Injection molding manufacturing process: review of case-based reasoning applications

Mohammad Reza Khosravani () and Sara Nasiri
Additional contact information
Mohammad Reza Khosravani: University of Siegen
Sara Nasiri: University of Siegen

Journal of Intelligent Manufacturing, 2020, vol. 31, issue 4, No 4, 847-864

Abstract: Abstract Although manufacturing technology has been developing rapidly, injection molding is still widely used for fabricating plastic parts with complex geometries and precise dimensions. Since the occurrence of faults in injection molding is inevitable, process optimization is desirable. Artificial intelligence (AI) methods are being successfully used for optimization in different branches of science and technology. In this paper, we review the application of one such method, case-based reasoning (CBR), to injection molding. CBR is an AI approach for knowledge representation and manipulation which considers successful solutions of past problems that are likely to serve as candidate solutions for a given problem. This method is being used increasingly in academic and industrial applications. Here, we review CBR systems that are used in injection molding for different purposes, such as process design, processing parameters, fault diagnose, and enhancement of quality control. In addition, we discuss trends for utilization of CBR in different phases of injection molding. The most significant challenges associated with application of CBR to injection molding are also discussed. Finally, the review is concluded by contemplating on some open research areas and future prospects.

Keywords: Injection molding; Case-based reasoning; Manufacturing process; Artificial intelligence; Fault detection (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://link.springer.com/10.1007/s10845-019-01481-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joinma:v:31:y:2020:i:4:d:10.1007_s10845-019-01481-0

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845

DOI: 10.1007/s10845-019-01481-0

Access Statistics for this article

Journal of Intelligent Manufacturing is currently edited by Andrew Kusiak

More articles in Journal of Intelligent Manufacturing from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().