Plug-in type work order auxiliary decision-making method and system based on artificial intelligence

Abstract

The invention provides a plug-in work order auxiliary decision-making method and system based on artificial intelligence, and belongs to the technical field of artificial intelligence. According to the invention, a plug-in work order assistant scheme is adopted to reduce the transformation cost of a work order processing system of an enterprise, and the existing systems and processes are reused tothe maximum extent; meanwhile, the front platform and the rear platform of the plug-in work order assistant are deployed in an enterprise internal network, data is obtained in a page monitoring and interface butt joint mode, the reading and writing of the whole database are avoided, and the safety of the data is improved; secondly, the functions of user problem classification, automatic work order distribution, work order portrait construction and priority calculation, work order information automatic query and display, intelligent decision of a solution, automatic backfilling of scheme information and the like are achieved through the artificial intelligence technology, and the intelligent degree of work order processing is improved; and finally, the modularized algorithm module supportsthe development and optimization of an algorithm model in a work order assistant, so that the modeling efficiency is improved, and the transformation and deployment cost caused by the algorithm optimization after the system is online is reduced.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence and relates to an artificial intelligence work order auxiliary decision-making method, in particular to an artificial intelligence-based plug-in work order auxiliary decision-making method and a system thereof. Background technique [0002] With the continuous expansion of enterprise scale and new business, the cost and efficiency of enterprise work order processing has become an important issue that enterprises need to consider and one of the bottlenecks restricting enterprise development. [0003] At present, the work order allocation of the work order processing system adopts the method formulated according to the business rules of the enterprise: through the matching relationship between the pre-configured problem type and the corresponding processing department, all work orders under a certain problem type are assigned to the work orders of the corresponding department or perso...

AI Technical Summary

Problems solved by technology

[0007]The existing work order allocation method does not consider the handling capacity of the work order personnel, and the work order priority setting is relatively rough, which cannot realize the differentiated processing of each work order , the user experience is relatively poor. When processing a work order, it is necessary to manually query multiple pages, resulting in low efficiency and increased pressure on the database. Afterwards, it is necessary to manually fill in solutions and processing opinions, etc. In order to solve the above technical problems, some smart work order products based on artificial intelligence technology have also been proposed to embed algorithm codes into corresponding function codes, but when optimization is required later , will involve the transformation and redeployment of the entire code base, and the transformation cost is relatively high; and if the existing work order system of the enterprise is replaced in the form of a complete set of solutions, the transformation cycle and cost are very large, and often the enterprise personnel are already familiar with it. It will take a relatively long period for the original work order processing system, process and method to adapt to the new system, and the subsequent upgrade also requires the cooperation of the supplier

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