Data collection is often a time-consuming activity and sometimes real-time required. Moving to automation could bring multiple benefits, but sometimes it may not be convenient. In this paper four different situations are analyzed, and for each of them a re-engineered solution enabled by information integration for automating the data collection, if applicable, is proposed. More into detail, the data collection is performed so as to apply a Statistical Process Control for quality management purposes on four different operations, taken as case studies and carried out on a filling machine produced by an Italian company. Statistical Process Control consists in determining two process capability indexes whose values, for completeness, are then compared with the relating Six Sigma level. One of the peculiarities of these case studies is that before collecting the measurements, the systems and instruments were validated through the ANOVA Gage Reproducibility & Repeatability method. This is somehow an innovative procedure, since quite often the preliminary validation step is neglected, thus involving the risk of inaccurate and distorted outcomes.
Statistical process control of assembly lines in manufacturing / Bottani, E.; Montanari, R.; Volpi, A.; Tebaldi, L.. - In: JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION. - ISSN 2452-414X. - 32:(2023), p. 100435.100435. [10.1016/j.jii.2023.100435]
Statistical process control of assembly lines in manufacturing
Bottani E.;Montanari R.;Volpi A.;Tebaldi L.
2023-01-01
Abstract
Data collection is often a time-consuming activity and sometimes real-time required. Moving to automation could bring multiple benefits, but sometimes it may not be convenient. In this paper four different situations are analyzed, and for each of them a re-engineered solution enabled by information integration for automating the data collection, if applicable, is proposed. More into detail, the data collection is performed so as to apply a Statistical Process Control for quality management purposes on four different operations, taken as case studies and carried out on a filling machine produced by an Italian company. Statistical Process Control consists in determining two process capability indexes whose values, for completeness, are then compared with the relating Six Sigma level. One of the peculiarities of these case studies is that before collecting the measurements, the systems and instruments were validated through the ANOVA Gage Reproducibility & Repeatability method. This is somehow an innovative procedure, since quite often the preliminary validation step is neglected, thus involving the risk of inaccurate and distorted outcomes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.