How it Works
Due to a lack of engineering support and limited knowledge of dynamic testing procedures, the frequency response measurements are rarely carried out, especially at Tier I and II facilities that fabricate a large fraction of the total number of U.S. discrete parts due to outsourcing from major aerospace and defense manufacturers. Therefore, the well-established BlueSwarf™ stability improvement technology (i.e., stability lobe diagrams, which separate stable and unstable cutting zones graphically as a function of chip width and spindle speed afforded by high-speed machining is very often not applied. The result is reduced process efficiency and part quality and increased cost. The development of this Internet-based data collection (MetalMax™ DC) and information delivery (Tool Dashboard™) platform described here will require no specialized knowledge from the user. The purpose of the Tool Dashboard™ is to allow users, without extensive knowledge of chatter theory or mechanical vibrations, to take full advantage of the available improvements in process efficiency. Tool Dashboards™ allow process planners to select high-speed milling parameters for maximized material removal rates in a science-based pre-process manner, rather than relying on experience or trial and error testing. The primary mechanism for realizing this capability is dynamics prediction for the tool/holder/spindle/machine assembly.
Through the introduction of our new easy-to-use MetalMax™ Data Collector, we eliminate the primary impediment to full implementation of the academic research in high-speed machining, particularly linear and nonlinear chatter (or unstable machining) models. The MetalMax™ DC enables quick measurement of each tool/machine combination’s frequency response with impact testing where an instrumented hammer is used to excite the structure and the response is recorded using an appropriate transducer, such as an accelerometer. The data collected is encrypted and sent via the internet to our engineers who analytically predict the assembly response by combining the measurements of the individual components with empirically-obtained parameters regarding the machine tool and cutter limits. The chatter models, which can be used to select cutting conditions for both dramatic increases in material removal rates and improved part accuracy, require knowledge of the system frequency response as reflected at the tool point. The results of this analysis are presented graphically and interactively in Tool Dashboards™.
Parameters of the machine/spindle/holder substructure (including the spindle specifications such as top speed and available power and torque), cutter material and geometry, workpiece material and radial immersion are combined with the tool point frequency response function (FRF) measurement. Based on this information, recommendations for chip load and maximum surface speed are made using parameters provided by the tool manufacturer. The data presented to the user in the Tool Dashboard™ includes the stability status, corresponding spindle speed-dependent material removal rate (which may be machine specific power or torque limited in some instances), and recommended milling operating parameters, i.e., spindle speed, axial and radial depths of cut. Due to temperature-driven chemical/diffusive wear, an upper bound on surface speed is imposed on the stability lobe-based spindle speed. In this case, the selected spindle speed can revised to avoid excessive tool wear, while still maintaining a reasonable depth of cut. Feed rates are re-calculated to compensate for chip-thinning caused by low width of cut engagements. Bending moment limitations are calculated based on drawbar gripping forces and tool projection. The user is given the option of choosing between maximizing metal removal rate or tool life.
Once a stable spindle speed and cutting depths are determined using the Tool Dashboard™, the optimized cutting can be validated and maintained using our patented Harmonizer® software. The RPM at which a cutter spins combined with the cutter diameter and number of teeth is responsible for creating the tooth passing frequency. Based on the engagement conditions, the relative magnitude of sound is recorded, and the level of cutting stability is recognized. This system follows a strict set of rules so as to eliminate regenerative waviness and hence eliminates any newly induced chatter by making an RPM recommendation which would put the system back in a stable cutting region. The sound file can be saved and uploaded to BlueSwarf for high level analysis and archiving. Over time, new sound files can be compared to the initial baseline recording to detect possible service issues.