A data-driven programming of the human-computer interactions for modeling a collaborative manufacturing system of hypoid gears by considering both geometric and physical performances. (June 2018)

• Record Type: Journal Article
• Authors: Ding, Han; Wan, Zhigang; Zhou, Yuansheng; Tang, Jinyuan
• Is Part Of: Robotics and computer-integrated manufacturing. Volume 51(2018)
• Page Start: 121
• Page End: 138
• Publication Date: 2018-06
• Subjects: Hypoid gears -- Collaborative manufacturing system -- Machine setting modification -- Human-compute interactions (HCIs) -- Data-driven programming; Robots, Industrial -- Periodicals; Computer integrated manufacturing systems -- Periodicals; Robotics -- Periodicals; Robots industriels -- Périodiques; Productique -- Périodiques; Robotique -- Périodiques; 670.285
• DOI: 10.1016/j.rcim.2017.10.003
• Languages: English
• ISSNs: 0736-5845

Abstract

Highlights: A complex manufacturing system for hypoid gear based on data-driven programming for the three main human-computer behaviors. Selection strategy about the optimal machine-tool setting and its high-order modification model considering residual ease-off. Data-driven programming for modification: high-order optimal machine setting modification with comprehensive consideration of tooth geometric and contact performances. Verification of the proposed data programming of human-computer behaviors in the hypoid manufacturing system. Abstract: Hypoid gears are widely used in transmission systems, which demands low noise and high strength for their hypoid gears. To meet those demands, it is significant to consider the geometric and physical performances of hypoid gears. To obtain the optimal performances, a collaborative manufacturing system of hypoid gears is composed of three interrelated processes: gear machining, measurement and modification. Since each of these three processes is complicated, the modeling of the collaborative manufacturing system is very difficult, especially when human-computer interaction (HCI) is needed in each process. To fulfill this problem, a data-driven programming for HCIs in the collaborative manufacturing system is proposed. For modeling each of those three processes, the data-driven programming is applied to describe the HCI in each process. Subsequently, the collaborative manufacturing system is modeled with full consideration of both geometric and physical performances. To solve this model, a Levenberg-Marquardt algorithm with a trust region strategy is employed to obtain a stable numerical solution. A numerical instance is given to show the validity of the proposed method.