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Tracking and decision of outsourcing service for auto parts

Published: 28 September 2021 Publication History

Abstract

In the process of integration of manufacture and service, an intelligent external processing service model for auto parts has been established through the analysis of the external processing business in the auto parts manufacturing industry. The model firstly uses the auto parts processing event to drive external processing tasks in the industrial Internet environment. Secondly, based on the process tracking graphical modeling method, it constructs the external processing service tracking time series unit and external processing service tracking time series flow, thereby realizing the multi-operation RFID process tracking of external processing service. Finally, the fuzzy comprehensive evaluation algorithm is used to determine the decision of external processing service. The application of specific examples demonstrates the feasibility and superiority of the tracking and decision-making mechanism of external processing service for auto parts.

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DSIT 2021: 2021 4th International Conference on Data Science and Information Technology
July 2021
481 pages
ISBN:9781450390248
DOI:10.1145/3478905
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 September 2021

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Author Tags

  1. Auto parts
  2. Manufacturing service
  3. Outsourcing processing
  4. Service decision
  5. Service tracking

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  • Research-article
  • Research
  • Refereed limited

Funding Sources

  • the National Social Science Foundation, China

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DSIT 2021

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Overall Acceptance Rate 114 of 277 submissions, 41%

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