Self-organizing evaluation model and algorithm for manufacturing cloud services driven by user behavior

Abstract

Manufacturing cloud services represent a basic element of cloud manufacturing platforms and have expanded rapidly. However, effective methods to evaluate extensive manufacturing cloud services objectively are scarce, greatly limiting the efficiency and effectiveness of cloud manufacturing. We employ user behavior data to propose a self-organizing evaluation method for manufacturing cloud services in four respects, including mode, model, algorithm, and application. First, a self-organizing evaluation mode for manufacturing cloud services is proposed. Second, a self-organizing evaluation model and corresponding manufacturing cloud service and user behavior models are established by using the positive feedback principle and the mutually reinforcing relationship between manufacturing cloud services and users. On this basis, a self-organizing evaluation algorithm for manufacturing cloud services combined with the entropy value method is proposed to integrally evaluate manufacturing cloud services and users. Finally, a manufacturing cloud service evaluation system is developed, and experiments are conducted to verify the feasibility and effectiveness of the model and algorithm. The proposed evaluation method can effectively identify valuable services and professional users in a self-organizing and sustainable manner and can therefore promote the ordering and utilization of extensive manufacturing cloud services.