Developing an online application for automating "house of quality" construction for QFD analysis

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Abstract

QFD analysis is among the few quality tools that can encompass a wide range of processes in product manufacturing. This analysis enables effective planning for the implementation of various technical support tools, which complement each other in prioritizing each problem - product imperfections and low competitiveness. A significant drawback of QFD analysis is the considerable time and effort required to construct the final table/matrix, known as the "house of quality". The study investigated existing solutions aimed at reducing analysis time and identified the main parameters for their implementation. Based on the collected data, the key strengths and weaknesses of existing solutions were identified, and a web application was developed. This article aimed to develop an online application that simplifies and accelerates QFD analysis. The developed application facilitates the automation of the QFD analysis process, significantly enhancing the efficiency of quality management professionals and reducing the time required for this procedure.

About the authors

M. S. Ostapenko

Industrial University of Tyumen

Email: ms_ostapenko@mail.ru
ORCID iD: 0000-0002-3838-3815

U. S. Kholboeva

Industrial University of Tyumen

Email: umida.kholboeva@mail.ru

A. M. Tveryakov

Industrial University of Tyumen

Email: tverykov@mail.ru
ORCID iD: 0000-0002-6444-2559

References

  1. Остапенко М. С. Применение методики QFD для стандартизации параметров металлорежущего инструмента. Известия Самарского научного центра Российской академии наук. 2020;22(1):31–42. Режим доступа: http://www.ssc.smr.ru/media/journals/izvestia/2020/2020_1_31_42.pdf.
  2. Фирсов А.С. QFD-метод макропроектирования металлорежущих станков. Вестник Витебского государственного технологического университета. 2003;(5):72–77.
  3. Шкаруба Н. Ж., Леонов О. А., Темасова Г. Н., Вергазова Ю. Г., Черкасова Э. И., Голиницкий П. В., Антонова У. Ю. Совершенствование QFD-анализа для оценки качества специальной техники. Москва: Логос; 2020. 90 с.
  4. Fatma Kutlu Gündoğdu, Cengiz Kahraman. A novel spherical fuzzy QFD method and its application to the linear delta robot technology development. Engineering Applications of Artificial Intelligence. 2020;87:103348. https://doi.org/10.1016/j.engappai.2019.103348
  5. Norhafizah Dasuki, Fairuz Izzuddin Romli. Quality function deployment for new standing cabin concept of commercial transport aircraft. Journal of Mechanical Engineering. 2018;SI(5):247–257. Available at: https://www.researchgate.net/publication/327528753_Quality_Function_Deployment_for_new_standing_cabin_concept_of_commercial_transport_aircraft.
  6. Лаптев Н. И., Зорин Ю. В., Газизулина А. Ю., Карсунцева А. А. Развитие методологии QFD на примере производства удлиненных кумулятивных зарядов. Известия Самарского научного центра Российской академии наук. 2016;18(4):53–57. Режим доступа: http://www.ssc.smr.ru/media/journals/izvestia/2016/2016_4_53_57.pdf.
  7. Kai-Jung Chen, Tsu-Ming Yeh, Fan-Yun Pai, Der-Fa Chen. Integrating refined Kano model and QFD for service quality improvement in healthy fast-food chain restaurants. International Journal of Environmental Research and Public Health. 2018;(7):1310. https://doi.org/10.3390/ijerph15071310
  8. Gonzalez M. E. Improving customer satisfaction of a healthcare facility: reading the customers’ needs. Benchmarking: An International Journal. 2019;(3):854–870. https://doi.org/10.1108/BIJ-01-2017-0007/full/html.
  9. Alireza Alinezad, Azadeh Seif, Nima Esfandiari. Supplier evaluation and selection with QFD and FAHP in a pharmaceutical company. The International Journal of Advanced Manufacturing Technology. 2013;68(1):355–364. https://doi.org/10.1007/s00170-013-4733-3.
  10. Karanjekar S. B., Lakhe R. R., Deshpande V. S. Building QFD model for technical education: Students as stakeholders. International Journal of Mechanical and Production Engineering Research and Development (IJMPERD). 2018;8(1):621– 634. Available at: https://www.academia.edu/36512606/BUILDING_QFD_MODEL_FOR_TECHNICAL_EDUCATION_STUDENTS_AS_STAKEHOLDERS.
  11. Kazemi M. A. A., Poorebrahimi A., Estemdad N. Developing the model of CRM and QFD in the banking industry by customer participation in service delivery. European Journal of Business and Social Sciences. 2014;3(1):137–145. Available at: https://www.academia.edu/6940240/DEVELOPING_THE_MODEL_OF_CRM_AND_QFD_IN_THE_BANKING_INDUSTRY_BY_CUSTOMER_PARTICIPATION_IN_SERVICE_DELIVERY.
  12. Pandey R., Mukherjee T. Fuzzy QFD for decision support model in evaluating basic cause of children falling into Blue whale game Mumbai. In: 2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT), Mumbai, 13 August, 2018. Mumbai, India; 2018. P. 108–110. https://doi.org/10.1109/ICALT.2018.00032.
  13. Кушнир В. И. Опыт внедрения статистических методов управления качеством в системе TechnologiCS. CADmaster. 2003;(2):14–18. Режим доступа: https://www.cadmaster.ru/magazin/articles/cm_17_technologics.html.
  14. Klochkov Y. S., Tveryakov A. M. Approaches to the improvement of quality management methods. International Journal of System Assurance Engineering and Management. 2020;11(2):163–172. https://doi.org/10.1007/s13198-019-00939-x
  15. Papić L., Klochkov Yu., Aronov J., Gazizulina A. Systems reliability: statistical analysis and applications. Belgrad: The Research Center of Dependability and Quality Management DQM; 2022. 164 p.

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