1. Department of Machinery

2. Cowork with Georgia Tech Oli tehtud mitmed artiklid koos. 2 doktoranti külastasid Yan Wang-i, kuid siis kui ta oli UCF ülikoolis. Yan Wang on välis liige meie grandil ETF9460 Shevtshemko tegi Yan Wangiga koos projekti Fulbright raames VF446. Rohkem infot koostöö osas saab vaadata www.idssteam.com www.idssteam.com

3. Cowork with Georgia Tech 1.Shevtshenko, E.; Bashkite, V; Maleki, M.; Wang, Y. (2012). Sustainable Design of Material Handling Equipment: A win-win approach for manufacturers and customers. Mechanika, 18(5) 2.Sahno, J.; Opik, R.; Kostina, M.; Paavel, M.; Shevtshenko, E., Wang, Y. (2012). Knowledge Management Framework for Production Route Selection in Manufacturing Enterprises. In: Proceedings of the 8th International Conference od DAAAM Baltic Industrial Engineering 19- 21st April 2012 3.Shevtshenko, E.; Yan, W. (2009). Decision support under uncertainties based on robust Bayesian networks in reverse logistics management. International Journal of Computer Applications in Technology, 36 4.Shevtshenko, E.; Karaulova, T.; Kramarenko, S.; Wang, Y. (2009). Manufacturing project management in the conglomerate enterprises supported by IDSS. Journal of Achievements in Materials and Manufacturing Engineering, 33(1) 5.Shevtshenko, E.; Karaulova, T.; Kramarenko, S.; Wang, Y. (2009). Manufacturing project management in the conglomerate enterprises supported by IDSS. Journal of Achievements in Materials and Manufacturing Engineering, 33(1), 94 - 102.

4. Shevtshenko, E., Zahharov, R., Karaulova, T.; Wang, Y. (2008). Advanced Concepts Integration for the Compression of Construction Project Schedule. Katalinic, B. (Toim.). DAAAM International Scientific Book 2008 (759 - 772). Viin, Austria: DAAAM International Vienna Kramerenko, S.; Shevtshenko, E.; Karaulova, T.; Wang, Y (2008). Decision Analysis in Project Management Process. Journal of the Machine Engineering, 8(2) Shevtshenko, E.; Karaulova, T.; Kramarenko, S., Y. Wang (2007). IDSS used as a framework for collaborative projects in conglomerate enterprises. Journal of Achievements in Materials and Manufacturing Engineering, 22. Shevtshenko, E.; Karaulova, T.; Kramerenko, S.; Wang, Y. (2007). IDSS as a tool for project management in a collaborative network of SME-S. Journal of the Machine Engineering, 7(2, Manufacturing Intelligent Design and Optimization)-

5. Common Structure of Mektory Project Implementation MEKTORY Project Enterprise diagnostic Reconstruction of the manufacturing system Contact with enterprise Improvements suggestions Processes modelling and simulation Reliability analysis of the processes Enterprise level Masters & Doctoral students, researches Case study for thesis University level Contact with other universitats

6. Tasks of Project 1.Choosing of the most appropriate methods for analysis at machinery enterprises 2.Elaboration of the effective decision making methodology for production process reliability growth 3.Connection of the methodology with the standard methods for reliability estimation 4.Practical implementation of the proposed methodology 5.Transfer of data from analyzing system to decision making system Objective is increasing of efficiency and productivity of the company. Using the new methods and elaboration new tools for enterprise efficiency increasing.

7. Project for Densel Baltic The main aim of the current project is Database elaboration for ISO 9001 documentation for SME The database allows quickly determine relationship between different ISO documents and get constant feedback of the company’s quality system.

8. view of the infosystem development

9. Main procedures Additional procedures

10. Database structure and implementation

11. Procedure description

12. Structure of procedure implemented in ARIS

13. NPV (Net present value) calculation procedure Implementad in MS EXCEL

14. Ü Document connected with current procedure

15. Processes reliability assesment Reliability assessment tool must help engineers quickly and with great precision estimate the most unreliable places of a production process and to suggest the most efficient ways for reliability improvement

16. Process Model is Base for Reliability Analysis SMEs encounter with difficulties to implement reliability principles in production due to: complexity of existing methods for reliability estimation necessity of expensive software and skilled employees difficulties in decision making for reliability improvement SMEs encounter with difficulties to implement reliability principles in production due to: complexity of existing methods for reliability estimation necessity of expensive software and skilled employees difficulties in decision making for reliability improvement

17. Common framework of research Quantitative measures of system reliability Recommendation for reliability improvement Enterprise statistical data of faults Process model FTA Reliability prediction RBD Equipment maintenance plan Input data Methods Results BBN for decision making Classifier of faults FMEA Extended part of reliability analysisMain part of reliability analysis Reliability of manufacturing process

18. Data transfer from FMEA to BBN

19. Template of the classifier of faults in BBN

20. The algorithm of integration process

21. BBN after “Poke-Yoke” implementation Probability of error on the top level is 11%! It was improved by 3%. Probabilities of “Personnel error” class and “Inattention to details” were improved by 3% and 16%, respectively