The Exploration of Integrating the Midjourney Artificial Intelligence Generated Content Tool into Design Systems to Direct Designers towards Future-Oriented Innovation
将中途人工智能生成内容工具整合到设计系统中，引导设计师朝着面向未来的创新方向探索

Abstract 摘要

In an age where computing capabilities are expanding at a breathtaking pace, the advent of Artificial Intelligence-Generated Content (AIGC) technology presents unprecedented opportunities and challenges to the future of design. It is crucial for designers to investigate how to utilize this powerful tool to facilitate innovation effectively. As AIGC technology evolves, it will inevitably shift the expectations of designers, compelling them to delve deeper into the essence of design creativity, transcending traditional sketching or modeling skills. This study provides valuable insights for designers on leveraging AIGC for forward-thinking design innovation. We focus on the representative AIGC tool, “Midjourney”, to explore its integration into design systems for collaborative innovation among content creators. We introduce an AIGC-based Midjourney path for product design and present a supporting tool card set: AMP-Cards. To confirm their utility, we undertook extensive validation through advanced prototype design research, task-specific project practices, and interdisciplinary collaborative seminars. Our findings indicate that AIGC can considerably enhance designers’ efficiency during product development, especially in the “explorative product shape” phase. The technology excels in identifying design styles and quickly producing varied design solutions. Moreover, AIGC’s capacity to swiftly translate creators’ concepts into visual forms greatly aids in multidisciplinary team communication and innovation.
在计算能力迅猛扩张的时代，人工智能生成内容（AIGC）技术的出现为设计的未来带来了前所未有的机遇和挑战。对设计师来说，研究如何有效利用这一强大工具以促进创新至关重要。随着 AIGC 技术的发展，它必然会改变设计师的期望，迫使他们深入探讨设计创意的本质，超越传统的素描或建模技能。本研究为设计师提供了关于如何利用 AIGC 进行前瞻性设计创新的宝贵见解。我们关注代表性的 AIGC 工具“Midjourney”，探讨其如何融入设计系统以促进内容创作者之间的协作创新。我们介绍了基于 AIGC 的 Midjourney 产品设计路径，并提出了一个支持工具卡片套装：AMP-Cards。为了确认它们的实用性，我们通过先进的原型设计研究、任务特定项目实践和跨学科协作研讨会进行了广泛验证。 我们的研究结果表明，AIGC 可以显著提高设计师在产品开发过程中的效率，特别是在“探索性产品形状”阶段。该技术在识别设计风格和快速生成多样化设计方案方面表现出色。此外，AIGC 快速将创作者的概念转化为视觉形式的能力极大地促进了跨学科团队的沟通和创新。

1. Introduction 1. 引言

In the burgeoning realm of Artificial Intelligence Generated Content (AIGC), we are witnessing a technological evolution that transcends the traditional production limitations of designers, paving the way for unparalleled capabilities in limitless content generation. Currently, the applications of AIGC extend from media and education to entertainment, marketing, and scientific research, highlighting the technology’s potential to provide users with high-quality, efficient, and personalized content services [1]. The progress in AIGC is set to reshape the working methods of designers and influence collaboration modes in the design industry. Several artificial intelligence (AI) tools are increasingly impacting the design arena. For instance, the ChatGPT chatbot can engage in logical conversations and produce self-initiated copywriting, novels, scripts, and essays, thus enhancing human–computer interaction [2,3,4,5,6]. Another example is the Stable Diffusion AI painting model, which obtained several prizes at international art competitions for the works it has created [7]. Midjourney, rooted in the Stable Diffusion AI painting paradigm, is a text-driven image generation tool. With just a textual prompt, it can generate the corresponding image in approximately one minute. Midjourney harnesses the synergistic collaboration between human intuition and machine intelligence, empowering both specialized content creators and the broader audience to envision and craft beyond the traditional confines of “technology” and “efficiency” [3,8]. The recent iteration, Midjourney 5.2, introduces features such as object locking, partial redrawing, and drawing style selection, broadening its applicability across various domains, including product design, animation, gaming, and fashion. Furthermore, it consistently delivers images of leading quality and creativity [3].
在人工智能生成内容（AIGC）蓬勃发展的领域中，我们正在见证一种技术进化，超越了设计师传统生产的限制，为无限内容生成开辟了前所未有的能力。目前，AIGC 的应用范围从媒体和教育延伸到娱乐、营销和科学研究，突显了这项技术为用户提供高质量、高效和个性化内容服务的潜力。AIGC 的进展将重塑设计师的工作方法，并影响设计行业的合作模式。一些人工智能（AI）工具正日益影响设计领域。例如，ChatGPT 聊天机器人可以进行逻辑对话，并生成自发的文案、小说、剧本和论文，从而增强人机交互。另一个例子是稳定扩散 AI 绘画模型，在国际艺术比赛中获得了多个奖项，因其创作的作品而备受赞誉。Midjourney，根植于稳定扩散 AI 绘画范式，是一种以文本驱动的图像生成工具。 仅凭文字提示，Midjourney 可以在大约一分钟内生成相应的图像。Midjourney 利用人类直觉和机器智能之间的协同合作，赋予专业内容创作者和更广泛的观众超越传统“技术”和“效率”范围的构想和创作能力。最近的版本，Midjourney 5.2，引入了诸如对象锁定、部分重绘和绘图风格选择等功能，扩大了其在产品设计、动画、游戏和时尚等各个领域的适用性。此外，它始终提供领先质量和创意的图像。

