作為一種基于“場(chǎng)”的全新設(shè)計(jì)軟件，DfAM 有助于推廣“增材制造”工藝的應(yīng)用，因?yàn)樗梢钥s短產(chǎn)品開(kāi)發(fā)周期，降低返工成本和風(fēng)險(xiǎn)。
by Blake Perez
真正的創(chuàng)新絕不僅是某個(gè)時(shí)刻的靈光一現(xiàn)，而更需要堅(jiān)定不移地對(duì)最初的想法或設(shè)計(jì)進(jìn)行不斷迭代和改進(jìn)，大量設(shè)計(jì)和創(chuàng)新模型與方法均可證明這一點(diǎn)。舉個(gè)例子，大家可能都知道戴森吸塵器的出色性能，但并非所有人了解，首次面世前，戴森首款無(wú)袋真空吸塵器實(shí)際已經(jīng)經(jīng)過(guò)了超過(guò) 5000 次的迭代與測(cè)試。美國(guó)久負(fù)盛名的 F-15 鷹式戰(zhàn)機(jī)也基于原始設(shè)計(jì)，不斷迭代出性能更強(qiáng)的 B、C、D、E 戰(zhàn)斗機(jī)。迭代往往可以收獲創(chuàng)新，而拒絕迭代則可以免去獲得新知識(shí)可能承擔(dān)的風(fēng)險(xiǎn)，但這樣做的后果是，到最后即便想改變和創(chuàng)新也將再無(wú)機(jī)會(huì)。
事實(shí)上，工程設(shè)計(jì)過(guò)程中的迭代可能困難重重，而且成本昂貴。任何設(shè)計(jì)修訂都會(huì)不可避免地產(chǎn)生最少數(shù)個(gè)小時(shí)的返工，而一些由于幾何尺寸造成的建模錯(cuò)誤更是將導(dǎo)致一系列毫無(wú)意義的重復(fù)工作。正因如此，盡管大家已經(jīng)充分理解迭代過(guò)程對(duì)產(chǎn)品開(kāi)發(fā)的重要性，但仍對(duì)這種“麻煩”存在本能的抵觸情緒。
增材制造的情況也不例外。事實(shí)上，由于存在文件編譯、配置編譯及模型分層等步驟，增材制造設(shè)計(jì)（Design for Additive Manufacturing，下簡(jiǎn)稱(chēng) DfAM）在修改設(shè)計(jì)時(shí)需要進(jìn)行的返工更多。很多情況下，DfAM 經(jīng)常作為一種“事后補(bǔ)救”而被應(yīng)用在工程設(shè)計(jì)的靠后環(huán)節(jié)。到了這個(gè)階段，設(shè)計(jì)人員通常僅會(huì)對(duì)部件設(shè)計(jì)進(jìn)行一些小修改，比如增加一些獨(dú)立功能、給關(guān)鍵部位額外增加一點(diǎn)尺寸（從而保證一些關(guān)鍵尺寸不會(huì)受到加工過(guò)程的影響）等。設(shè)計(jì)人員還可以進(jìn)行其他修改，從而充分挖掘增材設(shè)計(jì)的潛能。但遺憾的是，為了保證這些改動(dòng)，很多配套或相關(guān)特性也必須同時(shí)進(jìn)行返工。不難想象，這勢(shì)必會(huì)產(chǎn)生額外的時(shí)間成本和金錢(qián)成本。
在典型的增材設(shè)計(jì)中，設(shè)計(jì)人員必須首先使用 CAD 軟件工具將設(shè)計(jì)概念表現(xiàn)出來(lái)，然后一步步將其轉(zhuǎn)化為可以支持生產(chǎn)、打印的文件。很顯然，設(shè)計(jì)人員如需回到 CAD 階段，調(diào)整零部件的設(shè)計(jì)或幾何尺寸，則必須再一次完成后續(xù)的所有步驟，產(chǎn)生很大的工作量。即使無(wú)需回到最初的 CAD 階段，對(duì)后續(xù)任何一環(huán)的改動(dòng)都會(huì)導(dǎo)致其他環(huán)節(jié)的返工。
不過(guò)，軟件行業(yè)的最新發(fā)展可能會(huì)改變這種現(xiàn)狀。目前，軟件行業(yè)推出了一種基于隱式建模的開(kāi)發(fā)框架，可以在設(shè)計(jì)文件改變后進(jìn)行自動(dòng)編譯與重建，并將多個(gè)工程知識(shí)來(lái)源集中至唯一的數(shù)據(jù)平臺(tái)，整合多種文件類(lèi)型，讓整個(gè)過(guò)程更加敏捷。這種開(kāi)發(fā)框架可以消除傳統(tǒng)迭代和創(chuàng)新過(guò)程中的主要障礙，并將 DfAM 無(wú)縫集成至產(chǎn)品設(shè)計(jì)與制造流程中。
接下來(lái)，讓我們一起看看設(shè)計(jì)人員將如何設(shè)計(jì)一款輕量級(jí)增材制造剎車(chē)腳踏，并通過(guò)該例子熟悉隱式建模開(kāi)發(fā)框架下的 DfAM 工作流程。
首先，我們需要確定腳踏板大致的幾何結(jié)構(gòu)。為了給這個(gè)部件減重，我們將借助該開(kāi)發(fā)框架下的晶格工具，充分嘗試不同的晶格構(gòu)造。接著，設(shè)計(jì)人員會(huì)根據(jù)零部件對(duì)硬度的要求，對(duì)各個(gè)晶格類(lèi)型進(jìn)行加厚，并將其疊加至原始模型。
