Universal Journal of Industrial and Business Management Vol. 2(4), pp. 103 - 110
DOI: 10.13189/ujibm.2014.020402
Reprint (PDF) (294Kb)


Efficient Determination of Sampling Rate and Sample Size in Statistical Process Control


Alessio Gerardo Maugeri 1,*, Gabriele Arcidiacono 2
1 Leanprove – A&C srl, Via Alfonso La Marmora, 45, 50121 Florence, Italy
2 Università degliStudiGuglielmo Marconi, Dipartimento per le Tecnologie, e i Processi di Innovazione (DTPI) Via Plinio, 44,
Rome, Italy

ABSTRACT

We propose a simple method for the determination of minimum efficacious sampling rate and sample size in Shewhart-like control charts, a controversial topic both in the academic and industrial fields dealing with Statistical Process Control (SPC). By modeling the control procedure as the sampling of a stochastic process and analyzing data in the frequency realm, it is possible to identify meaningful system time scales and apply the well-known Nyquist–Shannon sampling theorem in order to define conditions for an efficient quality control practice. Such conditions express the minimal requirements for an efficacious monitoring of quality indices, indicating the minimal efficacious sampling rate and the minimal effective size of rational subgroups in Xbar and R (or S) charts, which are useful both in the set-up phase and in the on-line control phase of the Shewhart’s control charts. Results can be applied also to I-MR charts. No statistical assumptions are made on the monitored data; in particular neither statistical independence nor Gaussianity is assumed in the derivation of the results. We focus on continuous processes like those typical in, but not limited to, e.g. refining, chemical processing and mining.

KEYWORDS
Sampling Rate, Sample Size, Control Charts, Statistical Process Control (SPC), Nyquist-Shannon Sampling Theorem, Correlation Time, Lean Six Sigma (LSS)

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Alessio Gerardo Maugeri , Gabriele Arcidiacono , "Efficient Determination of Sampling Rate and Sample Size in Statistical Process Control," Universal Journal of Industrial and Business Management, Vol. 2, No. 4, pp. 103 - 110, 2014. DOI: 10.13189/ujibm.2014.020402.

(b). APA Format:
Alessio Gerardo Maugeri , Gabriele Arcidiacono , (2014). Efficient Determination of Sampling Rate and Sample Size in Statistical Process Control. Universal Journal of Industrial and Business Management, 2(4), 103 - 110. DOI: 10.13189/ujibm.2014.020402.