Journal of Quality Engineering and Management

Abstract Purpose: This research aims to identify and examine the relationship between the barriers to implementing Quality 4.0 in the Yazd tile and ceramic sector.
Methodology: A systematic review was employed to identify and categorize barriers, while the combined Fuzzy DEMATEL-ANP (FDANP) method was used in the quantitative phase to elucidate the relationships among these barriers and to prioritize them.
Findings: The qualitative analysis revealed 18 barriers across four categories. The Quantitative findings indicated that "High Cost of Implementation and lack of transparency in Return on Investment" emerged as the most causal barrier, while "failure to consider Quality 4.0 as a strategic issue and source of competitive advantage" was identified as the most consequential barrier to implementing Quality 4.0 in the Yazd tile and ceramic industry. Also, the key obstacles to the implementation of Quality 4.0 in the Yazd ceramic and tile industry include the lack of quantitative metrics for assessing the impact of Industry 4.0 on quality, the failure to consider Quality 4.0 as a strategic issue and a source of competitive advantage, the absence of advanced training programs for personnel, insufficient financial resources for implementing Quality 4.0, and the lack of stakeholder involvement in Quality 4.0 initiatives and projects.
Originality/Value: This study employs a hybrid Fuzzy DANP approach to support managers and decision-makers in strategizing for overcoming obstacles to the adoption of Quality 4.0. It achieves this by identifying barriers, determining their interrelationships, and prioritizing them.

Abstract The purpose of the current research is to design a structure so that it can be used to investigate the drivers of the appropriate implementation of quality 4.0 in the country's steel industry. In order to carry out this research, ten stimuli were initially identified using research literature. Then, using the interpretative structural modeling technique, these stimuli were structured using the opinions of 13 experts. , in order to fit the obtained structure, the structural equation modeling of the tools related to it, including measurement model fitting, structural and general model fitting, were used. For this purpose, a questionnaire containing 33 questions with a five-point Likert scale was designed and in order to complete it, opinions were sought from 214 managers and employees of the country's steel industry. The findings of the research on the high effectiveness of reward stimuli and control of big data in proper implementation have quality 4.0.