BTX Precision Completes Acquisition of Addison Precision Manufacturing!
BTX Precision is excited to announce the successful acquisition of Addison Precision Manufacturing (APM), marking its first acquisition of…
CloudNC, a leader in manufacturing technology, has unveiled the CAM Assist Cycle Time Estimator, an AI-powered tool designed to speed up and simplify the CNC machining estimation process. Aimed at addressing the common bottlenecks in quoting, this tool automates the traditionally labor-intensive task of estimating cycle times, making it up to 20 times faster, depending on the complexity of the parts.
The Cycle Time Estimator integrates seamlessly with popular platforms such as Mastercam and Autodesk Fusion, allowing users to quickly estimate machining times and tool paths for 3-axis and 3+2 axis parts. Once generated, the data can be smoothly integrated into the existing estimation workflows, helping machine shops bid on more projects and optimize their resource usage.
CloudNC CEO and co-founder Theo Saville emphasized the importance of the tool, stating, “Quoting for new work is a major bottleneck in the machining industry. Our solution not only speeds up the process but also allows estimators to handle multiple parts simultaneously, providing accurate estimates far faster than manual methods.”
Building on CloudNC’s CAM Assist AI solution, the Cycle Time Estimator automates tool selection and machining algorithms, ensuring accuracy and consistency while reducing human errors. Additionally, the tool provides crucial metadata such as part volume and machining efficiency, further enhancing the estimation process.
Mark Hyde from FJH Group praised the new tool: “CAM Assist has cut our quoting time by 70%, ensuring we generate accurate cycle times and tool paths. This has allowed us to win more work by offering precise estimates.”
With this innovative solution, CloudNC continues to push the boundaries of automation in CNC machining, helping manufacturers increase efficiency, reduce errors, and ultimately win more projects.
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