Title: Lean evaluation system of manufacturing enterprises based on full lifecycle

Authors: Le Yang; Guozhang Jiang; Zhongyuan Li; Gongfa Li; Chao Xu

Addresses: Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China; Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China ' Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China; 3D Printing and Intelligent Manufacturing Engineering Institute, Wuhan University of Science and Technology, Wuhan 430081, China ' Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China; 3D Printing and Intelligent Manufacturing Engineering Institute, Wuhan University of Science and Technology, Wuhan 430081, China ' Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China; Research Centre of Biologic Manipulator and Intelligent Measurement and Control, Wuhan University of Science and Technology, Wuhan 430081, China ' Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China

Abstract: The production of manufacturing enterprises is a complex process. Lean production is hard to achieve lean weight reduction. It is very important to propose a lean life assessment framework. This paper evaluates the lean production level of the whole life cycle of the company by using the fuzzy theory and the neural network technology, establishes a scientific and systematic framework of the lean evaluation index of the whole life cycle, and establishes the evaluation model of the fuzzy neural network. The example analysis shows that the actual output value of the fuzzy neural network model is not much different from the predicted output value, which indicates that the model has high-prediction accuracy. The experimental results further verify the reliability and validity of the model. The system framework can well plan and evaluate the whole lean production level. Accurate assessment of lean production level is an effective way to improve lean levels.

Keywords: whole life cycle; system architecture; fuzzy theory; neural network; evaluation system.

DOI: 10.1504/IJWMC.2019.102252

International Journal of Wireless and Mobile Computing, 2019 Vol.17 No.3, pp.285 - 292

Received: 14 Jan 2019
Accepted: 27 Apr 2019

Published online: 05 Sep 2019 *

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