Production Data Acquisition and Analysis Management System: An Example Based on a Study of Automotive Supplier Solution

Lubomir Lengyel

Abstract

Quality of data coming from manual entry of information is a key element in efficiency of decision making process for all support functions and as well management allowing them to quickly react on changing circumstances of working environment. Principle finding of analysis performed within an automotive production companies shows a need to cover such requirement and develop a robust solution with efficient data collection, business intelligence capabilities and analysis support required for fast decision making process speeding up reaction in case of non-conformity. Purpose of KONIS system is providing a highly efficient solution for manual data entry, statistical analysis and decision making support for modern production company.

References

CADCAM Integration, 2013. SuiteMDI. A Manual Data Inputing Application with Support for SuiteMonitoring. [Online] Available at: http://www.suitefactory.com/htmlbrochures/suitemdi.htm [Accessed. 15 November 2013].

Pegasie Technologies, 2013. Intelligent data entry automation. Available at: http://www.pegasie.com/intelligent_data_entry_automation_(idea).php [Accessed 15 October 2013].

Points North, 2013. How to Better Monitor Work Floor Performance, Streamline Tracking Processes and Obtain Accurate, Up-to-the-minute Data. Available at: http://www.points-north.com/whitepapers/lstouchdata.pdf [Accessed 2 September 2013].

Production Process, 2013. ProductionACE Reports: Standard, Custom and Export to Excel and Other Applications. Available at: http://productionprocess.com/ [Accessed 10 November 2013].

Robbins, K., 2013. Problems With the Manual Entry of Data. Available at: http://www.ehow.com/print/info_8101077_problems-manual-entry-data.html [Accessed 10 October 2013].

Warren Wolfe, 2010. How to Better Monitor Work Floor Performance, Streamline Tracking Processes and Obtain Accurate, Up-to-the-minute Data Available at: http://www.points-north.com/whitepapers/lstouchdata.pdf.

Weir, C.R., Hurdle, J.F., Felgar, M.A., Hoffman, J.M., Roth, B., et al., 2003. Direct text entry in electronic progress notes. An evaluation of input errors. Methods Inf Med 42 (1/2003), pp. 61–67, Available at: http://square.umin.ac.jp/DMIESemi/y2003/20040216/03010061.pdf.

Wahi M.M., Parks D.V., Skeate R.C., Goldin S.B., 2008. Reducing errors from the electronic transcription of data collected on paper forms: a research data case study. J Am Med Inform Assoc. 2008 May-Jun; 15(3), pp. 386–389. doi: 10.1197/jamia.M2381

Rieder HL, Lauritsen JM, 2011. Quality assurance of data: ensuring that numbers reflect operational definitions and contain real measurements. Int J Tuberc Lung Dis, 2011 Mar; 15(3) pp 296-304.

MacKenzie, I. S., & Soukoreff, R. W. (2002). Text entry for mobile computing: Models and methods, theory and practice. Human-Computer Interaction, 17, pp. 147-198. [Online] Available at: http://www.yorku.ca/mack/hci3.html [Accessed 12 12 2013].

Authors

Lubomir Lengyel
lengyel.lubomir@gmail.com (Primary Contact)
Lengyel, L. (2013). Production Data Acquisition and Analysis Management System: An Example Based on a Study of Automotive Supplier Solution. Quality Innovation Prosperity, 17(2), 103–110. https://doi.org/10.12776/qip.v17i2.260
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