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Industry 4.0 and Industrial Robots: A Study from the Perspective of Manufacturing Company Employees      
Yazarlar
Şemsettin Çiğdem
Gaziantep Üniversitesi, Türkiye
Ieva Meidute-Kavaliauskiene
Doç. Dr. Bülent YILDIZ Doç. Dr. Bülent YILDIZ
Kastamonu Üniversitesi, Türkiye
Özet
Background: Human–robot collaboration is essential for efficient manufacturing and logistics as robots are increasingly used. Using industrial robots as part of an automation system results in many competitive benefits, including improved quality, efficiency, productivity, and reduced waste and errors. When robots are used in production, human coworkers’ psychological factors can disrupt operations. This study aims to examine the effect of employees’ negative attitudes toward robots on their acceptance of robot technology in manufacturing workplaces. Methods: A survey was conducted with employees in manufacturing companies to collect data on their attitudes towards robots and their willingness to work with them. Data was collected from 499 factory workers in Istanbul using a convenience sampling method, which allowed for the measurement of variables and the analysis of their effects on each other. To analyze the data, structural equation modeling was used. Results: The results indicate that negative attitudes towards robots have a significant negative effect on the acceptance of robot technology in manufacturing workplaces. However, trust in robots was found to be a positive predictor of acceptance. Conclusions: These findings have important implications for manufacturing companies seeking to integrate robot technology into their operations. Addressing employees’ negative attitudes towards robots and building trust in robot technology can increase the acceptance of robots in manufacturing workplaces, leading to improved efficiency and productivity.
Anahtar Kelimeler
human–robot collaboration | industrial robots | intention to use | negative attitudes | trust
Makale Türü Özgün Makale
Makale Alt Türü ESCI dergilerinde yayımlanan tam makale
Dergi Adı LOGISTICS-BASEL
Dergi ISSN 2305-6290
Dergi Tarandığı Indeksler SCOPUS, ESCI
Makale Dili İngilizce
Basım Tarihi 03-2023
Cilt No 7
Sayı 1
Sayfalar 1 / 18
Doi Numarası 10.3390/logistics7010017
Makale Linki https://www.mdpi.com/journal/logistics