As an embodiment of technological advancement and intellectual progress, AI guides designers to transform into intelligent designers. The rapid evolution of AI positions it as more than just a tool for design; it also manifests a degree of creativity, sparking debates around the question “Will AI replace designers”? We contend that the relationship between AI and human designers should be seen as complementary rather than substitutive. A synergy of “human intelligence + artificial intelligence”, or “fusion intelligence”, is likely to emerge [9]. AI acts as a collaborative partner, establishing a symbiotic relationship with designers and steering their innovative thinking systematically [10,11,12]. In the case of Midjourney, the tool has made a breakthrough in the basic modules of AI co-design and has been successfully integrated into the design innovation process. Here, we employed the Double Diamond model, a structured and iterative approach to describe the design process as Define (Design Definition), Discover (Design Research), Develop (Design generation) and Deliver (Design Implementation). As we can see from Figure 1, the Midjourney AIGC tool plays a key role in the two critical phases of design research and conceptual design, enabling rapid visualization and facilitating efficient communication across multidisciplinary contexts. For researchers, Midjourney’s rapid visualization capabilities offer a novel research tool that stimulates ideas, supports morphological studies and improves the efficiency of trials. For companies, Midjourney is instrumental in enhancing design efficiency. Its use of the Vincennes diagram provides a new way of expressing the needs of both parties A and B. At the same time, Midjourney significantly reduces the cost of software learning for designers, lowers the barriers to design expression, and boosts the communication efficiency of interdisciplinary teams. With the collaboration of AI, the design process will become more systematic and efficient, allowing designers to delve deeper into design research [13]. This will enable them to integrate knowledge from various disciplines to build an understanding of key interdisciplinary challenges and better equip them to tackle future design problems [14].
作为技术进步和智力进步的体现，人工智能引导设计师转变为智能设计师。人工智能的快速演进使其不仅仅是设计工具；它还展现出一定程度的创造力，引发了围绕“人工智能会取代设计师吗？”的争论。我们认为，人工智能与人类设计师之间的关系应被视为互补而非替代性的。 “人类智慧+人工智能”或“融合智能”的协同作用可能会出现。人工智能充当协作伙伴，与设计师建立共生关系，并系统地引导他们的创新思维。在 Midjourney 的案例中，该工具在人工智能共同设计的基本模块上取得了突破，并成功地融入了设计创新过程。在这里，我们采用了双钻石模型，这是一种结构化和迭代的方法，用于描述设计过程，包括定义（设计定义）、发现（设计研究）、开发（设计生成）和交付（设计实施）。 正如我们从图 1 中所看到的，Midjourney AIGC 工具在设计研究和概念设计的两个关键阶段中发挥着重要作用，实现快速可视化并促进跨学科背景下的高效沟通。对于研究人员来说，Midjourney 的快速可视化能力提供了一种新颖的研究工具，激发了想法，支持形态学研究，并提高了试验的效率。对于公司而言，Midjourney 在提高设计效率方面起着关键作用。其使用 Vincennes 图表的方式提供了一种表达 A 和 B 双方需求的新途径。同时，Midjourney 显著降低了设计师软件学习的成本，降低了设计表达的障碍，并提升了跨学科团队的沟通效率。通过人工智能的协作，设计过程将变得更加系统化和高效，使设计师能够更深入地进行设计研究。这将使他们能够整合来自各个学科的知识，建立对关键跨学科挑战的理解，并更好地为解决未来的设计问题做好准备。

Figure 1. Midjourney’s impact on design processes.
图 1. Midjourney 对设计过程的影响。

This paper aims to investigate how the Midjourney AIGC Tool can be integrated into design innovation systems to equip designers with future-oriented design literacy across different forms of product innovations and interdisciplinary collaborations. Specifically, we explore the following three research questions:
本文旨在探讨如何将 Midjourney AIGC 工具整合到设计创新系统中，以赋予设计师未来导向的设计素养，涵盖不同形式的产品创新和跨学科合作。具体而言，我们探讨以下三个研究问题：

• RQ1: How does AIGC assist designers in developing leading-edge exploratory product design innovations?
  RQ1：AIGC 如何帮助设计师开发领先的探索性产品设计创新？
• RQ2: How does AIGC rapidly empower designers to focus on task-oriented product design practices?
  RQ2：AIGC 如何快速赋能设计师专注于面向任务的产品设计实践？
• RQ3: How does AIGC facilitate the communication of interdisciplinary collaboration in design innovation?
  RQ3：AIGC 如何促进设计创新中跨学科合作的沟通？

Section 2 presents how to use the Midjourney tool for design practice in four steps, while Section 3 covers the Discussion, followed by the Conclusion in Section 4.
第 2 节介绍了如何使用 Midjourney 工具进行设计实践的四个步骤，而第 3 节涵盖了讨论，随后是第 4 节的结论。

2. Methods 2. 方法

We selected the AI drawing tool Midjourney as an example to demonstrate how AIGC can collaborate and innovate with designers in design practice. This process can be divided into the following four main steps:
我们选择了 AI 绘图工具 Midjourney 作为示例，以展示 AIGC 如何在设计实践中与设计师合作和创新。这个过程可以分为以下四个主要步骤：

• Step 1—Introduction of AMP-Cards: Propose the formula-based AIGC Midjourney Prompt cards for product design;
  步骤 1—引入 AMP 卡片：提出基于公式的 AIGC 中途提示卡片，用于产品设计；
• Step 2—Conducting leading-edge exploratory program practices: Develop product design concepts through prototype-based design research;
  第二步——进行领先的探索性项目实践：通过基于原型的设计研究开发产品设计概念；
• Step 3—Undertaking enterprise design task-oriented project practice: Delve into how AIGC empowers designers to advance their design practice through examples of projects.
  第三步——进行以企业设计任务为导向的项目实践：深入探讨 AIGC 如何通过项目示例赋予设计师推进他们的设计实践。
• Step 4—Hosting interdisciplinary collaborative design workshops: Investigate the influence of AIGC on interdisciplinary collaboration for design innovation through a design workshop, and gather participants’ feedback through interviews.
  第四步—举办跨学科协作设计研讨会：通过设计研讨会调查 AIGC 对设计创新跨学科协作的影响，并通过访谈收集参与者的反馈。

2.1. Step 1: AIGC-Based Midjourney Prompt Cards for Product Design
2.1. 步骤 1：基于 AIGC 的产品设计中程提示卡

Midjourney is a generative AI service that creates images from natural language descriptions called prompts; therefore, it is important to give the right command. Figure 2 summarizes our Midjourney usage as follows: (1) input two style migration reference maps and generate a fusion map; (2) combine the fusion map with the Prompt formula; (3) select the intended solution; (4) iterate on the intended solution using the Prompt formula; (5) select the final solution.
Midjourney 是一种生成式人工智能服务，可以根据所谓的提示从自然语言描述中创建图像；因此，给出正确的命令非常重要。图 2 总结了我们对 Midjourney 的使用方式如下：（1）输入两个风格迁移参考地图并生成融合地图；（2）将融合地图与提示公式结合；（3）选择预期解决方案；（4）使用提示公式对预期解决方案进行迭代；（5）选择最终解决方案。

Figure 2. Midjourney usage flow.
图 2. 中途使用流程。

The standardization and accuracy of the prompt considerably influence the quality of the images generated using Midjourney [15]. Based on the literature review [16,17,18] and our team’s hands-on experience, we propose the following product design formula:
提示的标准化和准确性极大地影响使用 Midjourney 生成的图像的质量[15]。根据文献综述[16,17,18]和我们团队的实践经验，我们提出以下产品设计公式：

Reference Image + Target Product (sound design) + Design Discipline (industrial design) + CMF (anodized aluminum, cold stamping) + Designism (modernism) + Designer/Brand (Ditramus/Apple) + Camera View (side view) + Background (white background) + Rendering Method (OC rendering/virtual rendering) + Lighting (global lighting) + Sharpness (4K).
参考图像 + 目标产品（声音设计）+ 设计学科（工业设计）+ CMF（阳极氧化铝，冷冲压）+ 设计主义（现代主义）+ 设计师/品牌（Ditramus/苹果）+ 摄像头视图（侧视图）+ 背景（白色背景）+ 渲染方法（OC 渲染/虚拟渲染）+ 灯光（全局照明）+ 锐度（4K）。

