24 فروردین 1403
غلامرضا جمالي

غلامرضا جمالی

مرتبه علمی: دانشیار
نشانی: دانشکده کسب و کار و اقتصاد - گروه مدیریت صنعتی
تحصیلات: دکترای تخصصی / مدیریت صنعتی، گرایش تولید و عملیات- دانشگاه تهران
تلفن: 31222123
دانشکده: دانشکده کسب و کار و اقتصاد

مشخصات پژوهش

عنوان
Analysis and Prioritization of Quality 4.0 dimensions and companies' readiness to adapt to industry 4.0 evolutions through Bayesian Best -Worst method
نوع پژوهش مقالات در همایش ها
کلیدواژه‌ها
Quality 4.0, Quality 4.0 Management, Change Management, Quality 4.0 Organizational Dimensions, Bayesian Best-Worst Method
پژوهشگران هادی بالوئی جام خانه (نفر اول) ، رضا جلالی (نفر دوم) ، رضا شاهین (نفر سوم) ، روی لیما (نفر چهارم) ، احسان رسولی (نفر پنجم) ، غلامرضا جمالی (نفر ششم به بعد)

چکیده

Introduction: The evolutions of the Fourth Industrial Revolution helped many companies and organizations to survive, achieving economic success and ensuring competitiveness, and has put them under pressure to align their goals, policies, strategies, and the nature of their operations with these changes. Therefore, the concept of quality and the nature of its operations to meet customers' needs in the digital era must be changed and updated in accordance with these developments. Quality 4.0 facilitates coordination between quality management and industry 4.0. A review of the literature shows that the concepts and perspectives of quality 4.0 have not yet evolved and matured, and therefore there is little research on the alignment of quality 4.0 management with industry 4.0 technologies. Purpose: The main purpose of this study is to identify and evaluate quality 4.0 indicators to draw a roadmap for organizations to align quality 4.0 management with industry 4.0 technologies. Methodology: To achieve the goal, first the literature of quality 4.0, quality 4.0 management as well as industry 4.0 technologies were studied to gain a broad understanding of the subject. Then the dimensions and quality 4.0 indicators that are potentially affected by the implementation of Industry 4.0 are identified. Next, the importance and prioritization of dimensions and quality 4.0 indicators for alignment with Industry 4.0 using the Bayesian Best-Worst method are determined. Findings: The research findings identify the dimensions and quality 4.0 indicators in different classes and then prioritize each of the indicators according to their importance in aligning quality 4.0 management with industry 4.0 technologies. Conclusion: The results of this study help to facilitate the process of change management towards quality 4.0 in companies and outline a roadmap for companies to prioritize the nature of their operations with these changes and developments and the need for revision and provides inv