Improving the methods for determining the index of quality of subsystem element interaction

Authors

DOI:

https://doi.org/10.15587/1729-4061.2021.244929

Keywords:

man-machine system, technology of determining interaction, means of index assessment, assessment conditions

Abstract

It was proposed to improve the existing method of determining the quality of interaction of the elements of subsystems of the Machine Operator-Machining Center-Control Program for manufacturing parts (MO-MC-CP) system. This method combines estimates of social (machine operator), technical (machining center), and informational (control program for manufacturing parts) subsystems. Improvements were achieved through the use of four independent indices which are defined separately. One index takes into account single, double and triple interactions of integrated indicators where values of specific weight of weight coefficients depend on the sample size. The other three indices are a synergistic effect where the weight coefficients do not depend on the sample size. Therefore, the model of this index was modified at the expense of additional subsystems.

Existing approaches to determining the indices are not focused on the assessment of the quality of interaction of the MO-MC-CP system, have software limitations, and work with limited sample sizes. With this in mind, it was decided to improve the existing tools of determining the quality indices of interaction to assess levels of interaction of the subsystem elements.

The proposed software-implemented methods and the technology of index assessment improve the efficiency of the assessment of complex systems. Experimental verification has shown the superiority of interaction quality indices over those in the existing methods. A sign of efficiency is as follows: a smaller value of mean-square deviation of the proposed indices in comparison with the existing ones: S(ІQI1)=0.812; S(ІQI2)=0.271; S(ІQI3)=0.675; S(ІQI4)=0.57 and S(І)=0.947; S(І)=0.833; S(І)=0.594, respectively.

The results obtained in the study of the interaction quality index are useful and important because they make it possible to better assess the interaction of subsystem elements and apply the proposed technology at industrial enterprises.

Author Biography

Alexander Laktionov, National University «Yuri Kondratyuk Poltava Polytechnic»

