Evaluating innovative future robotic applications in manufacturing using a fuzzy collaborative intelligence approach

Ensuring the long-term competitiveness of a factory is a critical but challenging task. Robotic applications are an effective means to fulfill this task. These applications enable rapid, high-volume, and error-free production while avoiding danger and improving workers’ health. However, such applications are budget-intensive and can only support limited functionality in the factory. Despite more advanced sensors, computing, networking, and robotic technologies, innovative robotic applications in manufacturing have yet to be proposed. Making full use of limited resources and time requires establishing a systematic procedure to compare possible innovative robotic applications in manufacturing. Accordingly, a fuzzy collaborative intelligence (FCI) approach is proposed in this study. The proposed FCI approach enables experts to choose flexibly from six evaluation models according to their points of view. Fuzzy weighted intersection (FWI) is then applied to reasonably aggregate experts’ evaluation results. The proposed FCI approach was applied to a precision machining factory in Taichung, Taiwan, to evaluate and compare five innovative robotic applications in manufacturing. According to the experimental results, effectiveness was the most relevant criterion for innovative robotic applications. Furthermore, transferring machines from overcapacity to undercapacity factories under the guidance of an Internet of Machines (IoM) outperformed the other innovative robotic applications by 22%.