A proposal on stability improvement of resource matching in crowdsourced manufacturing

Abstract

Recently, crowdsourced manufacturing concept highly attracts attention. In crowdsourced manufacturing, each participant shares its manufacturing resources to improve asset efficiency. To realize this concept, it is important how to make matching between resource requests and resource offers which achieve high efficiency improvement in fair way. Previously, some authors showed production efficiency improvement with some resource matching algorithms. But, accumulation of knowledge about the design of crowdsourced manufacturing is not sufficient currently. To support the design of crowdsourced manufacturing system, we previously proposed an evaluation method based on matching stability analysis for resource matching between resource requests and offers. The previous computational results showed that the system profit maximization policy made resource matching plans instable. In this research, we propose a balancing method between the system profit and the matching stability based on the 'nucleolus' concept in cooperative game theory. The proposed method reduces the maximum dissatisfaction of each resource request with procurement cost sharing. The computational experiments show that the proposed method improves resource matching stability with keeping system profit level in most cases. It cannot be generally stated how much the dissatisfaction with the resource request can be regarded as a virtually stable matching. So, it is important to evaluate property of crowdsourced manufacturing system with computational simulations and discuss politely among the participants before decision of the design of crowdsourced manufacturing system. In the future, we will examine resource matching methods from the viewpoint of the strategyproofness concept in market design theory, and evaluate them in various scenarios and in real manufacturing environment to clarify which situation is appropriate for crowdsourced manufacturing.