ASME B89.4.10-2021 pdf free.Methods for Performance Evaluation of Coordinate Measuring System Software.
1 ð21Þ SCOPE A critical issue in industrial coordinate metrology is the measurement ofa work piece to assure compliance with its dimensional requirements. When using a computerized coordinate measuring system (CMS), the usual practice is to correlate computer-calculated outputs with the dimensional requirements of the workpiece. This correlation is performed by various computer routines that process dimensional coordinate data sets consisting of measurement samples of the object being evaluated. The purpose ofthis Standard is to provide guidelines forevaluatingthe qualityofsolutions generated byCMS software and to define minimal documentation requirements for software providers. Additionally, this Standard gives default definitions for collections ofdata sets that span a variety ofreal-world measuring scenarios. These data sets are depen- dent on the fitting algorithm being tested. This Standard is concerned with testing the behavior of algorithm imple- mentation,notthetestingofalgorithms themselves. Thus,thesoftwareistreatedas ablackbox; onlytheinputandoutput are observed and evaluated. Itis notthe intentofthis Standard to endorse or rate any computational method or system. Software performance evaluation is useful because it (a) allows objective validation of software (b) reduces the possibility of error in software application (c) defines a method of comparing CMS software This Standard covers the following areas: input data, feature construction, software documentation, performance characterization, and test methodologies.
3.1 Input Data Rawdata to be used to testand analyze CMS software maybe obtained byphysicallyinspectinga testworkpiece or by mathematicalcomputation. Theformerrepresents atestoftheentiremeasuringsystem,whilethelatterapproachavoids operator, workpiece, environment, and machine influences. The latter approach also makes it possible to more closely control the raw data sets, including limits on their spatial distribution, as well as inclusion of artificially induced form errors. For software analysis, the latter approach is the most universally accepted and the most reliable. This is the approach addressed herein.
3.2 Data Analysis The raw data points are processed by mathematical algorithms with the purpose to calculate perfect-form substitute features. First, substitute features are calculated to represent the original data. Then the substitute features are used to evaluate conformance to tolerances or to determine other geometric characteristics ofthe workpiece. An alternative to the use of substitute features is the use of Functional Gage Simulation, described in Nonmandatory Appendix D. Differentmethods canbeusedforobtainingsubstitutefeatures. Thesemethodsmayhavedifferentobjectivefunctions, i.e., different criteria for deciding that a particular substitute feature is better or worse than other possible substitute features. Different criteria can, in general, lead to different results. The proper selection of fitting criterion and data analysis method is outside the scope ofthis Standard. Fitcriteria are usuallybased on L P -norm estimation, or minimum- circumscribed, or maximum-inscribed methods. Refer to Nonmandatory Appendix C for explanations ofthese methods. The objective ofthis Standard is notto decree thatanyone methodis betterthan anyother. Guidance is providedto the user for checking whether particular CMS software produces results that agree sufficiently closely with the reference results within the context of the design requirements.ASME B89.4.10 pdf download.