In addition, using the prompt formula combined with many practical experiences, a set of application cards—AIGC-based Midjourney Prompt Cards for Product Design (Figure 3)—were created. These cards offer a convenient tool for novice Midjourney designers to progress from product concepts to product forms by providing succinct guidance. Experienced designers can also use this card template to create and grow their work area, which requires a Prompt card.
此外，结合许多实际经验，使用提示公式创建了一套应用卡——基于 AIGC 的产品设计中程提示卡（图 3）。这些卡片为初学者中程设计师提供了一个方便的工具，通过提供简洁的指导，帮助他们从产品概念进展到产品形态。有经验的设计师也可以使用这些卡片模板来创建和扩展他们的工作领域，这需要一个提示卡。

Figure 3. AIGC-based Midjourney Prompt Cards for Product Design (AMP-Cards). Note that all the images within the cards are created by Midjourney.
图 3. 基于 AIGC 的产品设计中程提示卡（AMP-Cards）。请注意，卡片中的所有图像均由 Midjourney 创建。

AMP-Cards can be expandable based on their creators’ accumulated AIGC application experience. To facilitate the expansion of their own product design AIGC Prompt card, we have summarized and sorted a number of keywords that are strongly related to product design and affect the quality of generation (Table 1) so that creators can quickly generate the desired design solutions via Midjourney [19,20].
AMP 卡片可以根据其创建者积累的 AIGC 应用经验进行扩展。为了促进其产品设计 AIGC 提示卡的扩展，我们总结并整理了一些与产品设计密切相关且影响生成质量的关键词（表 1），以便创建者可以通过 Midjourney 快速生成所需的设计解决方案[19, 20]。

Table 1. AIGC Collaborative Industrial Design Strong Keywords Library.

Materials	Processing	Designism	Designer
Anodized aluminum	Super plastic molding	Modernism	Dieter Rams
Carbon fiber	Injection molding	Deconstructionism	Raymond Loewy
Stainless steel	Blow molding	Postmodernism	Charles and Ray Eames
Ceramic	Extrusion molding	Minimalism	Philippe Starck
Glass	Rotational molding	Maximalism	Jonathan Ive
Acrylic	Thermoforming	Functionalism	Karim Rashid
ABS plastic	Die casting	Constructivism	Marc Newson
Polycarbonate	Sand casting	Futurism	Naoto Fukasawa
Nylon	Investment casting	Brutalism	Ross Lovegrove
Leather	Lost-wax casting	Expressionism	Richard Sapper
Wood	Vacuum casting	Surrealism	Patricia Urquiola
Concrete	Metal spinning	Abstract expressionism	Jasper Morrison
Silicone	Hydroforming	Pop art	Ingo Maurer
Rubber	Compression molding	Art deco	Yves Behar
Brass	Transfer molding	Constructivism	Marcel Wanders
Copper	Foam molding	Post-structuralism	Alfredo Häberli
Bronze	Hot forging	Structuralism	Hella Jongerius
Zinc	Cold forging	Eclecticism	Tom Dixon
Titanium	Roll forging	technocracy	Konstantin Grcic
Gold	Coining	Art nouveau	Stefan Sagmeister
Silver	Swaging	Arts and crafts	Sam Hecht
Platinum	Wire drawing	Environmentalism	Tadao Ando
Nickel	Deep drawing	Humanism	Peter Eisenman
Tin	Spinning	Rationalism	Bjarke Ingels
Iron	Bending	Primitivism	Zaha Hadid
Alloy	Roll bending	Neo-classicism	Norman Foster
Epoxy	Hydro bending	Neo-expressionism	Jean Nouvel
…	…	…	…

2.2. Step 2: AIGC Empowers Product Design Innovation for Leading-Edge Prototyping Exploration
2.2. 第二步：AIGC 推动产品设计创新，为领先的原型探索提供支持

Future design is increasingly focusing on the integration and innovation of design systems. The demands on designers’ qualifications are no longer confined to their design skills; instead, there is a greater emphasis on understanding design systems, that is, the fusion of multidisciplinary knowledge and abilities related to design. Consequently, designers are more likely to engage in design research from an interdisciplinary perspective, uncover deeper layers of design inspiration, and create innovative designs rich in principled qualities. With the aid of AIGC collaborative design, designers can conserve more energy to focus on researching design inspirations, particularly those stemming from the real world, for example, bionics. By delving into other fields, they are able to uncover design inspirations across a broader spectrum.
未来设计越来越注重设计系统的整合和创新。对设计师资格的要求不再局限于他们的设计技能；相反，更加强调对设计系统的理解，即与设计相关的跨学科知识和能力的融合。因此，设计师更有可能从跨学科的视角进行设计研究，发掘更深层次的设计灵感，并创造富有原则性质的创新设计。借助 AIGC 协作设计，设计师可以节省更多精力专注于研究设计灵感，特别是那些源自现实世界的灵感，例如仿生学。通过深入其他领域，他们能够发现更广泛范围的设计灵感。

Utilize a design application based on the study of the morphology of pearl scallops to demonstrate how AIGC can assist designers in conducting design innovations for cutting-edge prototyping explorations. We analyzed existing research on pearl scallops, with a particular focus on the unique structure that has evolved to adapt to a hostile environment. Using Canny edge detection, we processed forty-nine scallop images from Figure 4a for edge extraction. As a result, two morphological patterns were identified and are presented in Figure 4b. In this process, we utilized parametric design for shape fitting and regularity validation, paving the way for Midjourney generation.
利用基于对珍珠扇贝形态学研究的设计应用程序，演示 AIGC 如何协助设计师进行前沿原型探索的设计创新。我们分析了关于珍珠扇贝的现有研究，特别关注了其进化适应恶劣环境的独特结构。通过 Canny 边缘检测，我们处理了来自图 4a 的四十九张扇贝图像进行边缘提取。结果显示，识别出两种形态学模式，并在图 4b 中呈现。在这个过程中，我们利用参数化设计进行形状拟合和规则性验证，为中途生成铺平了道路。

Figure 4. Pearl shell image processing: (a) Pearl Scallop Image Collection; (b) Edge detection.
图 4. 珍珠贝壳图像处理：(a) 珍珠扇贝图像采集；(b) 边缘检测。

