References
References:
1. Shewhart, W.A. (1926), Quality Control Charts, Bell System Technical Journal, Vol 5, Issue 4, Pages 593-603.
2. W.A. Shewhart (2012), The Application of Statistics as an Aid in Maintaining Quality of a Manufactured Product, American Statistical Association, pages 546-548.
3. Zichang He & Wen Jiang (2017): A New Belief Markov Chain model and Its Application in Inventory Prediction, International Journal of Production Research, DOI: 10.1080/ 002075 43.2017.1405166
4. Jong Min Kim (2021): Deep Learning- Based Residual Control Chart for Binary Response, New Advances and Applications in Statistical Quality Control, 13(8), 1389.
5. Wei- Heng Huang(2021): Control Charts for Joint Monitoring of the Lognormal Mean and Applications in Statistical Quality Control, 13(4), 549.
6. Muhammad Muazzem Hossain (2010): The Development and Research Tradition of Statistical Quality Control, International Journal of Productivity and Quality Management 5(1) DOI:10.1504/IJPQM.2010. 029505.
7. Michael Stuart, Eamonn Mullins, Eileen Drew (1996): Statistical Quality Control and Improvement European Journal of Operational Research, Vol 88, Issue 2, Pages 203-204
8. Terna Godfrey Leren; Samson Kuje; Abraham Lorkaa Asongo; Innocent Boyle Eraikhuemen(2020): Application of Statistical Quality Control in Monitoring the Production, Packaging and marketing process of Sachet water, Journal of Scientific Research and Reports, page 32-45
9. Saniga, E.M.(1993): Decision Support and Statistical Quality Control, International Journal of Quality & Reliability Management, Vol.10 No.2.
10. C.E.Okorie (2015): Markov Chain Models in Discrete Time Space and Application to Personnel Management, Journal for studies in management and planning, Vol 50, Issue 8, page 1314-1329
11. Damjan Skulj (2009): Discrete Time Markov Chain with interval probabilities, International Journal of Approximate Reasoning, Vol 50, Issue 8, Pages 1314-1329.
12. Jiawei Yang, Qiangyi sha (2011): Research and Application by Markov Chain Operators in the mobile phone market, 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce.
13. Lamiae Douiri(2016): Models for Optimization of Supply Chain Network Design Integrating the cost of Quality: A Literature Review, American Journal of Industrial and Business Management, Vol.6 No.8
14. Jiju Antony, Michael Sony(2021), A Study on the Ishikawa’s Original basic tools of Quality in South American Companies: Results from a pilot survey and directions for further Research, The TQM Journal, ISSN: 1754-2731.
15. Samwel Manyele, Nyakorema Rioba (2016), Monitoring Saccharification Process in Brewery Industry using Quality Control Charts, Engineering, Vol.8 No.7
16. Leakemariam Berhe, Tesfay Gidey(2016) Assessing the Awareness and Usage of Quality Control tools with Emphasis to Statistical Process Control in Ethiopian manufacturing Industries, Intelligent Information Management, Vol.8 No.6
17. Preethi, E, Arumugam, R, Applications of Stochastic Models in Web Pageranking, 2017, International Journal of Recent Trends in Engineering and Research (IJRTER), Volume 3, Issue 3, pp. 245-252.
18. Dr.R.Arumugam, C.Gowri, M.Rajathi (2019), A statistical look at on the Impact of Dengue fever in Thanjavur District the usage of SPSS, Compliance Engineering, Vol. 10, Issue. 12, pp. 671-683.
19. Dr.R.Arumugam, B.Sri Ranjani, M.Rajathi (2019), A statistical study on the Production of Crops before and after Gaja cyclone in the delta region around Thanjavur District, Compliance Engineering, Vol. 10, Issue. 12, pp. 598-607.
20. M.Rajathi, R.Arumugam (2019), Applications of Mobile learning in the higher educational institutions through Statistical approach, International Journal of Recent Technology and Engineering (IJRTE), Vol. 8, Issue. 1, pp-1431-1439.
21. Dr.R.Arumugam and M. Rajathi, “A Markov Model for Prediction of Corona Virus
COVID-19 in India- A Statistical Study”, Journal of Xidian University, Vol. 14,
Issue. 4, pp-1422-1426.
22. Dr.R.Arumugam and M. Rajathi, “Applications of Manpower with various stages in Business using stochastic models”, International Journal of Recent Trends in Engineering and Research, Vol. 3, Issue. 1, pp-95-100.