Modeling and Analysis for Inherent Energy Efficiency of Two-machine Bernoulli Serial Lines

Longyao Xu*, Peiji Liu, Xu Wang, Fangyuan Yu, Chao Liu

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference publication

Abstract

In recent years, the topic of balancing the energy efficiency of production systems with production performance parameters such as productivity and buffer capacity has received increasing attention. However, the existing research generally focuses on the operational energy efficiency of the production system, which may changes with various workpieces and make it difficult to support the formation and optimization of high-efficiency production lines. For this reason, we firstly propose the inherent energy efficiency of production systems to describe the common characteristics of the operational energy efficiency that do not vary with workpiece changes when production systems machining various possible future workpieces. Secondly, the specific inherent energy efficiency model which based on the unreliability of the production unit and the limited capacity of the product buffer of the Bernoulli two-machine serial production system has been established. Then a mathematical analysis method oriented to the optimal solution for the production line buffer capacity and the inherent energy efficiency has been proposed. Finally, numerical analysis is used to verify that the models and methods proposed in this paper are instructive for energy-efficient design and upgrading of production systems.

Original languageEnglish
Title of host publication2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)
PublisherIEEE
Pages2961-2966
Number of pages6
ISBN (Electronic)9798350358513
DOIs
Publication statusE-pub ahead of print - 23 Oct 2024
Event20th IEEE International Conference on Automation Science and Engineering, CASE 2024 - Bari, Italy
Duration: 28 Aug 20241 Sept 2024

Publication series

NameIEEE International Conference on Automation Science and Engineering
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference20th IEEE International Conference on Automation Science and Engineering, CASE 2024
Country/TerritoryItaly
CityBari
Period28/08/241/09/24

Bibliographical note

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