Pattern 1: The shells feature arched rather than semicircular ridges, interspersed with tiny grooves as depicted in Figure 5, a design that enhances their resistance to pressure. To analyze this particular shape, we employed Ameba, a topology optimization plug-in for Rhino 7.4 modeling software, validating the morphology based on the modeled structure. We discovered that the arch shape plays a significant role in improving pressure distribution upon ground contact. Furthermore, after 59 iterations of bidirectional evolutionary structural optimization (BESO) applied to the arch shape, a fine groove structure emerged on the ridge. This structure bears a resemblance to the parallel arrangement seen in the pearl oyster, substantiating the validity of Pattern 1.
模式 1：这些壳具有拱形而不是半圆形的脊，夹杂着微小的凹槽，如图 5 所示，这种设计增强了它们对压力的抵抗力。为了分析这种特殊形状，我们使用了 Ameba，这是 Rhino 7.4 建模软件的拓扑优化插件，根据建模结构验证了形态。我们发现拱形在改善地面接触时的压力分布中起着重要作用。此外，在将双向演化结构优化（BESO）应用于拱形的 59 次迭代后，脊上出现了一种细微的凹槽结构。这种结构类似于珍珠贝中看到的平行排列，证实了模式 1 的有效性。

Figure 5. Morphological study of pearl scallops. After selecting the subject, we created a topological diagram to illustrate the scallop’s hierarchical structure: Level 1 (A) and Level 2 (B, components of A). The pearl scallop is divided into shell A1, soft part A2, and eye A3. Shell A1 further splits into ridge B1 and groove B2, while the soft part is divided into muscle B3 and gill B4.
图 5. 珍珠扇贝的形态学研究。在选择对象后，我们创建了一个拓扑图来说明扇贝的层次结构：第 1 级（A）和第 2 级（B，A 的组成部分）。珍珠扇贝分为壳 A1、软部分 A2 和眼睛 A3。壳 A1 进一步分为脊 B1 和槽 B2，而软部分分为肌肉 B3 和鳃 B4。

Pattern 2: The fan-shaped growth pattern of pearl scallop in dividing the ridge and groove, in contrast to the traditional concentric fan with increasing radius of equal difference, tends to encrypt from the outside to the inside gradually, and this structure effectively reduces the problem of pressure concentration. In this case, the circular interpolation blending algorithm was applied to simulate the variation of growth pattern sparsity by fitting the morphology. With Rhino modeling software, we built a classic curved shaft structure, and then with the Ameba plug-in, we performed finite element analysis to verify this structure [21,22] (Figure 5).
模式 2：珍珠扇贝在分隔脊和槽的扇形生长模式中，与传统的同心扇形相比，半径逐渐增加的等差扇形，倾向于从外到内逐渐加密，这种结构有效地减少了压力集中的问题。在这种情况下，采用圆形插值混合算法来模拟生长模式稀疏性的变化，通过拟合形态。利用 Rhino 建模软件，我们构建了一个经典的曲线轴结构，然后使用 Ameba 插件进行有限元分析来验证这种结构[21,22]（图 5）。

The morphology of the pearl scallop served as inspiration for the design of the submarine, an artificial underwater product. We applied AMP-Cards and entered the following keywords in Midjourney: Autonomous Underwater Vehicle design, Industrial design, anodized aluminum, dark grey, hot-pressing process, futuristic, technological, studio lighting, white background, 8k, photo-realistic, an arched structure with serrated grooves in the style of industrial and technical subjects, arch cut out template, in the style of solarpunk. An arch is shown with a sharp edge and is shaped into a wave pattern. Figure 6 displays the specific generation process: restricted by six references, three series of conceptual design generation attempts were first made, followed by selecting the three preliminary solutions. Using the “/blend” command of Midjourney, the three solutions were combined and iterated to generate the final solution. This solution emphasizes the structure of the pearl scallop ridges and incorporates grooves in the center protrusions to enhance the shell’s strength. The external structure is semi-closed, and the edge morphology reflects the irregular margins of the pearl scallop.
珍珠扇贝的形态启发了潜水艇的设计，这是一种人造水下产品。我们应用了 AMP-Cards，并在 Midjourney 中输入了以下关键词：自主水下车辆设计，工业设计，阳极氧化铝，深灰色，热压工艺，未来主义，技术性，工作室照明，白色背景，8k，照片逼真，呈工业和技术主题风格的拱形结构，拱形切割模板，以太阳朋克风格呈现。拱形展示了一个带有锋利边缘并呈波浪图案的结构。图 6 展示了具体的生成过程：受到六个参考的限制，首先进行了三个系列的概念设计尝试，然后选择了三个初步解决方案。使用 Midjourney 的“/blend”命令，将三个解决方案组合并迭代生成最终解决方案。该解决方案强调了珍珠扇贝脊的结构，并在中央突起处加入凹槽以增强壳体的强度。外部结构是半封闭的，边缘形态反映了珍珠扇贝的不规则边缘。

Figure 6. Submarine design based on pearl scallop morphology study under AIGC collaboration. Five dimensions are proposed to evaluate the AIGC generation results from a morphology design viewpoint.
图 6. 根据珍珠扇贝形态学研究设计的潜艇，是 AIGC 合作的成果。提出了五个维度来评估 AIGC 生成结果，从形态设计的角度来看。

The case above demonstrates the collaborative impact of AIGC, as exemplified by Midjourney, in the rapid visualization (transformation) of design inspirations into conceptual design solutions. It can efficiently generate multiple abstract solutions for designers, significantly reducing designers’ workload in the ‘shape-making’ phase of conceptual design. This efficiency enables designers to devote more time [23] and energy to inspiration research, stimulates deeper innovation capabilities, and promotes interdisciplinary collaboration to solve more complex problems [24] (Figure 7). This approach to AIGC co-design may serve as a model for industrial designers’ future methods of operation [25,26].
上述案例展示了 AIGC 的协作影响，正如 Midjourney 所展示的，将设计灵感迅速可视化（转化）为概念设计解决方案。它可以为设计师高效地生成多个抽象解决方案，显著减少设计师在概念设计的“塑造”阶段的工作量。这种效率使设计师能够将更多时间和精力投入到灵感研究中，激发更深层次的创新能力，并促进跨学科合作以解决更复杂的问题（图 7）。这种 AIGC 共同设计的方法可能成为工业设计师未来操作方法的模式。

Figure 7. Improvement in design efficiency by AIGC collaboration.
图 7. 通过 AIGC 合作在设计效率方面的改进。

2.3. Step 3: AIGC Assists Companies in Designing Task-Oriented Practice Programs
2.3. 步骤 3：AIGC 协助公司设计面向任务的实践计划

AIGC boasts significant advantages in mastering design styles and rapidly outputting multiple solutions, facilitating the swift and iterative progress of company-commissioned designs, particularly in projects with a focus on styling [27]. Taking Midjourney as an example, the success of a design relies on two key factors: (i) identifying and uploading a reference that aligns with the desired design style in accordance with the company’s specifications; (ii) inputting the appropriate prompt for AIGC to generate logic. The prompt serves as the primary means of interaction between designers and AIGC, and selecting the correct prompt words is crucial to maximizing AIGC’s efficiency, enabling it to quickly generate a plethora of design solutions for designers to select.
AIGC 在掌握设计风格和快速输出多种解决方案方面具有显著优势，有助于公司委托设计的快速和迭代进展，特别是在注重样式的项目中[27]。以 Midjourney 为例，设计的成功取决于两个关键因素：(i) 根据公司的规格标准确定并上传与所需设计风格一致的参考资料；(ii) 输入适当的提示以便 AIGC 生成逻辑。提示是设计师和 AIGC 之间的主要交互方式，选择正确的提示词对于最大化 AIGC 的效率至关重要，使其能够快速生成大量设计解决方案供设计师选择。

