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| Paixão,Carla S. S.; Santos,Adão F. dos; Voltarelli,Murilo A.; Silva,Rouverson P. da; Carneiro,Franciele M.. |
| ABSTRACT The knowledge of the operational quality of soybean harvester provides useful information to management in order to obtain the maximum performance of all available resources, with minimal expenses. The aimed of this study was to evaluate the quality of mechanized soybean harvesting operation in different formats of plots through statistical process control. Treatments were established from the formats of existing plots in the area (irregular, trapezoidal and rectangular). The activities carried out during the harvest were monitored (harvesting, unloading, handling, maneuvering and climate charts) and through these activities were made the calculation of capacity and harvesting operation efficiencies. In the determination of total losses were used... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Grain harvester; CUSUM; Machine performance; Glycine max (L.) Merrill. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000100106 |
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| Petitgas, Pierre; Poulard, Jean-charles. |
| Quantitative analysis of the spatial patterns in age-structured fish populations provides a useful complement to stock assessment methods. The spatial distribution of an age-structured population is characterized by indicators for location, dispersion and aggregation, which are estimated from survey data. The times series of spatial indicators are organised in a 3D data structure with dimensions along indicators, age classes and years. Multi factor analysis (MFA) is applied to quantify the reproducibility in time of the multivariate structure between age classes and indicators. MFA computes the mean annual pattern over the age classes. The deviation around that pattern in each year is also quantified. A multivariate indicator that characterise the spatial... |
| Tipo: Text |
Palavras-chave: Spatial distribution; Monitoring; CUSUM; Multi factor analysis. |
| Ano: 2009 |
URL: http://archimer.ifremer.fr/doc/2009/publication-6688.pdf |
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| Mesnil, Benoit; Petitgas, Pierre. |
| Statistical Process Control (SPC) methods are extensively used in manufacturing contexts to monitor production processes. This article illustrates their potential utility for monitoring the state of marine ecosystems, using survey indicators. We exemplify the use of one SPC tool, the cumulative sum (CUSUM) control chart, to detect persistent changes in the state of a system as new observations are collected, using simulated and real data. Practical guidelines are given on how the chart parameters can be tuned to achieve an acceptable compromise between the ability to detect anomalies quickly and keeping the risk of false alarms low. The common performance measures associated with control charts depend on some key assumptions being met, and the potential... |
| Tipo: Text |
Palavras-chave: Aquatic resource monitoring; CUSUM; Statistical process control. |
| Ano: 2009 |
URL: http://archimer.ifremer.fr/doc/2009/publication-6689.pdf |
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| Petitgas, Pierre. |
| One method to assess fish stocks using a suite of indicators is the traffic light approach. In this approach, the time series of the different indicators are mapped on a common colour scale to highlight alerts that occur when indicators cross reference limit values. Until now, however, the procedure has lacked a statistical framework. Here, we propose the cumulative sum (CUSUM) monitoring scheme as a suitable statistical framework. CUSUM is a statistical process control method that detects deviations from a reference mean, according to defined performance criteria. With the CUSUM monitoring scheme, alarm signals can be triggered when indicators cross defined in-control limits that correspond to defined probabilities of false alarm and non-alarm (i.e.,... |
| Tipo: Text |
Palavras-chave: Integrated assessment; Traffic light approach; Monitoring; CUSUM; Indicators. |
| Ano: 2009 |
URL: http://archimer.ifremer.fr/doc/2009/publication-6690.pdf |
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