Forgetting curve models: A systematic review aimed at consolidating the main models and outlining possibilities for future research in production

Author:

Ferreira José Ângelo123ORCID,Valmorbida Edson Luiz123ORCID,Sato Bruno Goulart123,Fuentes Bruno Pontes123,Botti Renan123

Affiliation:

1. Department of Industrial Engineering Federal Technological University of Paraná Londrina Brazil

2. Department of Mathematics Federal Technological University of Paraná Londrina Brazil

3. Department of Mechanical Engineering Federal Technological University of Paraná Londrina Brazil

Abstract

AbstractThis research surveys current knowledge about forgetting curves and their application in production, aiming to identify the main characteristics and tendencies and research gaps on this topic. Faced with the need to improve tools that allow production planners to predict programmed batches with greater precision, it was found that there are still gaps to be filled that allow the application of learning and forgetting techniques in the production process. To compose the scope of this research, a systematization of the existing literature was carried out, using the keywords ‘forgetting curves’, ‘total forgetting’, ‘learning and forgetting curve’ and ‘forgetting effects’, in the databases of Science Direct, Scielo, Scopus, Web of Science and Google Academics, which allowed classifying and organizing the developed models into 3 groups: Deterministic models, Statistical models and Functional models. This systematic process consisted of selecting databases, filtering publications, reviewing information, and analysing models, providing a detailed analysis on a topic that, despite being promising, is poorly explored in the industry, demonstrating and indicating gaps in research and application. To be filled.

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Cited by 1 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

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