS PUMA SMX5100L / LB is a high-performance horizontal machining center engineered for demanding production environments. Featuring dual main spindles, this machine enables simultaneous machining operations, significantly boosting productivity and throughput. Each main spindle delivers a maximum turning diameter of 32.670 inches and a turning length of 120.100 inches, accommodating large and complex workpieces with ease. The 18.000-inch chuck diameter ensures robust workholding for heavy-duty applications. The machine’s rapid traverse rates are impressive, with X, Y, and Z axes each achieving 1,574 inches per minute, allowing for swift tool positioning and reduced non-cutting time. This combination of dual spindles, generous travel, and high-speed axis movement makes the SMX5100L / LB ideal for high-volume, precision machining tasks in industries such as automotive, aerospace, and energy. The horizontal configuration enhances chip evacuation and provides excellent access to the work area, improving overall machining efficiency. Designed with rigidity and stability in mind, the machine’s robust construction supports heavy cutting loads and maintains accuracy over extended production runs. Advanced control systems and automation-ready features further enhance operational flexibility and ease of integration into modern manufacturing workflows. The PUMA SMX5100L / LB stands out as a versatile, reliable solution for manufacturers seeking high-speed, high-precision horizontal machining capabilities.
Data Accuracy and Verification
Specifications and technical details are compiled from manufacturer documentation, historical records, and third-party industry sources. While care is taken to ensure accuracy, this information is provided for reference purposes only and may contain errors or omissions. Users should independently verify all details before relying on them.
If you identify any inaccuracies, please help us improve our data by