增材制造晶格結(jié)構(gòu)的通病在于晶格和覆蓋面容易剝離的問(wèn)題。對(duì)此，我們可以專(zhuān)門(mén)創(chuàng)建一套規(guī)則，將晶格平滑地混合至表層（第三步）。如今，憑借隱式建模開(kāi)發(fā)框架中的距離場(chǎng)，設(shè)計(jì)人員可以輕松將這種改動(dòng)應(yīng)用至全局，而無(wú)需再像傳統(tǒng)工具時(shí)代那樣，逐條手動(dòng)選擇模型中的每條邊，而幾何形狀的改動(dòng)則意味著必須花費(fèi)數(shù)小時(shí)重復(fù)這些枯燥的工作。
接著，我們的團(tuán)隊(duì)決定，每個(gè)晶格的厚度應(yīng)隨其與主安裝點(diǎn)的距離而變化。因此，我們?cè)趦?nèi)部區(qū)域增加一個(gè)厚度可變的晶格結(jié)構(gòu)，具體厚度由從一個(gè)平面表面（紅線部分）發(fā)散出的隱式場(chǎng)決定。通過(guò)這種做法，我們可以保證主安裝點(diǎn)附近具備足夠的硬度，因?yàn)槲覀冋J(rèn)為該區(qū)域未來(lái)將承受的應(yīng)力最高。在這步里，同樣是距離場(chǎng)讓我們得以制定這條規(guī)則，而我們?cè)谏弦徊街幸?guī)定的晶格與覆蓋面之間的規(guī)則依然可以重新生成。
在隱式建模開(kāi)發(fā)框架下，我們可以更加充分地利用場(chǎng)工具，不僅僅是通過(guò)距離場(chǎng)來(lái)構(gòu)建幾何結(jié)構(gòu)，還能借助各種各樣的場(chǎng)（數(shù)據(jù)）構(gòu)建晶格的中觀結(jié)構(gòu)，比如應(yīng)力、熱和流體模擬數(shù)據(jù)。實(shí)際上，您可以使用任何類(lèi)型的數(shù)據(jù)構(gòu)建您想要的幾何結(jié)構(gòu)。在設(shè)計(jì)剎車(chē)腳踏的例子中，我們決定使用工程師提供的Von Mises 應(yīng)力數(shù)據(jù)來(lái)修正晶格的厚度。
具體來(lái)說(shuō)，我們會(huì)在應(yīng)力值更高的地方增加晶格厚度，從而提供足夠的強(qiáng)度。正如上文所言，在隱式建模開(kāi)發(fā)架構(gòu)中，場(chǎng)是表達(dá)各類(lèi)組件數(shù)據(jù)的“基礎(chǔ)語(yǔ)言”，也正是有了“場(chǎng)”的概念，我們才能隨心所欲地使用各種數(shù)據(jù)構(gòu)建希望的幾何結(jié)構(gòu)。
到這一步，我們已經(jīng)準(zhǔn)備好了制動(dòng)腳踏板的幾何結(jié)構(gòu)，現(xiàn)在距離將其轉(zhuǎn)化為增材制造模型只差一步，也就是創(chuàng)建輪廓切片。同樣，由于采用了這種基于距離場(chǎng)的開(kāi)發(fā)框架，設(shè)計(jì)人員可以自由生成、指定增材工具路徑，掃描樣式，并跳過(guò)中間生成 STL 文件的過(guò)程，直接導(dǎo)出可用于加工的文件。
通常來(lái)說(shuō)，設(shè)計(jì)進(jìn)行到這個(gè)步驟，任何改動(dòng)都會(huì)引發(fā)文件編譯、配置編譯及模型分層等一連串返工，因此設(shè)計(jì)人員已經(jīng)很難對(duì)原始模型進(jìn)行更改了。不過(guò)，隱式建模則不存在類(lèi)似的問(wèn)題，即使我們改動(dòng)了設(shè)計(jì)，之前設(shè)置的規(guī)則也仍然有效。這點(diǎn)不難理解，假設(shè)有這么一個(gè)場(chǎng)景：工程團(tuán)隊(duì)已經(jīng)拿到了一組模擬數(shù)據(jù)，現(xiàn)在希望可以利用這些數(shù)據(jù)對(duì)現(xiàn)有設(shè)計(jì)進(jìn)行優(yōu)化。
在傳統(tǒng)工具時(shí)代，對(duì)晶格類(lèi)型和/或幾何結(jié)構(gòu)的任何修改都必須從第二步開(kāi)始進(jìn)行，動(dòng)靜相當(dāng)大，從時(shí)間和金錢(qián)成本考慮均不容易。如今，在隱式建模開(kāi)發(fā)架構(gòu)下，設(shè)計(jì)人員不僅可以高效地完成晶格類(lèi)型和/或幾何結(jié)構(gòu)的更改，而且還可以自動(dòng)沿用之前制定的規(guī)則，絲毫不用擔(dān)心后續(xù)步驟。比如，修改后的模型可自動(dòng)沿用之前制定的厚度和混合規(guī)則，設(shè)計(jì)人員無(wú)需進(jìn)行任何額外工作。事實(shí)上，這就是隱式數(shù)據(jù)結(jié)構(gòu)開(kāi)發(fā)設(shè)計(jì)的優(yōu)勢(shì)：保證快速、穩(wěn)健且保險(xiǎn)的重建。正如上文的描述，在設(shè)計(jì)人員完成修改后，工具將自動(dòng)沿用之前的規(guī)則，按照之前的工作流，生成逐步文件，直至最終生成生產(chǎn)所需的輪廓切片。
