A STUDY ON TOTAL QUALITY MANAGGEMENT IN INDIAN POLYMERS MANUFACTURING SECTOR

Abstract

Total Quality Management (TQM) is a rationale now widely accepted and practiced in most of manufacturing organizations as an organization-wide approach to improve quality, productivity, customer satisfaction and continuous improvement. ISO's quality-management principles, which consist of customer focus, leadership, engagement of people, process approach, improvement as a core objective and evidence-based decision-making Page 9, can serve as a conceptual framework for TQM (Garg et al. Empirical research has shown positive relationships between TQM practices and manufacturing or organizational performance in the Indian context but individual dimensions of TQM may have variable strength across organizational settings (Deshpande, 2019; Bhaskar, 2020). This study focuses on specifically the polymer manufacturing sector in India wherein raw materials consistency, process control, product quality and waste reduction and supplier performance are key operations aspects. Establishing and reviewing a relationship between basic TQM practices – management commitment, employee involvement, continuous improvement & supplier quality management and quality and operational performance has been the theme of the study. The proposed research design is quantitative, descriptive and analytical with primary data being collected from 300 respondents using structured questionnaire. The present study uses diagnostic measures of descriptive statistics and Pearson correlation analysis to analyze study variables using SPSS Statistics. It is found that all the four TQM practices have positive relationship with performance in the study findings continuous improvement is positively related with quality performance, whereas management commitment and more or less same associates quite strong. The research adds to TQM literature with evidence from a specific sector and offers practitioners in the Indian polymer manufacturing sector insights into decision making to achieve sustainable benefits. Future work may expand the framework by exploring dimensions of Industry 4.0, artificial intelligence, Green TQM, sustainability and automation and longitudinal performance implications.