Decision Model and Industry Optimization in Production: A Systematic Literature review

  • Armando Tirta Dwilaga Universitas Gunadarma
Keywords: Decision Models and Optimization, Production, Systematic Literature review, PRISMA

Abstract

This article aims to discover the modeling and optimization options relevant to production-related industrial sectors. PRISMA (Preferred Reporting Items for Systematic Review and Meta-analyses) is a preferred submission method with inclusive and exclusive criteria, one of the bases for the selection made from the ScienceDirect index database only for 2018, 2019, 2020, 2021, and 2022 is understanding decision models and optimization with production keywords. As a result, 823 articles were converted to 100 articles and 16 articles adjacent to the final selection of 10 articles were used. The detailed results of the list of journals used as the most common references from the journal Computers & Industrial Engineering are used to identify the results of this publication in more detail. The most common research model is the adaptive decision model, and the most common research methodology is quantitative. Advanced research with sophisticated applications from the latest technologies such as AI (Machine Learning) to (Deep Learning), this wider and varied use of data includes unstructured or unorganized data so that new concepts will lead to new decision model system innovations, still relatively little additional research that can be used in the realm of production in assembly, process quality, and the environment.

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Published
2023-03-26
How to Cite
Dwilaga, A. (2023). Decision Model and Industry Optimization in Production: A Systematic Literature review. Sainteks: Jurnal Sain Dan Teknik, 5(1), 57-71. https://doi.org/https://doi.org/10.37577/sainteks.v5i1.528
Section
Articles