我們已經(jīng)在上文中詳細(xì)描述了設(shè)計(jì)或更改增材制造零部件的流程，而且也了解了設(shè)計(jì)人員在這種架構(gòu)下可以隨時(shí)回到之前中斷的地方進(jìn)行更改，非常靈活方便。
這種新型精簡(jiǎn)工程設(shè)計(jì)流程主要得益于隱式建模技術(shù)，允許設(shè)計(jì)人員隨時(shí)回到任何步驟進(jìn)行修改且無(wú)需擔(dān)心重建的工作量和穩(wěn)定性，并配置結(jié)構(gòu)角度，最終導(dǎo)出可以直接用于加工的切片文件。這不僅可以節(jié)省設(shè)計(jì)人員的時(shí)間，而且還可以消除設(shè)計(jì)修訂和迭代的障礙。
為了向世人呈現(xiàn)一款偉大的創(chuàng)新產(chǎn)品，戴森先生共花了十五年時(shí)間，完成了 5127 次迭代。如今，基于場(chǎng)的設(shè)計(jì)軟件的效率更高、學(xué)習(xí)更快，設(shè)計(jì)迭代速度出現(xiàn)了指數(shù)型增長(zhǎng)，之前十五年的工作現(xiàn)在可能僅需幾天就能完成。隱式工程工作流不僅可以安全地重構(gòu)增材制造零部件，還可以強(qiáng)力支持多個(gè)維度的早期設(shè)計(jì)探索，進(jìn)而助力增材制造工藝的廣泛應(yīng)用，并推動(dòng)未來(lái)產(chǎn)品制造方式變革的到來(lái)。
A new field-based design software is supporting more widespread use of Additive Manufacturing, for faster product development times with less rework and risk.
by Blake Perez
Most models and methods for design and innovation suggest that true innovation comes from not just a single event of inspiration, but rather the constant iteration and improvement upon an initial idea or design. James Dyson tested over 5,000 iterations of his product before releasing the company’s first bagless vacuum cleaner. The F-15 Eagle fighter jet models B, C, D, and E were all iterations of the original design. It’s clear that the ability to iterate leads to innovation and an inability to iterate leaves the exchange of risk for knowledge until the very end, when there’s little time left to make changes and innovate.
Truth is, iteration in design engineering can be difficult and expensive. Design revisions result in hours of rework and a duplication of effort when models fail due to geometric errors. No wonder there is a natural aversion to iterate even though its impact on product success is well understood.
Design for Additive Manufacturing is no exception. DfAM introduces even more manual rework in file translations, build configuration, and slicing steps when a design is altered. Often DfAM is left as an after-thought of engineering design. At this point, low-level changes are made to the as-designed part to enable self-supporting features or to add sacrificial volumes that can be machined away for dimensionally critical features. There are other changes that can be made to fully leverage the capabilities of additive manufacturing (AM), but such changes to a model might require other dependent features to be reworked. Again, this is time-consuming and expensive.
