Reducing the latency between machining and measurement using FEA to predict thermal transient effects on CMM measurement

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Abstract

Coordinate Measuring Machines (CMM) are widely used to validate the dimensional conformance of machined components. Since time frames are critical in ensuring cost effective production, it is important to know when a machined component is ready for dimensional inspection. A common approach is to delay the inspection until the component has reached thermal stabilization such as 20 °C as standard, however, this latency incurs an uncertainty of getting either under or overestimated which can result in a considerable waste of time and resources lowering cost effectiveness. Conversely, premature measurement could also increase the measurement uncertainty if significant temperature gradients exist. This paper presents an approach to predict the required latency at which the machined component is within critical thermal boundary conditions and ready for dimensional checks. The approach is comprised of experimental tests required to obtain key boundary conditions including convective and Thermal Contact Conductance (TCC) values. FEA was then used to simulate and validate the latency based on anticipated workpiece conditions. The method was validated on an industrial part, namely a Venturi vessel, in two typical scenarios i.e. placed on the (1) Chuck and (2) CMM to predict the latency required for thermal stabilization using a pre-selected part tolerance level of 1.5 µm. The validation revealed 8.3 min for (1) and 7.6 min for (2) which is a considerable reduction of latency in comparison to waiting for longer periods. This technique was also compared with a typical CMM measurement regime of using a single temperature sensor for compensation. A simple comparison yielded an over or under compensation of 7 µm depending on the position of temperature sensor on the vessel surface. The validations have allowed the formation of a platform for the FEA software to be effectively used to predict the required latency to improve the management of CMM machine usage while ensuring low uncertainty and a cost effective solution.
LanguageEnglish
Pages260-277
Number of pages18
JournalMeasurement: Journal of the International Measurement Confederation
Volume135
Early online date14 Nov 2018
DOIs
Publication statusPublished - Mar 2019

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Coordinate measuring machines
machining
Machining
Finite element method
Temperature sensors
Stabilization
Inspection
Boundary conditions
Chucks
temperature sensors
Cost effectiveness
vessels
inspection
Thermal gradients
stabilization
Costs
boundary conditions
costs
cost effectiveness
Hot Temperature

Cite this

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title = "Reducing the latency between machining and measurement using FEA to predict thermal transient effects on CMM measurement",
abstract = "Coordinate Measuring Machines (CMM) are widely used to validate the dimensional conformance of machined components. Since time frames are critical in ensuring cost effective production, it is important to know when a machined component is ready for dimensional inspection. A common approach is to delay the inspection until the component has reached thermal stabilization such as 20 °C as standard, however, this latency incurs an uncertainty of getting either under or overestimated which can result in a considerable waste of time and resources lowering cost effectiveness. Conversely, premature measurement could also increase the measurement uncertainty if significant temperature gradients exist. This paper presents an approach to predict the required latency at which the machined component is within critical thermal boundary conditions and ready for dimensional checks. The approach is comprised of experimental tests required to obtain key boundary conditions including convective and Thermal Contact Conductance (TCC) values. FEA was then used to simulate and validate the latency based on anticipated workpiece conditions. The method was validated on an industrial part, namely a Venturi vessel, in two typical scenarios i.e. placed on the (1) Chuck and (2) CMM to predict the latency required for thermal stabilization using a pre-selected part tolerance level of 1.5 µm. The validation revealed 8.3 min for (1) and 7.6 min for (2) which is a considerable reduction of latency in comparison to waiting for longer periods. This technique was also compared with a typical CMM measurement regime of using a single temperature sensor for compensation. A simple comparison yielded an over or under compensation of 7 µm depending on the position of temperature sensor on the vessel surface. The validations have allowed the formation of a platform for the FEA software to be effectively used to predict the required latency to improve the management of CMM machine usage while ensuring low uncertainty and a cost effective solution.",
keywords = "Thermal error, CMM, CNC, Soaking Times, Temperature measurement, Thermal contact conductance",
author = "Naeem Mian and Simon Fletcher and Andrew Longstaff",
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AU - Mian, Naeem

AU - Fletcher, Simon

AU - Longstaff, Andrew

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N2 - Coordinate Measuring Machines (CMM) are widely used to validate the dimensional conformance of machined components. Since time frames are critical in ensuring cost effective production, it is important to know when a machined component is ready for dimensional inspection. A common approach is to delay the inspection until the component has reached thermal stabilization such as 20 °C as standard, however, this latency incurs an uncertainty of getting either under or overestimated which can result in a considerable waste of time and resources lowering cost effectiveness. Conversely, premature measurement could also increase the measurement uncertainty if significant temperature gradients exist. This paper presents an approach to predict the required latency at which the machined component is within critical thermal boundary conditions and ready for dimensional checks. The approach is comprised of experimental tests required to obtain key boundary conditions including convective and Thermal Contact Conductance (TCC) values. FEA was then used to simulate and validate the latency based on anticipated workpiece conditions. The method was validated on an industrial part, namely a Venturi vessel, in two typical scenarios i.e. placed on the (1) Chuck and (2) CMM to predict the latency required for thermal stabilization using a pre-selected part tolerance level of 1.5 µm. The validation revealed 8.3 min for (1) and 7.6 min for (2) which is a considerable reduction of latency in comparison to waiting for longer periods. This technique was also compared with a typical CMM measurement regime of using a single temperature sensor for compensation. A simple comparison yielded an over or under compensation of 7 µm depending on the position of temperature sensor on the vessel surface. The validations have allowed the formation of a platform for the FEA software to be effectively used to predict the required latency to improve the management of CMM machine usage while ensuring low uncertainty and a cost effective solution.

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