ISSN (online): 2504-4494
Feb
2021
Dec
2021
In recent years, the demand for accurate machining and precise assembly of components in a way that makes it possible to locate and align them together in a much closer proximity has grown significantly. The demands put forward by recent innovations in the fields of nano-, micro-, and ultra-precision machining create a need for the development of novel methods for identification and correction of errors influencing machining, selection of optimal manufacturing parameters, and calibration and verification of machine tools. All of that is in order to push forward the machining capabilities, which in turn may bring very positive long-term effects, including reduction of friction in powertrain solutions leading to a decrease in emission of pollution, reduction of energy consumption, reduction of the amount of machining allowances, and reduction of time, costs, and energy expenditure for the purposes of mechanical processing. In this Special Issue of JMMP, we are looking for recent findings, which focus on accuracy improvements in machine tools and machining. We invite contributions on topics including but not limited to the following areas: Identification and compensation of machine tool errors; Selection of optimal machining parameters; Metrology systems integrated in manufacturing tools and lines; Optical metrology in manufacturing (vision-based measurement systems, fringe optics, laser triangulation, etc.); Machine tool performance; Calibration and verification of machine tools; Artefacts for machine verification; Uncertainty estimation; System accuracy modeling.
Keywords: machine tool; correction systems; inspection; verification; calibration; error identification; uncertainty estimation.
Accuracy Improvements in Machine Tools and Machining
In recent years, the demand for accurate machining and precise assembly of components in a way that makes it possible to locate and align them together in a much closer proximity has grown significantly. The demands put forward by recent innovations in the fields of nano-, micro-, and ultra-precision machining create a need for the development of novel methods for identification and correction of errors influencing machining, selection of optimal manufacturing parameters, and calibration and verification of machine tools. All of that is in order to push forward the machining capabilities, which in turn may bring very positive long-term effects, including reduction of friction in powertrain solutions leading to a decrease in emission of pollution, reduction of energy consumption, reduction of the amount of machining allowances, and reduction of time, costs, and energy expenditure for the purposes of mechanical processing. In this Special Issue of JMMP, we are looking for recent findings, which focus on accuracy improvements in machine tools and machining. We invite contributions on topics including but not limited to the following areas: Identification and compensation of machine tool errors; Selection of optimal machining parameters; Metrology systems integrated in manufacturing tools and lines; Optical metrology in manufacturing (vision-based measurement systems, fringe optics, laser triangulation, etc.); Machine tool performance; Calibration and verification of machine tools; Artefacts for machine verification; Uncertainty estimation; System accuracy modeling.
Keywords: machine tool; correction systems; inspection; verification; calibration; error identification; uncertainty estimation.
Chemical Abstracts (ACS), DOAJ, Emerging Sources Citation Index-Web of Science (Clarivate Analytics), Inspec (IET), Norwegian Register for Scientific Journals, Series and Publishers (NSD), Scopus (Elsevier), Web of Science (Clarivate Analytics), CLOCKSS (Digital Archive), e-Helvetica (Swiss National Library Digital Archive), Academic OneFile (Gale/Cengage Learning), EBSCOhost (EBSCO Publishing), Google Scholar, J-Gate (Informatics India), ProQuest Central (ProQuest), Science In Context (Gale/Cengage Learning).
Info at: www.mdpi.com/journal/jmmp/apc
Guest Editors
Prof. Dr. Adam Gąska
Prof. Dr. Ksenia Ostrowska