Improving the logistical processes in corporate service system

• Autorzy: Makarova I. , Khabibullin R. , Belyaev E. , Gabsalikhova L. , Mukhametdinov E.

Identyfikatory

DOI

10.20858/tp.2016.11.1.1

Warianty tytułu

RU

Совершенствование логистических процессов в системе фирменного автосервиса

• Języki publikacji: EN

Abstrakty

EN

The study deals with enhancing the reliability of freight cars by improving the corporate service system. Assessing of the quality of spare parts suppliers is discussed. An algorithm for supplier selection and an evaluation method, based on cluster analysis of indicators of supplier reliability, is proposed. Alternative developments for a service network, in view of expanding of the car fleet powered by natural gas-based fuel have been considered.

RU

В статье рассматриваются способы повышения надежности грузовых автомобилей путем совершенствования процессов в системе фирменного сервиса. Рассмотрен один из путей повышения надежности - оценка качества поставщиков запасных частей. Предложен алгоритм выбора поставщиков и метод оценки, основанный на кластерном анализе показателей надежности поставщика. Рассмотрены варианты развития сервисной сети при расширении парка автомобилей на газомоторном топливе.

Słowa kluczowe

EN

corporate system; spare parts suppliers; cluster analysis; vehicle on natural gas

PL

system korporacyjny; dostawcy części zamiennych; analiza klasterów; pojazdy zasilane gazem ziemnym

• Wydawca: Wydawnictwo Politechniki Śląskiej
• Czasopismo: Transport Problems
• Rocznik: 2016
• Tom: T. 11, z. 1
• Strony: 5--18
• Opis fizyczny: Bibliogr. 16 poz.

Twórcy

autor

Makarova I.

• Kazan Federal University Suumbike av., 10A, 423812, Naberezhnye Chelny, Russia

autor

Khabibullin R.

• Kazan Federal University Suumbike av., 10A, 423812, Naberezhnye Chelny, Russia

autor

Belyaev E.

• Kazan Federal University Suumbike av., 10A, 423812, Naberezhnye Chelny, Russia

autor

Gabsalikhova L.

• Kazan Federal University Suumbike av., 10A, 423812, Naberezhnye Chelny, Russia

autor

Mukhametdinov E.

• Kazan Federal University Suumbike av., 10A, 423812, Naberezhnye Chelny, Russia

Bibliografia

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• 2. Малкин, В.С. Техническая эксплуатация автомобилей: теоретические и практические аспекты. Учебное пособие. Москва: Академия. 2007. 288 p. [In Russian: Malkin, V.S.Maintenance of vehicles: theoretical and practical aspects. A study guide. Moscow: Academy].
• 3. Kubat, C. The database management system for Sakarya automotive suppliers and supply chain. Production Planning & Control. 2004. Vol. 15. No. 7. P. 719-730.
• 4. Боровиков, В.П. Statistica. Искусство анализа данных на компьютере. Санкт-Петербург:Питер. 2003. 344 p. [In Russian: Borovikov, V.P. Statistica. The art of data analysis on the computer. St. Petersburg: Peter].
• 5. Ho, W. & Xu, X. & Dey, P.K. Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research. 2010. Vol. 2020.P. 16-24.
• 6. Ho, W. & Dey, P.K. & Bhattacharya, A. Strategic supplier selection using multi-stakeholder and multi-perspective approaches. Int. J. Production Economics. 2015. Vol. 166. P. 152-154.
• 7. Dey, P.K. & Bhattacharya, A. & Ho, W. Strategic supplier performance evaluation: A case-based action research of a UK manufacturing organization. Int. J. Production Economics. 2015. Vol. 166.P. 192-214.
• 8. Chai, J & Ngai, E.W.T. Multi-perspective strategic supplier selection in uncertain environments. Int. J. Production Economic. 2015. Vol. 166. P. 215-225.
• 9. Sarkis, J. & Dhavale, D.J. Supplier selection for sustainable operations: A triple-bottom-line approach using a Bayesian framework. Int. J. Production Economics. 2015. Vol. 166. P. 177-191.
• 10. Hong-Zhong, H. & Zhi-Jie, L. & Murthy, D.N.P. Optimal reliability, warranty and price for new products. IIE Transactions. 2007. Vol. 39. P. 819-827.
• 11. SangHyun, L. & Kyungil, M. Fuzzy Failure Analysis of Automotive Warranty Claims Using Ageand Mileage Rate. Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence. Lecture Notes in Computer Science. 2009. Vol. 5755. P. 434-439.
• 12. SangHyun, L. & DongSu, L. & ChulSu, P. & et. al. A Fuzzy Logic-Based Approach to Two-Dimensional Warranty System. Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. Lecture Notes in Computer Science. 2008. Vol. 5227. P. 326-331.
• 13. Mark, L. & Alla, S. & Halasya, S.S. Predictive Maintenance with Multi-Target Classification Models. Intelligent Information and Database Systems. Lecture Notes in Computer Science. 2010. Vol. 5991. P. 368-377.
• 14. Xie, W. & Liao, H. & Zhu, X. Estimation of gross profit for a new durable product considering warranty and post-warranty repairs. IIE Transactions. 2014. Vol. 46. P. 87-105.
• 15. Buddhakulsomsiri, J. & Siradeghyan, Y. & Zakarian, A. & et. al. Association rule-generation algorithm for mining automotive warranty data. International Journal of Production Research. 2006. Vol. 44. No. 14. P. 2749-2770.
• 16. Rai, B. & N. Singh. Forecasting warranty performance in the presence of the ‘maturing data phenomenon. International Journal of Systems Science. 2005. Vol. 36. No. 7. P. 381-394.

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.