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Statisztikai ellenőrző diagramok az állatitermék-előállításban

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MAL 139 (11),697-703.(2017) (621.4Kb)
Date
2017-11
Author
Nagy, Sára Ágnes
Tőzsér, Dóra
Szombath, Gergely
Baranyi, Dániel
Reibling, Tamás
Biksi, Imre
Solymosi, Norbert
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Abstract
SUMMARY Background: In our age, the information society, the computer based technol ogies, including the data analytical procedures are part of each sites of the life. In the production animal sector more and more data are generated day by day. Unfortunately, only a small piece of this huge amount of data is transformed to information, that can be interpreted, used by professionals in decisions. Objectives: The present work demonstrates a relatively simple statistical approach that may help to improve the production, animal health and welfare measures in animal production sector. Materials and methods: Since the 1920s in the industry sector the Statistical Process Control (SPC) is a widely used toolbox to help the producers to improve the efficiency and profitability of production processes. The components of the SPC toolbox are the „magnificent seven”: histogram, check sheet, pareto chart, cause-and-effect diagram, defect concentration diagram, scatter diagram, con trol chart. The last one (also called as Shewhart chart) is the most widely used tool of SPC. Through a case study on piglet weaning weight the authors summa rizes the most important momentums of the creation and interpretation of the control charts. In the example a real world based simulated dataset was used to construct the control charts. Beside this a short review is presented to demon strate control chart applications in animal production areas. Results and Discussion: The presented case study helps the reader to under stand how the statistical control charts can improve the surveillance of animal production and animal health. The authors emphasise that in the „big data” age it is necessary to develop the computational, data analytical skills of veter inarians working on farms, to be able to convert the accumulating raw data to professionally usable information.
URI
http://hdl.handle.net/10832/2761
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