Calibration of 40 Kg Capacity Digital Scale on Automatic Machine Measurement Mass and Dimension Based on Arduino Uno Using CSIRO-NML: 1995 Method

  • Dodi Sofyan Arief Universitas Riau
  • Minarni Shiddiq Universitas Riau
  • Adhy Prayitno Universitas Riau
  • Muftil Badri Universitas Riau
  • Aditya Sukma Nugraha Research Center for Electrical Power and Mechatronics, LIPI
  • Afdila Muflihana Universitas Riau

Abstract

Every measuring instrument is subject to ageing as a result of mechanical, chemical or thermal stress and thus delivers measured values that change over time. This cannot be prevented, but it can be detected at the appropriate time through calibration. Instrument calibration is one of the primary processes used to maintain instrument accuracy. Calibration is the process of configuring an instrument to provide a result for a sample within an acceptable range. Eliminating or minimizing factors that cause inaccurate measurements is a fundamental aspect of instrumentation design. In this research, the load cell 40 kg assembly process is connected to several other supporting components to form a working system such as digital scale, then calibrated. As for the calibration process using the CSIRO-NML: 1995. Calibration results were analyzed using uncertainty analysis types A and B. Measurement uncertainty is the main parameter in this research. Uncertainties of type A and B are carried out to estimate the value of uncertainty in calibration measurements. By knowing the value of measurement uncertainty can be seen reading correction, and instrument limit of performance. Further the calibration results can be issued in a calibration certificate.

##Keywords:## digital scale, calibration, CSIRO-NML: 1995 method, uncertainty.
Published
Nov 19, 2018
How to Cite
ARIEF, Dodi Sofyan et al. Calibration of 40 Kg Capacity Digital Scale on Automatic Machine Measurement Mass and Dimension Based on Arduino Uno Using CSIRO-NML: 1995 Method. Proceeding of Ocean, Mechanical and Aerospace -Science and Engineering-, [S.l.], v. 5, n. 1, p. 97-102, nov. 2018. ISSN 2443-1710. Available at: <https://isomase.org/Journals/index.php/pomase/article/view/121>. Date accessed: 16 mar. 2025.