A Multi-State Model for Reliability Analysis of Metal Sheet Manufacturing Process Using Artificial Neural Network Technique

Author:

Chandra Anil,Gupta Surbhi,Jaggi Chandra Kant

Abstract

A manufacturing system is governed by its various processes upon which its efficiency is dependent. Since failure results in considerable losses, many manufacturing systems have certain redundancies for some processes. These redundancies cause the system to work under different efficiency states called multi-state elements. In this paper, various processes of metal sheet manufacturing unit have been categorized as subsystems to determine the multi-state probabilities of its different efficiency states. Artificial Neural Network Technique (ANN) has been used to estimate the change in these multi-state probabilities over time. The ANN has also been used to estimate variation in upstate and downstate probabilities of the system for a particular-time period. The results have been used to determine variation in profit over time for the system.

Publisher

Universiti Putra Malaysia

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference32 articles.

1. Alyson, G. W., & Aparna, V. H. (2007). Bayesian networks for multilevel system reliability. Reliability Engineering and System Safety, 92, 1413-1420.

2. Angel, M. (2019). Global crude steel output increases by 4.6% in 2018. Retrieved March 30, 2020, from https://www.reuters.com/article/us-steel-output-global/global-crude-steel-output-jumps-46-percent-in2018-worldsteel-idUSKCN1PJ1MF

3. Barlow, R., & Wu, A. (1978). Coherent systems with multi-state components. Mathematics of Operations Research, 3(4), 275-281.

4. Bhargava, C., & Handa, M. (2018). An intelligent reliability assessment technique for bipolar junction transistor using artificial intelligence techniques. Pertanika Journal of Science and Technology, 26(4), 1765-1776.

5. Bhati, B. C. (2019). Steel: Long and flat productions. Retrieved March 31, 2020, from http://www.careratings.com/upload/NewsFiles/Studies/Long%20and%20Flat%20Steel%20Products%20Feb%202019.pdf

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Assessment of Reliability Factors in Glass Manufacturing plant Using Boolean Algebra and Neural network;2022 12th International Conference on Cloud Computing, Data Science & Engineering (Confluence);2022-01-27

2. Reliability Modelling and Analysis of an Industrial Bakery Plant Using Boolean Function Technique;Advances in Information Communication Technology and Computing;2022

3. Performance characteristics and assessment of fire alarm system;Materials Today: Proceedings;2021-11

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3