TY - JOUR
T1 - Research on the optimal combination and scheduling method of crowdsourcing members in a cloud design platform
AU - Chen, Jian
AU - Mo, Rong
AU - Chu, Jianjie
AU - Yu, Suihuai
AU - Fan, Jiashuang
AU - Cheng, Fangmin
N1 - Publisher Copyright:
© IMechE 2019.
PY - 2019/9/1
Y1 - 2019/9/1
N2 - 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.
AB - 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.
KW - Cloud design platform
KW - crowdsourcing service
KW - optimal combination
KW - optimal scheduling
KW - workflow simulation
UR - https://www.scopus.com/pages/publications/85068166393
U2 - 10.1177/0954405419855874
DO - 10.1177/0954405419855874
M3 - 文章
AN - SCOPUS:85068166393
SN - 0954-4054
VL - 233
SP - 2196
EP - 2209
JO - Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
JF - Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
IS - 11
ER -