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Machine Learning in Production Planning and Control: A Review of Empirical Literature

Year: 2019

Type: article

Abstract: Proper Production Planning and Control (PPC) is capital to have an edge over competitors, reduce costs and respect delivery dates. With regard to PPC, Machine Learning (ML) provides new opportunities to make intelligent decisions based on data. Therefore, this paper provides an initial systematic review of publications on ML applied in PPC. The research objective of this study is to identify standard activities as well as techniques to apply ML in PPC. Additionally, the commonly used data sources in literature to implement a ML-aided PPC are identified. Finally, results are analyzed and gaps leading to further research are highlighted.

Source: IFAC-PapersOnLine

DOI: 10.1016/j.ifacol.2019.11.155

Authors: Juan Pablo Usuga Cadavid, Samir Lamouri, Bernard Grabot, Arnaud Fortin

Institutions: Arts et Métiers, Laboratoire d'Automatique, de Mécanique et d'Informatique Industrielles et Humaines, École Nationale d'Ingénieurs de Tarbes, Laboratoire Génie de Production

Language: English

Topic: Impact of AI and Big Data on Business and Society

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W2996946531

FWCI: 2.685

Cites: 27

Cited by: 36

Related to: 10