This article discusses how a system has been used to develop a means of manufacturing and certifying diamond indenters of an accurate and predictable standard, to meet the new industry standard.
Indentation testing is performed to determine the hardness of materials used in the manufacture of many types of machine parts. These tests apply a diamond indenter under load to the material; then, the size and shape of the indentation left in the material is measured to quantify the hardness. Until recently there has been no standardisation of indenters. The introduction of new standards for Rockwell C hardness tests traceable to NIST forces all testing machines and indenters to meet a single objective standard.
The diamond indenters currently produced vary because of the material from which they are made. Although the fact that diamonds are the hardest of all natural materials makes them ideal for hardness testing, this hardness also means that only other diamonds can shape a diamond indenter, and that is difficult. The Rockwell tip is a 120° right circular cone with a rounded tip. The characteristics of each diamond must be taken into account when making an indenter to ensure that the resulting indenter meets the prescribed standard. Small variations in the shape of one indenter compared with another can produce unacceptable variations in measured hardness, which are as large as the tolerances in the specification for the material being evaluated. To meet the NIST standard, variations in the geometry of diamond indenters had to be reduced.
The new machine characteristics
Pryor Knowledge Systems, a National Instruments Alliance Program member, worked with Dia-Tool to incorporate closed-loop electronic control into an improved manufacturing machine so that Dia-Tool can produce a higher quantity of indenters that meet the new standard. The new manufacturing machine, which incorporates National Instruments DAQ and GPIB boards in a National Instruments 256 MHz Pentium Pro computer under the control of LabVIEW software, combines the processing steps of shaping the indenter with the measurement of the resulting cone into a single automated diamond indenter finishing machine.
Grinding/polishing
The automation concepts implemented in this diamond indenter-finishing machine take full advantage of Dia-Tool's expertise in diamond finishing processes and incorporate improvements into the processing of the diamond indenters. The inspection cycle is incorporated within the same system. The operator testing an indenter sets parameters that control the machine - for example, the number of images to collect, the number of full rotations to process, and more. After manual insertion of the indenter into the fixture, the finishing process begins. The finishing portion of the LabVIEW program monitors position sensor signals using a DAQ board. The program uses a PCI-GPIB controller board to control:
* Grinding jig position.
* Grinding table:
- Angle.
- Rotation.
- Mutation.
- Speed.
* Dwell time of each grinding/polishing step.
Optical imaging
The finished indenter is automatically cleaned and then positioned in the optical imager. Use is made of a Cohu NTSC video camera and an IMAQ PCI-1408 image acquisition board to capture the image of the indenter cone. The machine analyses the profile data collected by the camera to determine whether the tip is within specification from the current viewing position. After preprocessing the image with LabVIEW and IMAQ Vision software, a neural network examines the pattern of edge-description data for deviations from the standard. The machine then rotates the indenter tip and collects and analyses another image until the tip has been viewed several times from several angles.
Neural network analysis
The Pryor Knowledge Systems' EZ-1 Neural Network System is used to improve the speed and accuracy of recognition of complex patterns in noisy data. Typical applications for this technology are vector recognition, spectral signature identification, object sorting, material identification, process control, signal recognition, optical signature recognition, and quality control. The EZ-1 Neural Network System PCI coprocessor board provides the speed of parallel processing for object recognition and classification processes. The coprocessor can analyse 1000 to 20 000 vectors per second, depending on input data rates and network configuration.
To prepare the machine for processing indenters, data from indenters that meet the standard and those that fail to meet the standard are used as prototypes to train the neural network to distinguish between standard indenters and the different failure modes, such as:
* Cone not 120° (±tolerance).
* Spherical tip not tangential to cone (±tolerance).
* Surface roughness.
* Radius of sphere not 200 µm (±tolerance).
When an indenter is being finished, the neural network coprocessor rapidly compares data derived from images of the indenter to the network prototypes. Then the condition of the tip is characterised to indicate acceptance, rejection, or recommendations for rework.
The new manufacturing machine, which incorporates National Instruments DAQ and GPIB boards under the control of LabVIEW software, combines the processing steps of shaping the indenter with the measurement of the resulting cone into a single automated diamond indenter finishing machine.
The National Instruments advantage
National Instruments LabVIEW provides graphical programming for rapid application development, along with easy linkage to GPIB and DAQ functions. These functions, plus the IMAQ Vision image processing functions and linkage to the EZ-1 Neural Network System, provide an integrated solution to the challenges facing Dia-Tool in automating its diamond indenter manufacturing.
National Instruments
082 877 8530
South Africa@ni.com
www.ni.com
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