A typical workflow when designing for AM starts with a conceptual design that gets represented in CAD software and is translated step-by-step to ultimately be configured for manufacturing. Changes to the part’s design or geometry in CAD require significant rework in order to get back to a print-ready configuration. Iterating back through one of these stages has an associated cost due to the rework required to adapt the models at each subsequent stage.
Recent software advances introduce a more agile development framework based on implicit modeling where changes to a design compile and rebuild automatically. A single data platform replaces multiple streams of engineering knowledge, consolidating a wide variety file types. This removes the traditional barriers to iteration and innovation and connects design and manufacturing in a way that enables DfAM in a seamless fashion.
Beyond simple distance fields
Let’s see what a DfAM workflow on this new type of platform might look like for an engineered part. The design opportunity here is to lightweight and additively manufacture a brake pedal.
The workflow starts with the initial bulk model geometry. In order to lightweight this part, various lattice configurations are explored with the platform’s lattice tools. Each lattice type is thickened and joined to the original model, according to part’s strength requirements.
A common problem with additively manufactured lattice structures is delamination between the lattice and skin. To mitigate this, a rule is created to blend the lattice into the skin smoothly (Step 3). Thanks to distance fields in implicit modeling, this can be done globally and robustly without manually selecting every edge in the model as would need to be done with conventional tools. Traditional methods would require hours of tedious edge selection that would need to be repeated if changes are made to the geometry.
