Machine tool capability profiles for representing machine tool health

Parag Vichare, Aydin Nassehi, James Thompson, Stephen T. Newman, Fiona Wood, Sanjeev Kumar

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


Abstract Control charts at present are used to provide statistical representation of machine tool health. These charts are based on machine tool testing standards, for example ISO 230, ASME B5.54 and VDI 3441, and can be utilised to decide a particular resource׳s level of utilisation during manufacturing execution. Although these standards provide an indication of machine tool accuracy, they do not provide any mechanism to exchange and use health information within these control charts to identify whether a particular machine is performing to the desired level of capability and whether that machine is healthy. It is only after control charts are manually interpreted, that machine tool selection decisions can be made. This paper reports research that exploits and extends an ISO 14649 (STEP-NC) Part 201 and Part 200 series (Machine Tool Data Model) for representing machine tool health data. This provides a new approach for representing statistical machine tool accuracy information while maintaining the compliancy within prevalent machine tool testing standards. A data model for representing machine tool health based on capability profiles has been proposed. A case study of machine tool showing the interpretation of a control chart with proposed data model has been utilised to represent machine tool health through capability profiles.
Original languageEnglish
Pages (from-to)70-78
Number of pages9
JournalRobotics and Computer-Integrated Manufacturing
Publication statusPublished - Aug 2015


  • CNC
  • Machine tools
  • Resource information modelling
  • Machine tool testing standards


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