Application of Mahalanobis-Taguchi System in Liver Function Profile of Methadone Flexi Dispensing Program

Authors

  • S N A M Zaini Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, 26600 Pekan Pahang, Malaysia
  • S K M Saad Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, 26600 Pekan Pahang, Malaysia
  • M Y Abu Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, 26600 Pekan Pahang, Malaysia

DOI:

https://doi.org/10.33736/jaspe.4283.2022

Keywords:

Mahalanobis-Taguchi system, classification, optimization, liver function profile, methadone flexi dispensing program

Abstract

Patients under the methadone flexi dispensing (MFlex) program are required to do blood tests like liver function profile. A doctor assesses 3 parameters like Alk phosphatase, ALT (SGPT), and AST (SGOT) to ensure the patient has a liver problem. Consequently, the existing system does not have a stable ecosystem towards classification and optimization. The objective is to apply the Mahalanobis-Taguchi system (MTS) in the MFlex program. The data is collected at Bandar Pekan clinic with 34 parameters. Two types of MTS methods are used like RT-Method and T-Method for classification and optimization respectively. The average Mahalanobis distance (MD) of healthy is 1.00 and unhealthy is 352.58. A positive degree of contribution has only 1 parameter. 15 unknown samples have been diagnosed. Type 2 of 6 modifications has been selected as the best-proposed solution. In conclusion, a pharmacist from Bandar Pekan clinic confirmed that MTS can solve problems in the classification and optimization of MFlex program.

References

Waly, G. (2021). World Drug Report 2021. United Nations: Office on Drugs and Crime. http://www.unodc.org/unodc/en/data-and-analysis/wdr2021.html

Buntat, Y., & Rahaman, D. R. (2014). Addiction profile among addicts detained at CRCC throughout Malaysia. Jurnal Antidadah Malaysia, 12(1), 110-121. ISSN: 1985-1707

Yuswan, F., & Dazali, M. N. M. (2016). Policies and Standard Operating Procedures Methadone Treatment Program. 7-42.

Peacock, A., Leung, J., Larney, S., Colledge, S., Hickman, M., Rehm, J., & Degenhardt, L. (2018). Global statistics on alcohol, tobacco and illicit drug use: 2017 status report. Addiction, 113(10), 1905-1926. https://doi.org/10.1111/add.14234

Ministry of Health of Malaysia. (2019). Malaysia Country Report on Drug Issues 2019. Alternative Development towards a Drug-Free ASEAN Community, 1-27.

Taguchi, G. (2001). Taguchi methods in LSI fabrication process. 6th International Workshop on Statistical Methodology, 1-6. https://doi.org/10.1109/IWSTM.2001.933815

Safeiee, F. L. M., & Abu, M. Y. (2020). Optimization using Mahalanobis-Taguchi System for inductor component. Journal of Physics: Conference Series, 1529, 1-7. https://doi.org/10.1088/1742-6596/1529/5/052045

Ghasemi, E., Aaghaie, A., & Cudney, E. A. (2015). Mahalanobis Taguchi system: a review. International Journal of Quality & Reliability Management, 32(3), 291-307. https://doi.org/10.1108/IJQRM-02-2014-0024

Taguchi, G., & Jugulum, R. (2002). The Mahalanobis-Taguchi Strategy: A Pattern Technology System. John Wiley and Sons, Inc. https://books.google.com.my/books?hl=en

Ohkubo, M., & Nagata, Y. (2019). Anomaly detection for unlabelled unit space using the Mahalanobis Taguchi system. Total Quality Management & Business Excellence, 1-15.

Chang, Z. P., Li, Y. W., & Fatima, N. (2019). A theoretical survey on Mahalanobis-Taguchi system. Measurement, 501-510. https://doi.org/10.1016/j.measurement.2018.12.090

Abu, M. Y., Nor, E. E. M., & Rahman, M. S. A. (2018). Costing improvement of remanufacturing crankshaft by integrating Mahalanobis-Taguchi System and Activity based Costing. IOP Conference Series: Materials Science and Engineering, 342, 1-10. https://doi.org/10.1088/1757-899X/342/1/012006

Wang, N., Zhipeng, W., Limin, J., Yong, Q., Xinan, C., & Zuo, Y. (2018). Adaptive Multiclass Mahalanobis Taguchi System for Bearing Fault Diagnosis under Variable Conditions. Sensors (Basel), 19(1), 1-16. https://doi.org/10.3390/s19010026

El-Banna, M. (2017). Modified Mahalanobis Taguchi System for Imbalance Data Classification. Computational Intelligence and Neuroscience, 1-15. https://doi.org/10.1155/2017/5874896

Mota-Gutiérrez, C. G., Reséndiz-Flores, E. O., & Reyes-Carlos, Y. I. (2018). Mahalanobis-Taguchi system: state of the art. International Journal of Quality & Reliability Management, 35(3), 596-613. https://doi.org/10.1108/IJQRM-10-2016-0174

Ohkubo, M., & Nagata, Y. (2019). Anomaly detection for unlabelled unit space using the Mahalanobis Taguchi system. Total Quality Management & Business Excellence, 1-15.

Fukuda, S. (2017). A Mahalanobis Taguchi Approach to Human Motion Control. Advances in Intelligent Systems and Computing, 65-71. https://doi.org/10.1007/978-3-319-60495-4_7

Res´endiz-Flores, E. O., & L´opez-Quintero, M. E. (2017). Optimal identification of impact variables in a welding process for automobile seats mechanism by MTS-GBPSO approach. Int J Adv Manuf Technol, 437–443. https://doi.org/10.1007/s00170-016-9395-5

Ketkar, M., & Vaidya, D. O. S. (2014). Evaluating and Ranking Candidates for MBA program: Mahalanobis Taguchi System Approach. Procedia Economics and Finance, 654 - 664. https://doi.org/10.1016/S2212-5671(14)00231-7

Shakya, P., Kulkarni, M. S. & Darpe, A. (2014). A novel methodology for online detection of bearing health status for naturally progressing defect. Journal of Sound and Vibration, 333(21), 5614-5629. https://doi.org/10.1016/j.jsv.2014.04.058

Liparas, D., Laskaris, N. & Angelis, L. (2013). Incorporating resting state dynamics in the analysis of encephalographic responses by means of the Mahalanobis–Taguchi strategy. Expert Systems with Applications, 40(7), 2621–2630. https://doi.org/10.1016/j.eswa.2012.11.014

Teshima, S., Hasegawa, Y., & Tatebayashi, K. (2012). Quality Recognition and Prediction: Smarter Pattern Technology with the Mahalanobis-Taguchi System. Momentum Press LLC, 1-220. ISBN 1606503421

Downloads

Published

2022-10-31

How to Cite

Zaini, S. N. A. M. ., Saad, S. K. M., & Abu, M. Y. (2022). Application of Mahalanobis-Taguchi System in Liver Function Profile of Methadone Flexi Dispensing Program. Journal of Applied Science &Amp; Process Engineering, 9(2), 1158–1176. https://doi.org/10.33736/jaspe.4283.2022