Search

Since cooperation has been identified to be a key factor of future manufacturing firms' success, manufacturing concepts incorporating cooperation gained increasing interest within research and industry. However, the benefits from a financial standpoint have not yet been investigated thoroughly. Therefore, this paper investigates financial aspects of a resource-sharing platform where manufacturing companies can request resources (in case of shortage) or offer them (in case of surplus) through a central platform. In the first step, the additional costs and revenues are worked out in the context of a resource-sharing network. In the second step, a model is developed in order to evaluate and compare the additional costs (manufacturing, management, administrative, penalty, inventory and distribution costs) as well as the additional revenues (incomes) of a resource-sharing platform. Then, platform-based and direct exchange-based resource sharing algorithms are compared from the financial perspective. Finally, the model is validated and tested with experiments conducted using an agent-based simulation model. The findings (1) can be applied in the design and operation of such a platform, and (2) are helpful for companies who are considering this type of collaboration as a way to increase their competitiveness. [ABSTRACT FROM AUTHOR]

The operation of production facilities is shifting from centralized organizations towards decentralized networks. The paper investigates and compares alternative mechanisms for resource sharing in distributed manufacturing. Specifically, with the same underlying assumptions, a platform and a direct exchange-based model are presented and examined. The models have in common that resource assignment decisions are made ultimately by the autonomous facilities, also based on trust they maintain towards each other. Agent-based simulation is used to compare the two mechanisms with respect to utilization rate, service level and communication load. The findings can be applied in the design of crowdsourced manufacturing platforms. [ABSTRACT FROM AUTHOR]

In order to decrease the ecological impact and footprint of supply chain actors, a promising mechanism for sustainability in the industry is represented by sharing resources with each other in a mutualistic way. The paper aims at introducing a novel framework that facilitates the collaborative work of manufacturing facilities and helps participants dynamically and safely negotiate available capacities shared within the federation. The center of the framework is an open API cloud- and simulation-based platform which supports the strategic collaboration of federated companies while helping them optimize resource utilization, avoid shortages and minimize the environmental impact of their logistics. [ABSTRACT FROM AUTHOR]

Manufacturing has moved from local towards global economy in the past decades enabling new paradigms to come into practice, such as distributed manufacturing which aims at increasing companies' flexibility with a decentralized system consisting of autonomous entities. In the paper, a distributed collaboration framework of manufacturing agents is introduced, where the members with resource shortages can request resources from others, divide requests among multiple agents, reorganize their production to be able to complete a request and cancel an undertaken task if needed. In a collaboration framework, it is essential to have a commitment to the promises: if participants cannot count on these commitments, the framework's efficiency may decrease. So as to motivate agents to keep their promises and to enable differentiating between reliable and non-reliable partners, here agents consider trustfulness during the selection from resource offering agents' proposals and make decisions considering subjective trust and public reputation values, which are computed based on successfulness of task performing and meeting due dates. In the paper, the impact of the proposed mechanism is investigated with multi-agent simulation. It is shown that considering trustfulness improves the overall system performance; and the improvement depends on the number of participants and the federation's load. [ABSTRACT FROM AUTHOR]