THE PRODUCTION QUALITY MANAGEMENT BASED ON THE PRECEDENT APPROACH AND THE CLUSTERING OF USE CASES

Autores

  • Timur N. Karimov
  • Shamil A. Khamadeev

DOI:

https://doi.org/10.22478/ufpb.2179-7137.2019v8n5.48626

Palavras-chave:

Knowledge base, case approach, quality management, technological preparation of production, clustering, Isikava's chart

Resumo

: In this work the problem of various discrepancies knowledge management is considered during realization of technological production processes of polypropylene tubes. Such discrepancies can make serious impact on manufacturing efficiency enterprise for the reasons of the compelled equipment stand still, sharp decline in final product quality, failures to meet time constraints of production shipment for the consumer, etc. In order to remove discrepancies it is required to define quickly the major factors exerting negative impact on production quality. And for each type of a product there can be the set of factors. The main way for work with the large volume of information concerning problems, their factors and ways of elimination is experience of experts. Such way owing to a human factor is not reliable and cannot be considered as the effective solution of the considered problem. In article as the decision the structure of the knowledge base on the basis of precedents (use cases) is offered. The precedent represents the information block including a basic situation and the decision corresponding to it. The offered structure is founded on hierarchy to Isikava's chart, one of popular instruments of quality control, and listed products. For filling of base precedents it is offered to use an algorithm of a clustering of data CLOPE. Results of work are the three-level structure of the knowledge base, model of a precedent, model of processes of addition of a new precedent and search of a precedent in the knowledge base, an algorithm of a clustering of precedents. It was revealed that the preliminary clustering allows reducing search time considerably. This approach can be used at a stage of technological preparation of production

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Biografia do Autor

Timur N. Karimov

Kazan Federal University, Naberezhnye Chelny Institute

Shamil A. Khamadeev

Kazan Federal University, Naberezhnye Chelny Institute

Referências

Valiev R.A., Khairullin A.Kh., Shibakov V.G. Automated Design Systems for Manufacturing Processes//Russian Engineering Research, 2015. - No. 35(9). - p. 662-665.

Hamadeev Sh. And, Bukharov of S. I. Baz of solutions knowledge of elimination of the discrepancies revealed during work of LLC Tissan//"The Kama readings. Collection of materials of the 2nd interregional scientific and practical conference of students, graduate students and young scientists". - Chelny Emb.: Publishing house Kama State Ing.-Ec. Acad.-2010. - page 123 - 126.

Lysenko of E. The automated synthesis of models of technological processes on the basis of case approach//Scientific sheets of the Belgorod state university. Series: Economy. Informatics. 2014. T. 29. No. 1-1 (172). Page 121-129.

Ishikawa, Kaoru (1990); (Translator: J. H. Loftus); Introduction to Quality Control; 448 p.

Yeremeyev, A.P., Warsaw, P. R. Search of the decision on the basis of structural analogy for intellectual systems of support of decision-making//News of RAS. Theory and control systems. 2005. No. 1. Page 97-109.

A. Aamodt, E. Plaza. Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. AI Communications. IOS Press, 1994, Vol. 7: 1.

Hamadeev Sh. A., Simonova L. A., Ilyukhin of A. K. Baz of precedents of technological routes of forming production within MES systems//Forge and forming production. Processing of materials pressure. 2009. No. 8. Page 29-35.

Jain A., Murty M., Flynn P. Data Clustering: A Review.//ACM Computing Surveys, 1999. Vol. 31, No. 3.

Yang J, Leskovec J. Defining and evaluating network communities based on ground-truth. In: Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics. Beijing, China; 2012. p. 1-10.

Rui Xu, D. Wunsch. Survey of clustering algorithms. IEEE Transactions on Neural Networks, 2005. Vol. 16, No. 3. p. 645-678

Paklin, N. Klasterization of category data: scalable algorithm CLOPE.//BaseGroup Labs - Technologies of the analysis of data. - 2004. URL: <https://basegroup.ru/community/articles/clope>, free. It is checked 14.04.2017.

Yang, Y., Guan, H., You. J. CLOPE: A fast and Effective Clustering Algorithm for Transactional Data In Proc. of SIGKDD ’02, July 23-26, 2002, Edmonton, Alberta, Canada.

Li Jie, Gao Xinbo, Jiao Licheng. A fuzzy CLOPE algorithm and its optimal parameter choice//Journal of Electronics (China), 2006. Vol. 23, No. 3. p. 384-388

Publicado

2019-10-27

Como Citar

KARIMOV, T. N. .; KHAMADEEV, S. A. . THE PRODUCTION QUALITY MANAGEMENT BASED ON THE PRECEDENT APPROACH AND THE CLUSTERING OF USE CASES. Gênero &amp; Direito, [S. l.], v. 8, n. 5, 2019. DOI: 10.22478/ufpb.2179-7137.2019v8n5.48626. Disponível em: https://periodicos.ufpb.br/index.php/ged/article/view/48626. Acesso em: 31 jan. 2023.

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