At this point, our team decides that we need the lattice’s thickness to vary as a function of distance from the main mounting point. A variable thickness lattice structure is added to the internal area. The thickness is driven from the implicit field emanating from a planar surface (the red line in the image). This strategy is meant to provide extra stiffness near the mounting point as we would expect the highest stresses at the interface. Again, distance fields allow us to specify this rule, and when we do, the rounds we specified in the previous step still regenerate.
With implicit modeling, we’re not just limited to simple distance fields to drive geometry. Any field can be used to intelligently drive the lattice’s mesostructure. Examples of usable fields include stress, thermal, and fluid simulation data. Practically, you can drive geometry with any data you have. In our brake pedal example, we’re going to use Von Mises stress data from the engineers to influence the thickness of the lattice.
Where higher stress values exist, the lattice elements are made thicker to provide strength where it is needed. This design workflow is enabled by systems built on implicit modeling, as fields are the foundational language in which component data is represented here.
Now that we have our brake pedal, the final step in creating additive-manufacturing-ready models is to create contour slices. A distance-field-based platform provides the freedom to generate and specify additive tool paths and scan patterns to deliver directly to machines without the use of intermediate STL files.
At this point in the design process, it’s traditionally very difficult to make design changes to the original model because such changes would set off a cascade of rework in modeling, build configuration, and slicing. With implicit modeling we don’t have the same constraints. We can make changes and trust the rules we made will still work. To demonstrate this, let’s consider a scenario where our engineering team brings simulation data to the table and is looking for a way to improve the design based on this new knowledge.
Normally, going all the way back to Step 2 of the design process to change the lattice type and/or geometry would be a major effort and possibly deemed infeasible due to time or resource constraints. Not only can this be done more efficiently with implicit technology but the other rules specified in the workflow will also automatically rebuild according to the new lattice geometry. All thickness rules and blends will still apply to the new model without additional work. This is the benefit of designing with an implicit data structure—rebuilds are fast, robust, and do not fail. And as before, the part will regenerate all the way to the contour slices that were specified in the initial workflow.
In this workflow, we showed constant progress towards an additively manufacturable part while still being able to iterate and make design changes that rebuild back to where we left off.
Streamlining the engineering design process in this new way enables robust rebuilding after changes to a design at any point. This ability is largely enabled by implicit modeling technology. Users have the ability to make upstream design changes that rebuild all the way down the design chain. They can also configure orientation and supports to export slices to send directly to a machine. Any upstream design changes will recompile all the way back to that point automatically. Not only does this save time for design engineers, but this also removes the barriers to design revisions and iterations.
James Dyson spent fifteen years completing the 5,127 iterations required to produce a great and innovative product. This kind of effort is now achievable in days with new field-based design software for exponentially reduced product development times. It’s possible to move quickly, gain deep product knowledge, and de-risk the whole product development effort. Connecting multi-dimensional, early-stage design exploration with an implicit engineering workflow that robustly rebuilds ready-to-manufacture parts is supporting more widespread use of AM and changing the way products are developed.
Author: Blake Perez
Source: AUTOMOTIVE ENGINEERING
迭代往往可以收獲創(chuàng)新，而拒絕迭代則可以免去獲得新知識(shí)可能承擔(dān)的風(fēng)險(xiǎn)，但這樣做的后果是，到最后即便想改變和創(chuàng)新，也將再無(wú)機(jī)會(huì)。但值得一提的是，迭代的成本相當(dāng)高。
典型增材設(shè)計(jì)的工作流（見(jiàn)上表）在對(duì)任何一步的修改都必須同時(shí)考慮其他步驟的修改成本。
隱式平臺(tái)工作流（見(jiàn)上表）可將多個(gè)功能知識(shí)來(lái)源集中至唯一的數(shù)據(jù)平臺(tái)，整合多種文件類(lèi)型。