We present a case study of Flying Aerospace (Beijing)’s flying vehicle design, in which the conventional vehicle is equipped with the capability for vertical take-off and landing (eVTOL), in addition to its standard ground operations. The company’s main design requirements for this project include (i) an appealing stylish design with a feasible structure; (ii) a transition to the Tesla Cybertruck design style; (iii) completion of the design within twenty-four hours. After analyzing the ‘impenetrable exoskeleton’ styling sensibility of the Cybertruck we converted its design elements—such as morphological style, materials, and color scheme—into textual descriptions to prepare for composing the prompt. AIGC-Midjourney and our design team collaboratively worked on the exterior. To enhance the accuracy of the prompt, we used Midjourney’s “/describe” command to input an image of the Cybertruck, allowing the AI to extract its stylistic elements. Additionally, we used AMP-Cards to input the prompt alongside the design concept: Flying car design, industrial design, black and white split, cold stamping, modernism, futurism, Tesla, perspective, white background, OC rendering, studio lighting, 4K. Within 20 min, we collaborated with Midjourney to conduct two rounds of iteration and generate 26 solutions. Based on a derived proposal that closely aligned with the company’s design requirements, we exported the STEP model, making modifications and manual adjustments based on the designer’s experience (Figure 8). It took only 10 h from the receipt of the project requirements to the completion of the design proposal, which the company approved on the first iteration. The company design task-oriented practice project demonstrates that AIGC collaborative designers can substantially enhance product design efficiency.
我们提供了一份关于 Flying Aerospace（北京）飞行器设计的案例研究，其中传统飞行器配备了垂直起降（eVTOL）功能，除了标准的地面操作外。该公司对这个项目的主要设计要求包括（i）具有吸引力的时尚设计和可行的结构；（ii）过渡到特斯拉 Cybertruck 设计风格；（iii）在二十四小时内完成设计。在分析 Cybertruck 的“坚不可摧的外骨骼”造型感知后，我们将其设计元素（如形态风格、材料和配色方案）转化为文本描述，以准备撰写提示。AIGC-Midjourney 和我们的设计团队共同致力于外观设计。为了提高提示的准确性，我们使用了 Midjourney 的“/describe”命令来输入 Cybertruck 的图像，让人工智能提取其风格元素。 此外，我们使用 AMP-Cards 将提示与设计概念一起输入：飞行汽车设计，工业设计，黑白分割，冷冲压，现代主义，未来主义，特斯拉，透视，白色背景，OC 渲染，工作室照明，4K。在 20 分钟内，我们与 Midjourney 合作进行了两轮迭代，生成了 26 个解决方案。基于一个与公司设计要求密切相关的提案，我们导出了 STEP 模型，并根据设计师的经验进行了修改和手动调整（图 8）。从接收项目要求到完成设计提案仅用了 10 小时，公司在第一轮迭代中就批准了。公司的设计任务导向实践项目表明，AIGC 协作设计师可以大大提高产品设计效率。

Figure 8. Modular flying car design based on the collaboration of prompt formulas.
图 8. 基于即时公式协作的模块化飞行汽车设计。

2.4. Step 4: AIGC Facilitates the Future of Design Innovation through Interdisciplinary Collaboration
2.4. 第四步：AIGC 通过跨学科合作促进设计创新的未来

Future design projects require interdisciplinary and multi-professional collaboration. However, previous projects [28] have demonstrated that achieving efficient communication and effective teamwork within interdisciplinary teams is invariably a challenge. Due to distinct fields of specialization, the lack of mutual understanding of the different knowledge backgrounds in traditional interdisciplinary cooperation results in high communication costs and slow project progress [29,30,31]. For example, students without a design background might lack the necessary sketch drawing skills to visually present their ideas to other group members, resulting in miscommunication issues due to their diverse professional backgrounds. The advent of AIGC presents an opportunity to transform the design process and potentially positively influence interdisciplinary team collaboration [32]. Therefore, we conducted a workshop on interdisciplinary collaborative design with AIGC synergy to observe the role of communication between members of Midjourney and AMP-Cards in multidisciplinary collaborations and to explore a new model of interdisciplinary collaborative design resulting from the introduction of AIGC [33].
未来的设计项目需要跨学科和多专业的合作。然而，之前的项目[28]表明，在跨学科团队内实现高效沟通和有效团队合作始终是一个挑战。由于不同的专业领域，传统跨学科合作中对不同知识背景的相互理解不足导致沟通成本高、项目进展缓慢[29, 30, 31]。例如，没有设计背景的学生可能缺乏必要的素描技能，无法将他们的想法以视觉方式呈现给其他组员，由于各自不同的专业背景而导致沟通问题。人工智能生成创意（AIGC）的出现为改变设计过程并可能积极影响跨学科团队合作提供了机会[32]。 因此，我们开展了一场关于跨学科协作设计的研讨会，利用 AIGC 的协同效应来观察 Midjourney 和 AMP-Cards 成员之间的沟通在多学科协作中的作用，并探索由引入 AIGC 而产生的跨学科协作设计新模式。

For this workshop, 12 students were recruited and divided into two groups. Each group consisted of four Mechanical Engineering students and two Industrial Design students. Group 1 engaged in co-design with AIGC-Midjourney, whereas Group 2 followed the conventional design process. The workshop project was based on the XY dual-axis mechanical platform derivative product concept idea.
对于这个研讨会，招募了 12 名学生，并分成两组。每组包括四名机械工程学生和两名工业设计学生。第一组与 AIGC-Midjourney 进行共同设计，而第二组遵循传统设计流程。研讨会项目基于 XY 双轴机械平台衍生产品概念。

