Performance evaluation method of the service quality dimensions using Six Sigma metrics, the main components’ quality indicator and the geometric capacity indicator

• Autorzy: Herrera Tomás José Fontalvo , Acosta Roberto Herrera , Maturana Ana Gabriela Banquez

Identyfikatory

DOI

10.2478/emj-2024-0005

• Języki publikacji: EN

Abstrakty

EN

This research aims to propose an evaluation and monitoring method with the Six Sigma performance metrics, the main component quality indicator, and the geometric capacity indicator to control service quality dimensions. The research was quantitative and evaluative. It was developed using primary historical information on the quality criteria of hotel service in twelve periods of 2019. It was possible to demonstrate that the geometric indicator was the most demanding capacity with a value of 0.91163, followed by the multivariate main components’ indicator with a value of 0.9559, establishing as a relevant finding the integrality of the three performance criteria to evaluate a service. Topics of service quality, Six Sigma metrics, multivariate main component and geometric capacity indicators were addressed as a theoretical foundation. The research provides a unique contribution in the form of an innovative and efficient continuous improvement method, which makes services more reliable and accurate. Univariate and multivariate statistics were intensively used to evaluate and improve the dimensions of a service from different perspectives. This method has not been considered from the same approach despite its great usefulness in quality control.

Słowa kluczowe

EN

service measurement; Six Sigma; multivariate capacity indicators

PL

pomiar usług; Six Sigma; wielowymiarowe wskaźniki wydajności

• Wydawca: Oficyna Wydawnicza Politechniki Białostockiej
• Czasopismo: Engineering Management in Production and Services
• Rocznik: 2024
• Tom: Vol. 16, no. 1
• Strony: 65--76
• Opis fizyczny: Bibliogr. 43 poz., tab., wykr.

Twórcy

autor

Herrera Tomás José Fontalvo

• Faculty of Economics University of Cartagena Centro Carrera Street 6 36100 Cartagena, Bolivar, Colombia

• https://orcid.org/0000-0003-4642-9251

autor

Acosta Roberto Herrera

• Faculty of Engineering Atlántico University 43 Street 50-53, Barranquilla 081001 Atlantico, Colombia

• https://orcid.org/0000-0002-9448-1188

autor

Maturana Ana Gabriela Banquez

• Faculty of Economics University of Cartagena Centro Carrera Street 6 36100 Cartagena, Bolivar, Colombia

