Integration of equipment performance data, machine and process models, and real-time condition information help create a smart machine tool. Smart machine tools are self aware and are capable of real time diagnosis and adaptation of parameters to take “first part correct” to an optimized “every part correct.” NIST will develop, validate, and demonstrate standards, sensors, and models required to convert current manufacturing equipment into smart machine tools by integrating machine models and machinability decision-making into commercially available computer aided manufacturing software for pre-process parameter optimization, and utilizing in situ monitoring of machine condition to adapt process parameters.
Develop, validate, and demonstrate standards promoting integration of equipment performance data, machine and process models, and real-time condition information for optimized operation of machine tools by 2014.What is the new technical idea?
To achieve timely production of technology-intensive complex products, U.S. manufacturers need current manufacturing equipment to evolve into smart machine tools that can know and communicate their capability and condition, and can optimize their performance. Currently, standards for assessing capabilities of machine tools do not address complex motion and loaded conditions. Meanwhile, there are several parallel efforts to develop standards to represent a machine tool for modeling and communication purposes. Additionally, robust and reliable sensor-based methods for real-time monitoring and prediction of machine dynamics and condition do not yet exist.
NIST will address these challenges by continuing the strong representation and support for national (American Society for Mechanical Engineering—ASME) and international (International Standards Organization—ISO) machine tool performance and information technology standards and by designing and developing the methods, models, devices, sensors, and integrated control required for smart machine tools. Standards for testing of complex coordinated motion will be validated and published. Information technology standards for machine tools will be harmonized while also including a standardized methodology for not only describing the physical structure of the machine tool but also its current capabilities and performance. Additionally, sensors for real-time monitoring of machine dynamics and condition will be calibrated in-situ to provide vital information that in combination with models of the machine and the process allow the machine to make real-time decisions to avoid errors and optimize performance. The end result will demonstrate to users a standard methodology to develop a smart machine tool capable of producing "every part correct."What is the research plan?
A smart machine tool is self aware. To accomplish this, the machine capabilities must be measured and represented in a way that can be input into and understood by the machine controller and other clients interacting with the machine. Several standards committees are currently working on information technology for machine tools, and NIST will support those efforts by acting as an unbiased source of leadership and information to harmonize the several standards addressing methods of digitally representing machines’ components. Standardized tests for geometric and kinematic errors are used to assess the capabilities of the machine and also provide inputs into machine models. This project will ensure that these standards remain up-to-date with modern agile machine tool technology, and this project will propose standardized methods for digitally specifying the machines’ capabilities (i.e., the results of standardized tests). Standardized tests for complex motion assess a machine's capabilities and can be used as validation/verification of machine model output. Standards for 5-axis coordinated motion are still in their infancy. Based on EL work on methods for measuring geometric error, measuring coordinated motion, designing and machining test parts, and modeling of complex motion (see recent results and future milestones), this project will provide technical support to standards committees by proposing, revising, validating, and demonstrating standards for instrumented tests and test artifacts for 5-axis coordinated motion, geometric and thermal tests of rotary heads/tables, and others.
Pre-process measurements when combined with machine and process models lead to the selection of appropriate machine parameters. A comprehensive machine model can be used to predict workpiece errors, which is an important concept in selecting an appropriate machine to produce a part within tolerance, but by itself is not the end goal. This project will test the robustness of a machine modeling method by developing comprehensive machine models for multiple machine tools of different configurations and work to integrate machine models with a commercially available computer aided manufacturing (CAM) package. This integration will not just predict part errors but compensate for them, choosing optimized part position and tool paths. Process models (e.g., a surface location model) can be used in combination with pre-process dynamics or condition testing to allow a user to select appropriate machining conditions based on a part's requirements. These pre-process decisions and compensations promote the concept of "first part correct."
Production machines may produce the first part correctly, but as many parts are produced and the machine ages, conditions of the machine change and the parameters for the first part may no longer be appropriate for later parts. For this reason, a smart machine tool must be able to self-diagnose its current condition and adapt to optimize its performance. This project will provide technical support to standards committees working toward standards in condition monitoring of machine tools. Initiating contact with these committees and their industrial representatives will provide a new source of end-users to help guide our research and foster creative new approaches to machine tool metrology. Pre-process dynamics tests will be used to calibrate in-situ sensors. These "trained" in-situ sensors will provide real-time monitoring of vital machine condition metrics (e.g. spindle condition, tool point dynamics, tool wear). A future direction for this project will be to input measurement signals of in-situ sensors into the machine controller and allow the controller to make automated decisions based on these measurements, adjusting machine parameters to appropriate levels to continually output "every part correct."
Some FY12 milestones related to measuring and modeling an alternative 5-axis machine tool are delayed because of a machine malfunction. The machine has been repaired, and these milestones should still be completed by the end of FY12 assuming continued normal operation of the machine.Standards and Codes:
EL is already engaged with national and international standards committees in machine tool performance testing (ASME B5-TC52, ISO TC39/SC2) and plays significant leadership roles in these efforts, as well as participation in national and international standard committees for information technology for machine tools (ASME B5 TC56 and ISO TC184/SC4). This project will continue to transfer our measurement science results, including development and evaluation of test methods, representative data sets, machine model demonstration, etc., to guide standards development in these committees. This project also looks to expand its participation in standards activities in condition monitoring of machines (ISO TC108/SC5).
EL staff member adjusts a setup to measure complex coordinated motion of a 5-axis machine tool.
Start Date:October 1, 2011
Lead Organizational Unit:el
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