Cyber-physical systems have been widely adopted in a number of industries, including healthcare, critical infrastructure, and manufacturing. The connectivity of machines, which characterizes cyber-physical systems and provides many of their benefits, leaves them vulnerable to cyber-attacks. Within manufacturing, cyber-attacks can compromise end-use parts, resulting in catastrophic part failure. Researchers have recently started to investigate the vulnerabilities within connected additive manufacturing machines, demonstrating vulnerabilities and proposing mitigation strategies. While informative, findings from past work are limited by the physical machines used in experiments, making results difficult to generalize to other systems. Further, physical experiments take time, waste stock material, and may not be generalizable for other machines. The goal of this work is to provide a digital testbed for future research to characterize the vulnerabilities of manufacturing CPS and develop new methods to effectively identify compromised parts. This paper proposes and validates an inexpensive and accessible simulation to accurately predict the physical output of a fused deposition modeling additive manufacturing machine. This simulation allows for efficient testing of attack vectors and determine the probability of attack detection using quality control methods. This study lays the groundwork for future research exploring the vulnerabilities in engineering design processes as manufacturers become increasingly reliant on connected production equipment.

网络物理系统已在许多行业中广泛采用，包括医疗保健，关键基础设施和制造业。机器的连通性是网络物理系统的特征，并提供了许多优势，使它们容易受到网络攻击。在制造过程中，网络攻击可能会损害最终使用的零件，从而导致灾难性的零件故障。研究人员最近开始研究连接的增材制造机器中的漏洞，演示漏洞并提出缓解策略。尽管提供的信息丰富，但过去工作中的发现受到实验中使用的物理机器的限制，从而使结果难以推广到其他系统。此外，物理实验会花费时间，浪费库存材料，并且可能无法推广到其他机器。这项工作的目的是为将来的研究提供一个数字测试平台，以表征制造CPS的脆弱性，并开发新的方法来有效地识别受损部件。本文提出并验证了一种廉价且可访问的仿真，以准确预测熔融沉积建模增材制造机的物理输出。该仿真可以有效测试攻击向量，并使用质量控制方法确定攻击检测的可能性。这项研究为将来的研究奠定了基础，因为随着制造商越来越依赖于连接的生产设备，它们将探索工程设计过程中的漏洞。