• https://orcid.org/0000-0002-8354-6396

Bibliografia

• Adhyapak, R., Baby, A., & Koppuravuri, S. (2019). Reduction in call handling time in transportation service industry using lean Six Sigma DMAIC methodology. International Journal of Productivity and Quality Management, 27(3), 352-368. doi: 10.1504/ijpqm.2019.101495
• Aldaihani, M., Alhussainan, A., & Terro, A. (2017). A framework for implementing Six Sigma methodology to accredit university campus facilities in Kuwait. International Journal of Productivity and Quality Management, 20(2), 217-237. doi: 10.1504/ijpqm.2017.081481
• Bagherian, A., Gershon, M., & Swarnakar, V. (2022). Role of employee training on Six Sigma implementation’s success: an empirical study. International Journal of Six Sigma and Competitive Advantage, 14(2), 247- 278. doi: 10.1504/ijssca.2022.124975
• Banquez, A., & Fontalvo, T. (2023). Global performance evaluation based on multivariable statistical control of a public utility company. Pesquisa operacional, 43. doi:10.1590/0101-7438.2023.043.00270103
• Barreto, R., & Herrera, R. (2022). Application of a proposed reliability analysis multivariate capability index on manufacturing processes. Quality Engineering, 34(1), 1-15. doi: 10.1080/08982112.2021.1973035
• Belcher, J. (2018). Developing a quality improvement plan for a small engineering firm in the USA with Six Sigma methodologies. International Journal of Productivity and Quality Management, 24(1), 1-11. doi: 10.1504/ijpqm.2018.091169
• Bothe, D. (1991). A Capability study for an entire product. ASQC Quality Control Transactions.
• Castagliola, P., Maravelakis, P., Psarakis, S., & Vännman, K. (2009). Monitoring capability indices using run rules. Journal of Quality in Maintenance, Engineering, 15(4), 358-370. doi: 10.1108/13552510910997733
• Castagliola, P., Maravelakis, P., Psarakis, S., & Vännman, K. (2009). Monitoring capability indices using run rules. Journal of Quality in Maintenance, Engineering, 15(4), 358-370. doi: 10.1108/13552510910997733
• Chan, L., Cheng, S., & Spiring, F. (1988). The robustness of the process capability index Cp to departures from normality’. In Matusita, K. (Ed.), Statistical Theory and Data Analysis II (pp. 223–239). North Holland, Amsterdam.
• Chen, K., Pearn W., & Lin, P. (2003). Capability Measures for Processes with Multiple Characteristics. Quality and Reliability Engineering International Qual, 19, 101-110. doi: 10.1002/qre.513
• Chia, H. (2023). A simple test to determine the contributors of fraction nonconforming shifts in a multivariate binomial process. Quality Engineering, 35(2), 279-289. doi: 10.1080/08982112.2022.2124876
• Clements, J. (1989). Process capability calculations for nonnormal distributions. Quality Progress, 95-100.
• Cumea, G. (2013). Índices de Capacidad Multivariados. Congreso internacional de arquitectura e ingeniería sostenible, México.
• Das, A., Suman, S., & Sinha, A. (2017). Development of multivariate process monitoring strategy for a typical process industry. International Journal of Productivity and Quality Management, 22(1), 1-21. doi: 10.1504/IJPQM.2017.085844
• De la Hoz, E., Fontalvo, T., & Fontalvo, O. (2020). Evaluación de la calidad del servicio por medio de Seis Sigma en un centro de atención documental en una universidad. Formación universitaria, 13(2), 93-102. doi: 10.4067/s0718-50062020000200093
• De La Hoz, E., Zuluaga, R., & Suarez, M. (2023). A Six Sigma and DEA approach for learning outcomes assessment at industrial engineering programs. International Journal of Six Sigma and Competitive Advantage, 14(3), 279-299. doi: 10.1504/ijssca.2023.130283
• Fontalvo, T., & Banquez, A. (2023). Comparative analysis of multivariate capacity indicators for serial and parallel systems. International Journal of Six Sigma and Competitive Advantage, 14(4). doi: 10.1504/ijssca.2023.10058903
• Fontalvo, T., De La Hoz, E., & Fontalvo, O. (2022a). Six Sigma method to assess the quality of the service in a gas utility company. International Journal of Process Management and Benchmarking, 12(2), 220-232. doi: 10.1504/ijpmb.2022.121628
• Fontalvo, T., Fontalvo, O., & Herrera, R. (2020). Monitoring and control of the quality dimensions performance of a service center in a high education institution. Información Tecnológica, 31(3), 113-120. doi: 10.4067/s0718-07642020000300113
• Fontalvo, T., Herrera, R., & Fontalvo, O. (2021). Método de evaluación de la capacidad multidimensional del nivel sigma de las dimensiones del servicio en un call center de una empresa telefónica. Revista Internacional de Gestión de la Productividad y la Calidad, 34(3), 319-335. doi: 10.4067/s0718-50062020000600247
• Fontalvo, T., Herrera, R., & Gonzalez, Y. (2022b). Yieldlevel performance of quality dimensions trough T2 charts and multivariate capacity indicators applied to a fumigation services company. International Journal of Industrial and Systems Engineering, 41(1), 71-90. doi: 10.1504/ijise.2022.122973