Group 1 discussed the design definition with all group members in the pre-conceptual design stage. Each group member combed through the AMP-Cards to devise a Prompt based on the design definition and then input the Prompt into Midjourney to obtain the generated design images. Following the generation of design drawings, the group members discussed the scheme and further optimized the Prompt cue words for the iteration. This interdisciplinary communication model for “idea visualization + language expression” could ensure that design solutions are rapidly iterated under a unified concept, markedly enhancing the efficiency of progression. Utilizing the “idea visualization + language expression” approach, students from both disciplines were able to grasp each other’s design intentions intuitively, facilitating discussions on design details without the risk of misinterpretation often associated with abstract language expression.
第一组在概念设计阶段与所有组员讨论了设计定义。每位组员通过整理 AMP-Cards，根据设计定义设计了一个提示，并将提示输入到 Midjourney 中以获得生成的设计图像。在生成设计图纸后，组员们讨论了方案，并进一步优化了提示词以进行迭代。这种“思想可视化+语言表达”的跨学科沟通模式可以确保设计解决方案在统一概念下快速迭代，显著提高了进展效率。利用“思想可视化+语言表达”方法，来自两个学科的学生能够直观地把握彼此的设计意图，促进对设计细节的讨论，避免了常常伴随抽象语言表达的误解风险。

Group 1 designed a solution for fast food in urban areas, proposing the idea of a customized hamburger vending machine. The burger consists of multiple layers of pre-cooked ingredients, catering to different diners’ preferences. The vending machine is equipped with a flexible hand on the XY platform to grab the corresponding elements and “make” the burger ingredients on a central platform, and the burger production process is visible to demonstrate the quality and freshness of the ingredients. Utilizing tools such as Midjourney and AMP-Cards, the team members efficiently worked through five rounds of conceptual solutions (see Figure 9), employing the “idea visualization + language expression” approach (illustrated in Figure 10). The entire design process was completed in approximately three hours.
第一组为城市地区的快餐设计了一个解决方案，提出了定制汉堡自动售货机的概念。这款汉堡由多层预先烹饪的食材组成，满足不同食客的口味偏好。自动售货机配备了一个灵活的手臂，位于 XY 平台上，可以抓取相应的元素并在中央平台上“制作”汉堡的食材，整个汉堡制作过程是可见的，以展示食材的质量和新鲜度。团队成员利用 Midjourney 和 AMP-Cards 等工具，高效地完成了五轮概念解决方案的工作（见图 9），采用了“想法可视化+语言表达”方法（见图 10）。整个设计过程大约耗时三个小时。

Figure 9. The first set of 5-round iterative design solutions based on Midjourney + AMP-Cards.
图 9. 基于 Midjourney + AMP-Cards 的第一组 5 轮迭代设计解决方案。

Figure 10. The first group of AIGC-based collaborative interdisciplinary co-design scenarios.
图 10. 基于 AIGC 的协作跨学科共同设计场景的第一组。

Compared to Group 1, Group 2 conducted their design process in a traditional collaborative manner, without the assistance of AIGC-Midjourney synergy. Their design concept focused on creating a massage chair equipped with an XY work platform and a machine vision system. This technology would enable the chair to intelligently recognize different body parts, aiming to alleviate the fatigue experienced by office personnel due to prolonged periods of sitting.
与第一组相比，第二组以传统的协作方式进行设计过程，没有借助 AIGC-Midjourney 协同。他们的设计概念侧重于打造一款配备 XY 工作平台和机器视觉系统的按摩椅。这项技术将使椅子能够智能识别不同的身体部位，旨在缓解办公人员因长时间坐着而感到的疲劳。

Group members gathered relevant design case studies to find design inspiration based on the design concept. Following an initial discussion, they each drew sketches based on their interpretations and then reconvened for a second round of discussion focused on these illustrations (Figure 11). As the mechanical background students were not able to effectively visualize the idea by sketch, the design background students re-drew the mechanical students’ sketches based on their face-to-face communication. The sketching solution was evaluated and selected in the third round of discussion. After modeling and rendering the final solution for approximately 4.5 h, the final solution was complete (Figure 12).
小组成员收集相关的设计案例研究，以设计概念为基础寻找设计灵感。在初步讨论后，他们根据自己的理解绘制草图，然后重新聚集进行第二轮讨论，重点放在这些插图上（图 11）。由于机械背景的学生无法通过草图有效地可视化想法，设计背景的学生根据面对面的沟通重新绘制了机械学生的草图。草图解决方案在第三轮讨论中进行评估和选择。在对最终解决方案建模和渲染约 4.5 小时后，最终解决方案完成（图 12）。

Figure 11. Interdisciplinary collaborative design scene based on the traditional model for the second group.
图 11. 基于传统模型的跨学科协作设计场景，适用于第二组。

Figure 12. The second group of solutions is based on the traditional design process.
图 12. 第二组解决方案基于传统的设计过程。

The data from the two groups in the interdisciplinary workshop are presented in Table 2. Over a comparable period, Group 1 (which utilized AIGC) underwent five times as many design iterations as Group 2, demonstrating that AIGC can significantly enhance design efficiency in interdisciplinary collaboration. To assess the quality of the designs, two external design experts were invited to evaluate the outcomes. Group 1 received scores of 85 and 88 out of 100, while Group 2 received scores of 78 and 80, showcasing the positive impact of AIGC on design quality. However, the evaluations from the external experts highlighted a shortcoming of AIGC in the aspect of design evaluation, which is a critical factor in the success of product design and demands a high level of expertise from designers.
跨学科研讨会两组的数据见表 2。在相同的时间段内，利用 AIGC 的第一组进行了五倍于第二组的设计迭代，表明 AIGC 可以显著提高跨学科合作中的设计效率。为了评估设计的质量，邀请了两位外部设计专家来评估结果。第一组得分为 85 和 88 分，而第二组得分为 78 和 80 分，展示了 AIGC 对设计质量的积极影响。然而，外部专家的评估突显了 AIGC 在设计评估方面的不足，这是产品设计成功的关键因素，需要设计师具备高水平的专业知识。

Table 2. Impact of AIGC in interdisciplinary design collaboration.

Group	Program	Iteration Number	Design Quality Assessment	Overview of Interview Feedback
Group 1 (Apply AIGC + AMP Cards)	Burger Vending Machine	5	85/88	AIGC facilitates interprofessional collaboration and communication. AIGC can make up for a lack of sketching skills. AIGC saves design time. The design iteration process lacks auxiliary evaluation functions.
Group 2 (Without AIGC)	Office Scene Massage Chair	1	78/80	Long time spent in the pre-program phase. The visual effect of the program was not satisfactory due to time restrictions. The mechanical background students had to rely on the design background students’ hand-drawing skills to express design ideas clearly.

