Research on the optimal combination and scheduling method of crowdsourcing members in a cloud design platform. (September 2019)

• Record Type: Journal Article
• Authors: Chen, Jian; Mo, Rong; Chu, Jianjie; Yu, Suihuai; Fan, Jiashuang; Cheng, Fangmin
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 233:Number 11(2019)
• Page Start: 2196
• Page End: 2209
• Publication Date: 2019-09
• Subjects: Cloud design platform -- crowdsourcing service -- optimal combination -- optimal scheduling -- workflow simulation; Mechanical engineering -- Periodicals; Engineering -- Management -- Periodicals; Manufacturing processes -- Periodicals; 629.8
• DOI: 10.1177/0954405419855874
• Languages: English
• ISSNs: 0954-4054

Abstract

Cloud design has become a potential emerging design service mode. More and more design service providers are clustered in a cloud design platform to become crowdsourcing members. Collaborative tasks published by the platform are usually performed by several crowdsourcing members, and the collaborative mode of crowdsourcing members is an asynchronous collaborative working mode. However, due to the variety of crowdsourcing members in terms of ability, time, and so on, how to combine crowdsourcing members into a rational crowdsourcing team has become a challenge. At the same time, due to the looseness and uncertainty of their collaborative mode, there is no effective guidance mechanism in the cooperation process. Therefore, we propose a method of crowdsourcing the optimal combination and scheduling of members. By evaluating the comprehensive abilities of crowdsourcing members, the method optimizes the selection of suitable crowdsourcing members for each subtask and combines them into a crowdsourcing team. At the same time, besides establishing a collaborative workflow simulation model to plan the timing of subtasks and the workflow of crowdsourcing members, the method also optimizes and schedules crowdsourcing members to process different subtasks in turn. Finally, in the case of the collaborative design task of a medical analgesia pump, this method is used to establish a rational crowdsourcing team for collaborative tasks and effectively plan the collaborative work process of crowdsourcing members. The results demonstrate that the proposed method is feasible and effective.