Total Quality Management in Higher Technical Education
RS Mishra1, Anshuman Pandey2, Aryan Rana3, Aakash Mehta4
1Prof. RS Mishra, Department of Mechanical Engineering, Delhi Technological University, Delhi, India.
2Anshuman Pandey, Department of Mechanical Engineering, Delhi Technological University, Delhi, India.
3Aryan Rana, Department of Mechanical Engineering, Delhi Technological University, Delhi, India.
4Aakash Mehta, Department of Mechanical Engineering, Delhi Technological University, Delhi, India.
Manuscript received on 11 May 2023 | Revised Manuscript received on 24 May 2023 | Manuscript Accepted on 15 June 2023 | Manuscript published on 30 June 2023 | PP: 29-39 | Volume-12 Issue-7, June 2023 | Retrieval Number: 100.1/ijitee.G95930612723 | DOI: 10.35940/ijitee.G9593.0612723
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The paper determines the behavior of Indian Technical Educational through the Total quality management tools and techniques, in this we tend to find the research gaps by reviewing some already existing research papers, and giving the solution through the analytical process of data analysis, we will majorly focus on the higher educational institutions. we will review the methodology that is currently being used by universities and how can they come at par as compared to the foreign universities. The reviewed papers will be used to find the shortcomings of the research and will be taken into consideration of analyzing it. Then we will be doing the quantitative data analysis of some collected data from google form and internet sources regarding the six TQM factors that influence the enrolment and hence the quality of institutions and determining the hypothesis result, then we will discuss the results and shortcomings of the analysis and will bridge those shortcomings by providing various possible solutions in that regards. In the whole process we have used data gathering, analyzing it and hence giving the solution. We have basically used IBM SPSS AND AMOS software to construct TQM models and their covariance relations. Now the future aspect of this paper is confirmed that the same procedure can be adopted to any industry for analyzing the quality of that organization.
Keywords: Total Quality Management, Technical Institutions, AMOS & SPSS.
Scope of the Article: Artificial Intelligence