设计方法学最新报告

S. O. Erikstad, B. Lagemann
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引用次数: 0

摘要

船舶系统设计方法不断发展。在战略层面上,我们已经看到了经典设计螺旋中顺序迭代过程中出现的四条主要进化轨迹。一种是基于模型的系统工程方法,它通过从需求到功能的结构化映射,并进一步形成最终合成为完整设计的元素,来消除迭代。另一种是基于集合的策略,即生成并分析大量设计,从中选择一个或几个解决方案进行进一步开发。第三个方向是整体优化策略,将螺旋模型中的主要步骤集成到一个公共平台上,从而能够自动识别一个或几个平衡的优选解决方案。最后,在典型的按订单设计的行业中,作为通过标准化提高竞争力的策略,我们已经看到模块化架构与基于配置的设计方法相结合的出现。在这四条进化轨迹中,在不同的成熟度水平上有几个更集中的发展。这包括可持续性设计、操作模拟、处理不确定性和变化的灵活性设计,以及风力辅助船舶的设计。最后,我们指出了一些新兴的发展,我们发现它们很有前景,但尚未成熟,无法对行业级应用程序产生重大影响。这包括人工智能和机器学习、扩展系统边界和数字孪生技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design Methodology State-of-the-Art Report
Marine systems design methodology is continuously evolving. On a strategic level, we have seen four major evolutionary tracks emerging from the sequential, iterative process captured in the classical design spiral. One is a model-based systems engineering approach that removes iterations by a structured mapping from needs to functions, and further to form elements that are finally synthesized into a complete design. Another is a set-based strategy, where a large number of designs are generated and analysed, from which one or a few solutions are selected for further development. A third direction is a holistic optimization strategy where the major steps in the spiral model are integrated onto a common platform that enables the automatic identification of one or a few balanced, preferable solutions. Finally, as a strategy towards improved competitiveness through standardization in a typical engineered-to-order industry, we have seen the emergence of modular architectures combined with configuration-based design methods. Across these four evolutionary tracks there have been several more focused developments on different levels of maturity. This includes design-for-sustainability, simulation of operations, design-for-flexibility to handle uncertainty and change, and design of wind-assisted vessels. Finally, we have pointed to some emerging developments that we find promising but have yet to mature into having a significant impact on industry level applications. This includes artificial intelligence and machine learning, extended system boundaries, and digital twin technologies.
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