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Estonian Journal of Engineering

Real time production monitoring system in SME; pp. 62–75

Full article in PDF format | doi: 10.3176/eng.2013.1.06

Aleksei Snatkin, Kristo Karjust, Jüri Majak, Tanel Aruväli, Tanel Eiskop


Real time production monitoring systems (PMSs) is an alternative to manual data collection and captures most of the required production data without human intervention. The general objective of the current study is to analyse PMSs and to offer particular solutions for small and medium sized enterprises (SMEs). The subtasks to be solved in the case of each particular PMS include determining relevant parameters, designing PMS and development of the data analysis and prognosis model for short term and long term planning. The selection of suitable PMS components and relevant parameters and the development of lathe cutting unit measuring system are described in the case study. Defendec Inc. and National Instruments Corporation wireless components were adopted to implement a part of the PMS.


  1. Saenz de Ugarte, B., Ariba, A. and Pellerin, R. Manufacturing execution system – a literature review. Prod. Plan. Control, 2009, 20, 525–539.

  2. Meyer, H., Fuchs, F. and Thiel, K. Manufacturing Execution Systems: Optimal Design, Planning, and Deployment. McGraw-Hill, New York, 2009.

  3. Tähemaa, T., Karjust, K. and Pohlak, M. ERP and PLM resources in Estonian SME’s. In Proc. 7th International Conference of DAAAM Baltic Industrial Engineering (Küttner, R., ed.). Tallinn, Estonia, 2010. Tallinn University of Technology, 2010, 386–391.

  4. Karjust, K., Küttner, R. and Pääsuke, K. Adaptive web based quotation generic module for SME’s. In Proc. 7th International Conference of DAAAM Baltic Industrial Engineering (Küttner, R., ed.). Tallinn, Estonia, 2010. Tallinn University of Technology, 2010, 375–380.

  5. Shin, B., Kim, G., Choi, J., Jeon, B., Lee, H., Cho, M., Han, J. and Park, D. A web-based machining process monitoring system for E-manufacturing implementation. J. Zhejiang Univ., Science A, 2006, 7, 1467–1473.

  6. Cowling, P. and Johansson, M. Using real time information for effective dynamic scheduling. Eur. J. Oper. Res., 2002, 139, 230–244.

  7. Majak, J. and Pohlak, M. Decomposition method for solving optimal material orientation problems. Compos. Struct., 2010, 92, 1839–1845.

  8. Kers, J., Majak, J., Goljandin, D., Gregor, A., Malmstein, M. and Vilsaar, K. Extremes of apparent and tap densities of recovered GFRP filler materials. Compos. Struct., 2010, 92, 2097–2101.

  9. Majak, J. and Pohlak, M. Optimal material orientation of linear and non-linear elastic 3D anisotropic materials. Meccanica, 2010, 45, 671–680.

10. Aruniit, A., Kers, J., Goljandin, D., Saarna, M., Tall, K., Majak, J. and Herranen, H. Particulate filled composite plastic materials from recycled glass fibre reinforced plastics. Mater. Sci. (Medžiagotyra), 2011, 17, 276–281.

11. Herranen, H., Pabut, O., Eerme, M., Majak, J., Pohlak, M., Kers, J., Saarna, M., Allikas, G. and Aruniit, A. Design and testing of sandwich structures with different core materials. J. Mater. Sci., Kaunas Univ. Technology, 2011, 17(4), 1–6.

12. Bixler, T. S. Remote monitoring and expert diagnostic support for the pulp & paper industry. In Conference Record, 54th Annual Pulp and Paper Industry Technical Conference. Seattle, WA, 2008, 181–191.

13. Subramaniam, S., Husin, S., Singh, R. and Hamidon, A. Production monitoring system for monitoring the industrial shop floor performance. Int. J. Syst. Appl. Eng. Developm., 2009, 3, 28–35.

14. Chetan, S. and Chen, F. The state of the art in intelligent real-time FMS control: A compre­hensive survey. J. Intell. Manufact., 1996, 7, 441–455.

15. Qiu, R. and Zhou, M. Mighty MESs. IEEE Robotics & Automat. Mag., 2004, 11, 19–26.

16. Nasarwanji, A., Pearce, D., Khoudian, P. and Worcester, R. The impact of manufacturing execution systems on labor overheads. In Proc. World Congress on Engineering (Ao, S., Len Gelman, L., Hukins, D., Hunter, A. and Korsunsky, A., eds). London, 2009. News­wood Ltd, 2009, vol. 1, 734–737.

17. Aruväli, T., Serg, R., Preden, J. and Otto, T. In-process determining of the working mode in CNC turning. Estonian J. Eng., 2011, 17, 4–16.

18. Aruväli, T., Otto, T. and Preden, J. Modern monitoring opportunities in shopfloor. In Annals of DAAAM for 2010 & Proceedings: The 21st International DAAAM Symposium “Intelligent Manufacturing & Automation: Focus on Interdisciplinary Solutions” (Katalinic, B., ed.). Zadar, Croatia, 2010. DAAAM International, Vienna, 2010, 989–990.

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