• Fontalvo, T., Herrera, R., & Zambrano, J. (2022c). Threephase method to assess the logistics service using Six Sigma metrics, Hotelling’s T-square control chart and a Main component capacity indicator. International Journal of Productivity and Quality Management, 35(1), 17-39. doi: 10.1504/IJPQM.2022.120720
• García, A., Plaza, A., Joseph, I., & Chong, A. (2020). Optimal multivariate control charts based on linear combination of normal variables. International Journal of Industrial and Systems Engineering, 34(2), 165-192. doi: 10.1504/ijise.2020.105289
• Herrera, R. (2018). Índices de Capacidad Multivariados. Puerto Colombia, Atlántico: Universidad del Atlántico Nuevas Propuestas. doi: 10.18273/revuin.v18n3-2019011
• Jackson, J. (1980). Main Component and Factor Analysis: Part 1 Main Components. Journal of Quality Technology, 12, 201-213.
• Madhani, P. (2022). Lean Six Sigma deployment in HR: enhancing business performance. International Journal of Human Resources Development and Management, 22(1/2), 75-97. doi: 10.1504/ijhrdm.2022.121314
• Maged, A. M., Haridy, S., Kaytbay, S., & Bhuiyan, N. (2019). Continuous improvement of injection moulding using Six Sigma: case study. International Journal of Industrial and Systems Engineering. (2019). Continuous improvement of injection moulding using Six Sigma: case study. International Journal of Industrial and Systems Engineering, 32(2), 243-266. doi: 10.1504/ijise.2019.10021839
• Najm, A., Ridha, M., & Aboyasin, N. (2022). Six Sigma and market performance in Jordanian hospitals. International Journal of Value Chain Management, 13(2), 141-159. doi: 10.1504/ijvcm.2022.123547
• Rana, P, Das, A., Suman, S., & MaitiRana, J. (2018). A statistical monitoring strategy for a pulp and paper industry. International Journal of Industrial and Systems Engineering, 28(4), 530-545. doi: 10.1504/ijise.2018.090449
• Shahriari, H., & Abdollahzadeh, M. (2009). A new multivariate process capability vector. Quality Engineering, 21, 290-299. doi: 10.1080/08982110902873605
• Sharma, J., Tyagi, M., Panchal, D., & Singh, R. (2022). Contemplation of food industry attributes confronted in smooth adoption of Lean Six Sigma practices. International Journal of Six Sigma and Competitive Advantage, 14(1), 32-69. doi: 10.1504/ijssca.2022.124294
• Shinde, R., & Khadse, K. (2009). Multivariate process capability using main component analysis. Ltd. Quality and Reliability Engineering International, 25(1), 69- 77. doi: 10.1002/qre.954
• Sikder, S., Mukherjee, I., & Chandra, S. (2019). A synergic multivariate statistical process control framework for monitoring, diagnosis, and adjustment of multiple response abrasive machining processes. International Journal of Industrial and Systems Engineering, 33(3), 314-345. doi: 10.1504/IJISE.2019.103443
• Sodhi, H. (2023). A comparative analysis of lean manufacturing, Six Sigma and Lean Six Sigma for their application in manufacturing organisations. International Journal of Process Management and Benchmarking, 13(1), 127-144. doi: 10.1504/ijpmb.2023.127902
• Sodhi, H., Singh, B., & Singh, D. (2023). SWOT analysis of Lean Six Sigma: a review. International Journal of Business Excellence, 29(2), 162-184. doi: 10.1504/ijbex.2023.128685
• Sodhi, H., Singh, D., & Singh, B. (2022). Implementation of Lean Six Sigma model for scrap reduction in machining sector. International Journal of Business Excellence, 27(1), 110-124. doi: 10.1504/ijbex.2022.123032
• Sreedharan, V. R., Trehan, R., Dhanya, M., & Arunprasad, P. (2020). Lean Six Sigma implementation in an OEM: a case-based approach. International Journal of Process Management and Benchmarking, 10(2), 147. doi: 10.1504/ijpmb.2020.106789
• Taam, W., Subbaiah, P., & Liddy, J. (1993). A note on multivariate capability indices. Journal of Applied Statistics, 20(3), 339-351. doi: 10.1080/02664769300000035
• Tamminen, S., Ferreira, E., Tiensuu, H., Helaakoski, H., Kyllönen, V., Jokisaari, J., Puukko, E., & Röning, J. (2019). An online quality monitoring tool for information acquisition and sharing in manufacturing: requirements and solutions for the steel industry. International Journal of Industrial and Systems Engineering, 33(3), 291-313. doi: 10.1504/ijise.2019.10024998
• Wang, F., & Chen, J. (1998). Capability index using principal components analysis. Quality Engineering, 11(1), 21-27. doi: 10.1080/08982119808919208
• Wang, F., & Du, T. C. T. (2000). Using principal component analysis in process performance for multivariate data. Omega, 28(2), 185-194. doi: 10.1016/S0305-0483(99)00036-5
• Wierda, S. (1994). Multivariate statistical process control - recent results and directions for future research. Statistica Neerlandica, 48(2), 147–168. doi: 10.1111/j.1467-9574.1994.tb01439.x