After the workshop, we interviewed members from both groups about their experiences of the workshop, as summarized in Table 2. An industrial design student from Group 1 expressed how AIGC improved their communication with mechanical engineering peers. They emphasized AIGC’s ease of use for those, like them, lacking sketching skills, and appreciated its efficiency in the design process. Conversely, Group 2 students, not using AI tools, spent more time in discussions and felt their visual output was subpar. Those with a mechanical background felt their ideas were not expressed clearly until design-background students helped translate them. The feedback aligns with the table data, showing Midjourney’s value in improving clarity and communication, especially for newcomers to the tool. Overall, integrating AIGC and AMP-Cards into interdisciplinary design workshops has augmented the advantages of quick, accurate, and visual communication, positively influencing multidisciplinary collaboration.
在研讨会结束后，我们对两组成员进行了采访，询问他们对研讨会的体验，总结如表 2 所示。来自第一组的一位工业设计学生表达了 AIGC 如何改善他们与机械工程同行的沟通。他们强调了 AIGC 对于那些缺乏素描技能的人来说易于使用，并赞赏其在设计过程中的效率。相反，未使用人工智能工具的第二组学生在讨论上花费了更多时间，并感觉他们的视觉输出不尽如人意。那些具有机械背景的人直到有设计背景的学生帮助翻译他们的想法，才觉得自己的想法没有清晰表达。反馈与表格数据一致，显示 Midjourney 在改善清晰度和沟通方面的价值，尤其对于工具的新手。总体而言，将 AIGC 和 AMP-Cards 整合到跨学科设计研讨会中增强了快速、准确和视觉沟通的优势，积极影响了多学科合作。

3. Discussion 3. 讨论

The evolution of AIGC has catalyzed innovation and shifts in the design production model, also reshaping the skillset needed for future designers, who will need to acquire a new perspective. We have summarized the AIGC-based Midjourney Prompt Cards for Product Design (AMP-cards), which will help creators quickly learn how to use Midjourney to visualize and graphically present their ideas to assist designers in conducting design research and practice, as well as interdisciplinary collaboration with the iconic tool Midjourney. The introduction of Midjourney can reduce the learning and production time cost of modeling and rendering in the design process, as well as the skill limitations of novice designers caused by the learning of design tools, which inhibits their creativity and creates frustration in learning. In other words, design practitioners can “free their hands” from learning skills and concentrate more on developing creativity and innovation.
AIGC 的演变催生了创新和设计生产模式的转变，也重塑了未来设计师所需的技能组合，他们需要获得新的视角。我们总结了基于 AIGC 的产品设计中程提示卡（AMP 卡），这将帮助创作者快速学习如何使用中程来可视化和图形化呈现他们的想法，以协助设计师进行设计研究和实践，以及与标志性工具中程进行跨学科合作。中程的引入可以减少设计过程中建模和渲染的学习和生产时间成本，以及由于设计工具学习而导致的新手设计师的技能限制，这抑制了他们的创造力并在学习过程中造成挫折。换句话说，设计从业者可以“解放双手”不再受技能学习的束缚，更专注于发展创造力和创新。

However, AIGC does not offer creators original design inspirations, so creators must discover their own. The technical principle of AIGC is to collect and learn from a large amount of text, images, and other multi-format data, combined with natural language processing, deep learning, and different algorithms, to automatically generate text content, images, and other creative design products, that is, through a large amount of existing data to optimize the algorithm for the automated generation of design content. In essence, these generated contents represent a fusion of existing solutions instead of original innovation. In most cases, as the design develops, the source of design inspiration has shifted from superficial motivation to in-depth study of a particular object, uncovering the mystery hidden beneath the surface to inspire design inspiration and apply it to a design project. For instance, in Case 1 in the article—Pearl Scallops Research—AIGC can accelerate the iterative process by rapidly generating program prototypes, freeing up much time and effort for pre-designing the research process. As a result, it is more likely to conduct leading-edge explorations with originality to realize the innovation of derivative concepts derived from the source, consisting of breakthrough and unique product solutions.
然而，AIGC 并不提供创作者原始的设计灵感，因此创作者必须自行发现。AIGC 的技术原理是收集并学习大量的文本、图像和其他多格式数据，结合自然语言处理、深度学习和不同的算法，自动生成文本内容、图像和其他创意设计产品，即通过大量现有数据优化算法，实现设计内容的自动化生成。实质上，这些生成的内容代表了现有解决方案的融合，而非原创创新。在大多数情况下，随着设计的发展，设计灵感的来源已经从表面动机转变为对特定对象的深入研究，揭示表面下隐藏的奥秘，激发设计灵感并应用于设计项目中。例如，在文章中的案例 1——珍珠扇贝研究中，AIGC 可以通过快速生成程序原型加速迭代过程，为预先设计研究过程节省大量时间和精力。 因此，更有可能以独创性进行前沿探索，实现从源头衍生出的衍生概念的创新，包括突破性和独特的产品解决方案。

AIGC provides a powerful and extensive design material library that gives designers instantaneous access to inspiring images based on their requirements [34,35]. This also implies that designers should dedicate time to collaborate effectively with AIGC, giving the AIGC tool accurate and specific instructions. In utilizing the Midjourney tool for Case 2—Flying Car Styling Design, designers are required to conduct a systematic and comprehensive product styling analysis of the Cybertruck and sort out the textual descriptions of the design elements to the prompt. This suggests that future designers will need to deepen their comprehension of classic design cases, styles, and CMFs to effectively use the Midjourney tool for intentional solution generation.
AIGC 提供了一个强大而广泛的设计素材库，使设计师可以根据他们的需求即时访问启发性的图片。这也意味着设计师应该花时间与 AIGC 有效合作，为 AIGC 工具提供准确和具体的指导。在使用 Midjourney 工具进行 Case 2—Flying Car Styling Design 时，设计师需要对 Cybertruck 进行系统和全面的产品造型分析，并整理设计元素的文本描述以响应提示。这表明未来的设计师需要加深对经典设计案例、风格和 CMF 的理解，以有效地利用 Midjourney 工具进行有意识的解决方案生成。

Furthermore, AIGC also provides a co-creative platform for interdisciplinary collaborative co-design, lowering the barrier of entry for non-design professionals and allowing more people to collaborate on design innovation. The future of design will necessitate even greater interdisciplinarity. Designers, engineers, scientists, and sociologists collaborate to develop integrated design solutions that solve increasingly complex problems and advance the design. This requires future designers to adapt to an interdisciplinary collaborative environment during their learning phase. The stumbling block in the process of multidisciplinary cooperation is that the knowledge gap between disciplines impedes the members’ understanding of one another’s ideas, and the abstract nature of the language expression itself is not friendly to the communication of ideas among the members. In Case 3—Interdisciplinary Design Workshop, students from diverse professional backgrounds apply the Midjourney tool to rapidly and visually express their design concepts. With AIGC, combined with AMP-Cards, as a rapid visualization tool, members from all fields can express their concepts accurately, bypassing the constraints of verbal communication. This greatly enhances the interdisciplinary collaborative process.
此外，AIGC 还提供一个跨学科协作共创平台，降低非设计专业人士的准入门槛，让更多人参与设计创新。设计的未来将需要更大程度的跨学科合作。设计师、工程师、科学家和社会学家合作开发综合设计解决方案，解决日益复杂的问题并推动设计的进步。这要求未来的设计师在学习阶段适应跨学科合作环境。在跨学科设计研讨会案例 3 中，来自不同专业背景的学生运用 Midjourney 工具快速、直观地表达他们的设计概念。 通过 AIGC 结合 AMP-Cards 作为一种快速可视化工具，来自各个领域的成员可以准确表达他们的概念，绕过口头沟通的限制。这极大地增强了跨学科合作过程。