PhD, Associate Professor

Department of Automation, Electronics and Telecommunications

References

  1. Tomitsch, M., Hoggenmueller, M.; Wang, B. T., Wang, C. M. (Eds.) (2021). Designing Human–Machine Interactions in the Automated City: Methodologies, Considerations, Principles. Automating Cities. Advances in 21st Century Human Settlements. Singapore: Springer, 25–49. doi: http://doi.org/10.1007/978-981-15-8670-5_2
  2. Gautam, R., Singh, P. (2015). Human machine interaction. International Journal of Science, Technology & Management, 4, 188–193.
  3. Cruz-Benito, J., García-Peñalvo, F. J., Therón, R. (2019). Analyzing the software architectures supporting HCI/HMI processes through a systematic review of the literature. Telematics and Informatics, 38, 118–132. doi: http://doi.org/10.1016/j.tele.2018.09.006
  4. Al Said, N., Al-Said, K. M. (2020). Assessment of Acceptance and User Experience of Human-Computer Interaction with a Computer Interface. International Journal of Interactive Mobile Technologies (iJIM), 14 (11), 107–125. doi: http://doi.org/10.3991/ijim.v14i11.13943
  5. Nardo, M., Forino, D., Murino, T. (2020). The evolution of man–machine interaction: the role of human in Industry 4.0 paradigm. Production & Manufacturing Research, 8 (1), 20–34. doi: http://doi.org/10.1080/21693277.2020.1737592
  6. Lepak, L. A. (2006). Metodolohichni zasady analizu i syntezu avtomatyzovanykh informatsiinykh system orhanizatsiinoho upravlinnia. Zbirnyk naukovo-tekhnichnykh prats. Naukovyi visnyk NLTU Ukrainy, 198–205.
  7. Liu, J.-X., Feng, S.-X., Zeng, X.-Y. (2019). Study on Influencing Factors of Controllers’ Undesirable Stress Response Based on GRAY-DEMATEL Method. 2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE). doi: http://doi.org/10.1109/qr2mse46217.2019.9021214
  8. Wijanarka, B. S., Nuchron, N., Rahdiyanta, D., Habanabakize, T. (2018). The Task of Machine Tool Operators in Small and Medium Enterprises in Indonesia. Jurnal Pendidikan Teknologi Dan Kejuruan, 24 (1), 39–45. doi: http://doi.org/10.21831/jptk.v24i1.18004
  9. Kozyr, A. H. (2021). Analiz metodychnoho zabezpechennia doslidzhen z otsinky erhatychnykh system v protsesi vyprobuvan obladnannia spetsialnoho pryznachennia: Matematychne ta imitatsiine modeliuvannia system. MODS 2021. Chernihiv: NU «Chernihivska politekhnika».
  10. Lysohor, V. M., Sorokun, S. V., Tsyhanenko, O. M. (2006). Modeli kontroliu hrupovoi vzaiemodii operatoriv liudyno-mashynnykh system upravlinnia u prostori peredatnykh funktsii. Tekhnika v silskohospodarskomu vyrobnytstvi, haluzeve mashynobuduvannia, avtomatyzatsiia, 283–291.
  11. Voloshchuk, R. V. (2013). Porivnialnyi analiz pidkhodiv do vyznachennia vahovykh koefitsiientiv intehralnykh indeksiv stanu skladnykh system. Induktyvne modeliuvannia skladnykh system, 5, 151–165.
  12. Kutkovetskyi, V. Ya. (2002). Ymovirnisni protsesy i matematychna statystyka v avtomatyzovanykh systemakh: navchalnyi posibnyk. Mykolaiv: Vyd-vo MDHU, 150.
  13. Tovkus, O. I., Antypenko, B. A., Bakhmach, M. V., Bychko, D. V., Yelisieieva, A. R., Kovalenko, R. Yu. (2017). Modeli ta informatsiini tekhnolohii proektuvannia i upravlinnia v skladnykh systemakh. Sumy: Sum DU, 84.
  14. Bouchner, P. Plenary Lecture. Research in the field of Human-Machine Interaction in transport systems: Development of analyzing tools, measurement methodologies and advanced interactive simulators. Available at https://www.wseas.org/cms.action?id=1390
  15. Krugh, M., McGee, E., McGee, S., Mears, L., Ivanco, A., Podd, K. C., Watkins, B. (2017). Measurement of Operator-machine Interaction on a Chaku-chaku Assembly Line. Procedia Manufacturing, 10, 123–135. doi: http://doi.org/10.1016/j.promfg.2017.07.039
  16. Lundberg, J., Johansson, B. J. E. (2020). A framework for describing interaction between human operators and autonomous, automated, and manual control systems. Cognition, Technology & Work, 23 (3), 381–401. doi: http://doi.org/10.1007/s10111-020-00637-w
  17. Villani, V., Czerniak, J. N., Sabattini, L., Mertens, A., Fantuzzi, C. (2019). Measurement and classification of human characteristics and capabilities during interaction tasks. Paladyn, Journal of Behavioral Robotics, 10 (1), 182–192. doi: http://doi.org/10.1515/pjbr-2019-0016
  18. Brzowski, M., Nathan-Roberts, D. (2019). Trust Measurement in Human–Automation Interaction: A Systematic Review. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 63 (1), 1595–1599. doi: http://doi.org/10.1177/1071181319631462
  19. Cochran, D. S., Arinez, J. F., Collins, M. T., Bi, Z. (2016). Modelling of human–machine interaction in equipment design of manufacturing cells. Enterprise Information Systems, 11 (7), 969–987. doi: http://doi.org/10.1080/17517575.2016.1248495
  20. Combefis, S., Giannakopoulou, D., Pecheur, C., Feary, M. (2011). A formal framework for design and analysis of human-machine interaction. 2011 IEEE International Conference on Systems, Man, and Cybernetics. doi: http://doi.org/10.1109/icsmc.2011.6083933
  21. Ke, Q., Liu, J., Bennamoun, M., An, S., Sohel, F., Boussaid, F.; Leo, M., Farinella, G. M. (Eds.) (2018). Computer Vision for Human–Machine Interaction. Computer Vision for Assistive Healthcare, 127–145. doi: http://doi.org/10.1016/b978-0-12-813445-0.00005-8
  22. Laktionov, O. I., Flehantov, L.O. (2019). Improvement of methodsquality assessment interaction machine workers with technical and information subsystem elements. Elektronni ta mekhatronni systemy: teoriia, innovatsii, praktyka. Poltava: Poltavskyi Natsionalnyi tekhnichnyi universytet imeni Yuriia Kondratiuka, 148–155.
  23. Laktionov, O. I. (2021). Doslidzhennia tekhnolohii otsiniuvannia y vidboru skladnykh system: Matematychne ta imitatsiine modeliuvannia system. MODS 2021. Chernihiv: NU «Chernihivska politekhnika».
  24. Akulenko, K. Yu. (2017). Konspekt lektsii z navchalnoi dystsypliny «Teoriia pryiniattia rishen» dlia studentiv spetsialnosti 122 «Kompiuterni nauky» dennoi formy navchannia. Rivne: NUVHP, 51.
  25. Bijma, F., Jonker, M., Vaart, A., Erné, R. (2017). An Introduction to Mathematical Statistics. Amsterdam University Press. doi: http://doi.org/10.1515/9789048536115
  26. Samborskyi, O. S. (2017). Obhruntuvannia vyboru metodu formuvannia vybirky u doslidzhenniakh farmatsevtychnoho rynku. Kharkiv: Natsionalnyi farmatsevtychnyi universytet MOZ Ukrainy, 27.

Downloads

Published

2021-12-29

How to Cite

Laktionov, A. (2021). Improving the methods for determining the index of quality of subsystem element interaction. Eastern-European Journal of Enterprise Technologies, 6(3 (114), 72–82. https://doi.org/10.15587/1729-4061.2021.244929

Issue

Section

Control processes