Research On Adaptive Adjustment For Service Composition In Cloud Manufacturing

As the foothold of global economic growth returns to the manufacturing and real economy,in order to get a better position in the market competition,the transformation and upgrade of manufacturing industry is imminent.Thanks to the development of cloud computing and the Internet of Things(LoT),a new networked manufacturing mode called cloud manufacturing(CMfg)appeared,enterprise users can trade and share the discrete manufacturing resources or their capacity through the cloud manufacturing platform in an efficient and high-quality collaborative way.The manufacturing service composition in CMfg is a key technology to satisfy the user's personalized manufacturing requirement and realize the optimal allocation of manufacturing resources,and as a hot issue of CMfg research,many experts and scholars were attracted to study it.However,the issue of dynamic scheduling in the implementation phase of the manufacturing service composition is relatively few,but this issue is very important to the "landing" of the CMfg mode.Therefore,this paper studied the adaptive Adjustment of cloud manufacturing service composition in the implementation phase.Firstly,the construction process of cloud manufacturing service composition was analyzed.In order to get a better understanding of the operation mechanism of cloud manufacturing service composition,this paper elaborated on the service composition from the aspects of the decomposition of cloud manufacturing task,the matching of manufacturing resource service and manufacturing task,and the election of the optimal service composition.In this part,the meta-manufacturing task(mmt)model,the meta-manufacturing capability(mmc)model and the matching model of mmt and mmc were established according to the characteristics of the machining industry.Because the optimization of cloud manufacturing service composition is a very complicated problem,only the method of studying it was analyzed in this part.Secondly,an adaptive adjustment framework for cloud manufacturing service composition was established.This paper took the exception of cloud manufacturing service as the research cut-in point of the adaptive adjustment of cloud manufacturing service composition,and chose the anomaly of cloud manufacturing service as the research object.The adaptive adjustment framework of cloud manufacturing service composition was consisted of the service exception discovery stage,the service exception analysis stage and the adjustment strategy stage,and the content of each process stage were expounded in this paper in detail.Then,the adaptive adjustment method of cloud manufacturing service composition was studied.Based on the existing adaptive adjustment framework of cloud manufacturing service composition,this paper mainly studied the adaptive Adjustment method on general strategy of service replacement.The adjustment method took the improved ant colony algorithm as the core algorithm,combined with the incremental adjustment mode of single service substitution and multiple services simultaneous substitution.The effectiveness of the adjusting method was validated through a simulation experiment.An algorithm comparison experiment with the particle swarm algorithm and the artificial colony algorithm was performed to validate the superiority of the improved ant colony algorithm.Finally,a prototype of cloud manufacturing platform developed by the author's laboratory group was introduced.Based on the theoretical research work in this paper,the corresponding part of the function was developed and implemented on the proto-platform.