Cloud manufacturing workshop operation uncertainty processing time model and estimation method

Abstract

The invention discloses a cloud manufacturing workshop operation time uncertainty model and estimation method, and the method comprises the steps of dividing the cloud manufacturing workshop operation time into a machining time part and a non-machining time part based on the coexistence of randomness and uncertainty in a cloud manufacturing scheduling decision actual operation environment; performing the workshop operation time modeling based on the uncertain random variables, and using the random variables, the uncertain variables and the convertible relationship among the uncertain random variables to comprehensively describe different types of workshop operation time factors, so that the applicability and the accuracy of the workshop operation time are improved. According to the invention, the characteristic that local data errors can be prevented from being propagated and amplified from a distance by using quadratic spline function interpolation is utilized, and the opportunity distribution of workshop operation time is simulated, so that more accurate workshop operation time on different confidence levels are obtained, and support is provided for the stability and reliability of a cloud manufacturing scheduling scheme.

Description

technical field [0001] The invention belongs to the technical field of cloud manufacturing scheduling optimization, and specifically relates to a cloud manufacturing operation uncertain processing time model and evaluation method, which are used to provide support for cloud manufacturing scheduling optimization. Background technique [0002] The globalization of manufacturing services poses new challenges to manufacturing companies. How to break through the shackles of geographical regions on business scope and manufacturing models, and to meet the demand for low-cost, high-quality, and high-efficiency products through large-scale collaborative manufacturing has become an urgent need for manufacturing companies. solved problem. As a new service-oriented networked manufacturing model, cloud manufacturing provides a new solution for manufacturing enterprises. It uses cloud computing, big data, Internet of Things, artificial intelligence and other advanced information technolo...

AI Technical Summary

Problems solved by technology

Due to the distribution, heterogeneity, dynamics, and autonomy of the cloud manufacturing system itself, the processing time of the job is affected by many factors and has great uncertainty.

The existing methods for describing job processing time can be divided into two categories, one is to model job processing time with precise time, which lacks full consideration of the uncertain environment of cloud manufacturing; the other is mostly through random variables or fuzzy It is difficult to fully characterize the characteristics of job processing time by modeling the job processing time

Therefore, the existing cloud manufacturing scheduling scheme needs to be revised frequently in the actual operating environment, which lacks reference value

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