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The collection of detailed sampling protocols is crucial tool for the success of the Nansen Legacy, because they ensure: Methodological agreement between the involved researchers Continuity and comparable data throughout the 5 years sampling period An easily accessible overview over parameters sampled Easier cruise planning
The collection of detailed sampling protocols is crucial tool for the success of the Nansen Legacy, because they ensure: Methodological agreement between the involved researchers Continuity and comparable data throughout the 5 years sampling period An easily accessible overview over parameters sampled Easier cruise planning
Citations
... Indeed, quite often the data collection is a time-consuming activity; moreover, in practice there is frequently the need for real-time and (above all) precise and accurate measurements [10]. Increased availability of high quality production data and reduced lead time of input data management are recognized among the main benefits achieved by companies which applied advanced automated data collection methods [11]. Also, literature stresses the fact that quality needs to be at the forefront of transformation under digitalization [12], given its importance. ...
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.
Проблема розрахунку допустимого рівня невизначеності вимірювання при допускному контролі виробів машинобудування залишається актуальною. Поставлена задача вирішується шляхом застосування імітаційно-статистичного моделювання контрольно-вимірювальних процедур. Для цієї мети розроблена алгоритмічна модель. Проведено комп'ютерні експерименти і отримані значення відсотків неправильно забракованих і неправильно прийнятих деталей від рівня невизначеності вимірювань, що оцінюється складовими по типу В. Показано, що при двохфакторній контрольно-вимірювальній процедурі вимоги до точності засобів вимірювань в порівнянні з однофакторним варіантом зростають у рази.
