Research On Estimation Of Manufacturing Grid Resources Based On Ranking Of Probabilities

Economic globalization has gradually made the competition of manufacturing sector evolveinto an all-round and multi-angle competition on global markets, technologies, resources, personneland so on. Manufacturing companies must make full use of the manufacturing resources that aredistributed around the globe and make responses to market demands quickly and efficiently.Therefore, manufacturing grid came into being under such circumstances, which applied advancedgrid technology to traditional manufacturing sector. Through manufacturing grid, the provider of themanufacturing resources rents the surplus manufacturing resources to the demand side; therefore,the supplier and the buyer of the resource shall make reasonable estimation on resource prices andnumbers to maximize their own interests before resources transaction. And in the process of priceand number estimation, the relevant factor affecting priceand number is that the future is uncertain,so the estimation to manufacturing resource prices and numbers should not only be a value but aprediction interval because the argument is uncertain. For such situation, this article proposes theresearch on estimation of manufacturing grid resources based on ranking of probabilities, andmakes analysis and finds the solution to predictive model of manufacture resource prices andnumbers under two constraints of weak ranking of probability and strict ranking of probabilities,and major works are as follows:（1）Analysis on resource trading process of manufacturing grid. On the basis of understandingthe concept, characteristics and architecture of manufacturing grid, the article analyzes the currentmainstream model of resource transaction under manufacturing grid, and describes the basic flow ofmanufacturing resources trading in manufacturing grid market, and notes the necessity of estimatingmanufacturing resource prices and numbers.（2）Estimation analysis of ranking of probability on manufacturing price and number undermanufacturing grid. After analyzing the factors affecting the price and number estimation,establishing the estimation model under two constraint conditions of weak ranking of probabilitiesand strict ranking of probabilities, describe the results range under the uncertain influential factorswith maximum expected value and minimum expected value, taking the variance as fluctuationsindicator of measure estimation, employing the methods of double targets estimation and usingexpected value and variance as and with two discrimination standards to build the estimationmethod of ranking of probabilities. （3）Case study of estimation model of manufacture resource price and number. Analyze andsolve the case of predictive model of manufacture resource prices and numbers under twoconstraints of weak ranking of probabilities and strict ranking of probabilities respectively, throughcase data, using related calculation software to get regression functions of grid and influentialfactors, and on such basis, calculate and discuss the extremes of the estimation value range of thefollowing price and number of the manufacturing resources under the two constraints and variance,proving the rationality of the model and superiority of its application.