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.

尽管制造技术发展迅速，但注射成型仍广泛用于制造具有复杂几何形状和精确尺寸的塑料零件。由于注模中不可避免地会出现故障，因此需要进行工艺优化。人工智能（AI）方法已成功用于科学和技术的不同分支中的优化。在本文中，我们回顾了一种基于案例推理（CBR）的方法在注塑成型中的应用。CBR是一种用于知识表示和操纵的AI方法，它考虑了过去问题的成功解决方案，这些解决方案很可能充当给定问题的候选解决方案。该方法在学术和工业应用中越来越多地被使用。这里，我们将回顾用于注塑成型的CBR系统的不同目的，例如过程设计，工艺参数，故障诊断和质量控制的增强。此外，我们讨论了在注塑成型不同阶段使用CBR的趋势。还讨论了与将CBR应用于注塑成型相关的最重大挑战。最后，通过考虑一些开放研究领域和未来前景来结束本综述。