Currently, the selection of AI-generated solutions depends largely on designers’ own experience, and there is still room for improvement in terms of market desirability, commercial value viability, and technical feasibility, and is primarily constrained by the following two technical limitations: (i) the lack of standardization in the generated results reduces the technical feasibility. For instance, AI can rapidly generate product structure in professional structural design (such as professional modeling software Creo’s 3D generative design). However, the generated structure consists primarily of heterogeneous and complex parts that are difficult to process and suffer high production costs. (ii) AI training models are unidirectional and irreversible [36]. As design research must continually integrate new interdisciplinary knowledge, AIGC must also figure out how to make AI progress with designers and adapt to future design paradigm shifts.
目前，AI 生成解决方案的选择在很大程度上取决于设计师自身的经验，市场吸引力、商业价值可行性和技术可行性仍有改进空间，主要受以下两个技术限制制约：(i) 生成结果缺乏标准化，降低了技术可行性。例如，AI 可以快速生成专业结构设计中的产品结构（如专业建模软件 Creo 的 3D 生成设计）。然而，生成的结构主要由异质和复杂部件组成，难以加工且生产成本高昂。(ii) AI 训练模型是单向且不可逆的。由于设计研究必须不断整合新的跨学科知识，AIGC 也必须找出如何使 AI 与设计师一起进步，并适应未来设计范式转变。

Future developments in AI technology and computer mathematics will significantly impact optimizing design evaluation methods [37,38]. To enhance the evaluation capability of AI co-design through machine learning, user data are incorporated into the model training process, and design concept visualization and quantitative evaluation models for personalized and highly specialized fields are developed. After a round of generation, the model can provide quantitative evaluation data and optimization suggestions (such as the ten-level scoring system of the ‘A’ Design Award) based on the results in a timely and objective manner, promoting the collaboration between AIGC and content generators to control the quality of the results as a “referee” [39] and enhancing the efficacy of cross-disciplinary research. Employing emotional computing, personality computing, social computing, cultural computing, and other scientific and humanistic methods, one can study the human experience mode, expand the boundaries of human cognition, and lay the communication foundation for future interdisciplinary teams to carry out design and innovation cooperation as “lubricant” [40].
未来人工智能技术和计算机数学的发展将显著影响优化设计评估方法[37, 38]。为了通过机器学习增强人工智能协同设计的评估能力，用户数据被纳入模型训练过程中，并开发了针对个性化和高度专业领域的设计概念可视化和定量评估模型。经过一轮生成，该模型可以根据结果及时客观地提供定量评估数据和优化建议（例如“A”设计奖的十级评分系统），促进 AIGC 与内容生成者之间的合作，以“裁判”身份控制结果质量，并增强跨学科研究的效力。利用情感计算、个性计算、社交计算、文化计算等科学和人文方法，可以研究人类体验模式，拓展人类认知边界，并为未来跨学科团队开展设计和创新合作奠定沟通基础，作为“润滑剂”[40]。

AIGC offers objective and comprehensive selection and judgment assistance functions for design collaboration, which will provide more accurate and targeted feedback information, allowing the generator to understand the design’s results and flaws better and enhance the overall quality of the invention. It is foreseeable that the future in the field of innovation will likely actualize the closed loop of interdisciplinary “research design”, achieving efficiency, precision, and stability [41].
AIGC 为设计协作提供客观全面的选择和评判辅助功能，将提供更准确和有针对性的反馈信息，使生成器更好地了解设计的结果和缺陷，并提高发明的整体质量。可以预见的是，未来创新领域可能会实现跨学科“研究设计”的闭环，实现效率、精确性和稳定性。

In addition, it should be noted that ensuring the originality of the designer’s concepts is important before leveraging the advantages of AI technology to enhance creative performance. AI should be used as a tool for enhancement and innovation rather than as a means of replication or replacement, thereby preserving the integrity, authenticity, and value of creative work.
此外，值得注意的是，在利用人工智能技术提升创意表现之前，确保设计师概念的独创性是重要的。人工智能应被用作增强和创新的工具，而非复制或替代的手段，从而保持创意作品的完整性、真实性和价值。

4. Conclusions 4. 结论

In this paper, we delve into the integration of AIGC into design systems, using Midjourney as a representative AIGC tool to enhance collaboration and innovation among creators. We propose an AIGC-based Midjourney approach for product design, equipped with prompt formulas and the accompanying AMP-Cards, which intends to help content creators master Midjourney skills more rapidly. The role of AIGC, exemplified by Midjourney, is explored through its application in cutting-edge design innovations, corporate projects, and interdisciplinary workshops. Specifically, AIGC co-design allows designers to focus more energy on researching design inspirations, particularly real-world inspirations, such as the design research of pearl scallops in Case 1. AIGC has an extraordinary advantage in design style mastery and rapid multi-program output, allowing for the rapid and iterative advancement of corporate-commissioned designs, particularly those concentrating on product styling style design. In cross-disciplinary teamwork, AIGC’s robust database enables rapid visualization of design concepts, facilitating communication and accelerating solution iteration.
在本文中，我们深入探讨了将 AIGC 整合到设计系统中，以 Midjourney 作为代表性 AIGC 工具，以增强创作者之间的协作和创新。我们提出了基于 AIGC 的 Midjourney 方法，用于产品设计，配备了快速公式和相应的 AMP-Cards，旨在帮助内容创作者更快地掌握 Midjourney 技能。通过在尖端设计创新、企业项目和跨学科研讨会中的应用，探讨了 AIGC 的作用，以 Midjourney 为例。具体而言，AIGC 共同设计使设计师能够更多地专注于研究设计灵感，特别是现实世界的灵感，比如案例 1 中对珍珠扇贝的设计研究。AIGC 在设计风格掌握和快速多程序输出方面具有非凡优势，可实现企业委托设计的快速和迭代推进，特别是那些集中在产品造型设计风格的设计。在跨学科团队合作中，AIGC 强大的数据库能够快速可视化设计概念，促进沟通并加速解决方案迭代。

It is expected that the use of Midjourney in product design and its case practice, as outlined in this paper, will provide creators and teams with inspiration and reference for future design research and trial and interdisciplinary collaboration. Simultaneously, the case study exposes areas of improvement for the Midjourney tool, which can provide suggestions for future enhancements to the AIGC design tool.
预计本文中概述的 Midjourney 在产品设计中的使用及其案例实践将为创作者和团队提供未来设计研究、试验和跨学科合作的灵感和参考。同时，案例研究揭示了 Midjourney 工具的改进领域，这可以为 AIGC 设计工具的未来增强提供建议。