Auto-DSM: Using a Large Language Model to generate a Design Structure Matrix

Edwin C.Y. Koh
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Abstract

The Design Structure Matrix (DSM) is an established method used in dependency modelling, especially in the design of complex engineering systems. The generation of DSM is traditionally carried out through manual means and can involve interviewing experts to elicit critical system elements and the relationships between them. Such manual approaches can be time-consuming and costly. This paper presents a workflow that uses a Large Language Model (LLM) to support the generation of DSM and improve productivity. A prototype of the workflow was developed in this work and applied on a diesel engine DSM published previously. It was found that the prototype could reproduce 357 out of 462 DSM entries published (i.e. 77.3%), suggesting that the work can aid DSM generation. A no-code version of the prototype is made available online to support future research.

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Auto-DSM:使用大型语言模型生成设计结构矩阵
设计结构矩阵(DSM)是一种用于依赖关系建模的成熟方法,尤其是在复杂工程系统的设计中。传统上,设计结构矩阵是通过人工方式生成的,可能需要与专家面谈,以了解关键的系统元素及其之间的关系。这种人工方法既费时又费钱。本文介绍了一种使用大型语言模型(LLM)来支持 DSM 生成并提高生产率的工作流程。在这项工作中开发了工作流程的原型,并将其应用于之前发布的柴油发动机 DSM。结果发现,在已发布的 462 个 DSM 条目中,原型可重现 357 个(即 77.3%),这表明该工作可帮助生成 DSM。该原型的无代码版本可在线获取,以支持未来的研究。
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