Our goal was to create a comprehensive Injection Molding simulation package in Fusion 360 Simulation workspace that would uniquely leverage the existing Moldflow simulation technology and introduce new innovative workflows. Enabling current and new Fusion 360 users to meet their design objectives whilst ensuring the part meets performance requirements.

According to our prior research, there is a diverse range of personas within the design-to-manufacture process. By analyzing our data, we identified an opportunity to concentrate on the partnership between two specific personas in the industry: Maria, the industrial designer, and Thomas, the mechanical engineer simulation analyst.

We conducted a Qualtrics survey to validate our preliminary hypotheses and better understand the issue. Then we organised a design sprint where we collaborated with internal stakeholders and experts to delve further into the problem and initiate the ideation and testing of potential strategic solutions.

The outcome of the design sprint

Intent* - How might we effectively capture a user's design intent to ensure that the final product accurately reflects their needs and desires?

Guidance* - How might we use real-time manufacturing advice to empower engineers to make informed decisions and drive continuous improvement in their design?

 Automation*- How might we optimize the use of automation in the design-to-manufacture process to reduce costs and improve quality?

Collaboration* - How might we foster a culture of collaboration to drive innovation and continuous improvement in the design-to-manufacture process?

Design Advisor

We imagined a future where Maria (the Part Designer) could seamlessly design and receive real-time manufacturing advice to help her make critical design decisions in all stages of her design process.  

Automatic validation

What if we could run a simulation analysis in the background and notify our users at the right moments? We envisioned a simulation view that felt like a playground where Maria (the Part Designer) could easily interpret results, and we guided her on the right path as she collaborated with Thomas (the Simulation Analyst).

A global storyboard research protocol was undertaken to address the following objectives. 

• Build a deeper understanding of the profiles involved in the different stages of the design-to-manufacturing workflow. Specifically, learn more about their attitudes, challenges, and demographic background.
• Measure perceived customer value for the Design Adviser and Automatic validation concepts from the perspective of both the Industrial Designer and Simulation Analyst users.
• Understand whether the industrial Designer will collaborate with the Simulation analyst when evaluating the manufacturability of their part designs.

Key Research Findings

The findings confirmed the initial persona profiles but also revealed a new persona that bridges the gap between the Industrial Designer and Simulation Analysts. This persona, Joana, a Mechanical Design Engineer, is a plastic part designer with basic injection molding simulation expertise, focusing on the overall design and core internal components. This revealed a new persona shifting our target generalist persona.

Both concepts were validated successfully and branched internally into two funded initiatives – Design Advisor and Fusion Injection Molding. My team continued envisioning a new Injection Molding simulation solution in Fusion 360. The Design Advisor initiative was assigned to another team we worked closely with throughout the process.

We conducted ongoing research with another 100 participants using various protocols to validate the complete workflow through low-fidelity prototypes for Joana (Mechanical Design Engineer -Generalist user) and Thomas (Simulation Analyst - Advanced user). The customers perceived the workflows as highly valuable, allowing us to generate further ideas and strengthen each stage of the workflow.

Setting up your design

Placing an Injection Location 

Problem: Injection locations involve defining where plastic material will be injected into the mold. Customers using Moldflow faced challenges correctly positioning injection locations and desired a more efficient way to place multiple injection points at a given time.

Solution: We aimed to allow our customers to add multiple locations by enabling them to move the originally placed location easily through a simple push-and-pull action. Additionally, we wanted to ensure that the injection location would always be visible, regardless of the model’s orientation in the canvas.

Specifying visually important faces  

Problem: During our research, visual defects were ranked as the top manufacturing issue customers were asked to resolve. The users understand which faces must not have visual defects while designing a part.

Solution: We developed the "Aesthetic Faces" feature that enables users to define faces with high aesthetic requirements that should be free from blemishes, like the outer faces of Dyson vacuum machines or the outer shells of computers. This allowed users to designate these faces during the setup environment, enabling the simulation analysis to take note of the selection.

Let’s imagine we have gone through the complete set-up process where we have specified the injection location, aesthetic faces, process settings and material. Now, all we have to do is run the analysis.

Summary Log

Problem: When running an analysis, customers might have had to wait hours/days for a complex setup to complete, where they are left waiting for a lengthy period, nor do they have access to any in-progress results. They did, however, have access to summary log data. Previous customers felt the Summary log data could be challenging to understand and interpret, especially for users who are not familiar with the simulation process (it looked like it was data coming from the matrix).

Solution: We created the Summary Overview, where the data is summarized for the user in a dashboard format that outlines the different phases of the complete injection molding process. In the overview of the study data, you can animate the process and view the data as it changes over time. You can also see the Guided Results interpretations and access the Guided Results for Next Steps suggestions once a result is completed.

Now, let’s imagine the results are completed and ready for review. We will launch the results environment.

Guided Results

Problem: The generalist personas may not know how to interpret the simulation results regarding the part's performance or potential defects. Previously, the results were presented in various visualisations, such as rainbow plots, that could be overwhelming for users who are not familiar with Injection Molding simulation.

Solution: We stepped back, reflected upon our research findings, and thought, what does Joana care about? Joana wants three simple questions answered:

1. Will the part fill?

2. Will the part have sink marks and weld lines in aesthetically important areas?

3. Will the part have problems with excessive warpage?

We designed a workflow called Guided Results that automatically answered the questions for our users and guided them on their next step in resolving any problems that may occur.

In the scenario above, the Guided Results panel automatically analyzes the filling of the part. It provides recommendations for optimising the design to improve filling and reduce the risk of voids and other defects by simplifying the workflow through a traffic light analogy to give users a more precise answer.

1.              Easy to fill

2.              Difficult to fill or may have quality problems

3.              Unlikely to fill or will have quality problems

4.              Will not fill

Let’s inspect the results in more detail. 

Cutting Planes

The Cutting planes command creates cross-sectional views, which can be useful for users to evaluate the inner areas of simulation results that cannot be visible on the surface. Our goal was to create an intuitive way of using the tool, where the user can select a starting XYZ plane and move it to any desired inner section.

We thought to ourselves, what if it was easy as cutting a slice of cake? 

Flatness

Additional customers also wanted the ability to inspect their warpage analysis, as warpage results aren’t as straightforward; the warpage changes depending on the part's orientation. We sat down with 20 simulation domain experts and explored various strategies to take.

 We quickly realized that the problem was more complicated than anticipated, so we tackled it comprehensively and re-examined our key research outcomes to answer the essential questions Joana might want to address during her design process. 

1. How will my part sit flat on a table?

2. How will parts join in an assembly?   

To answer these fundamental questions, we created the warpage flatness tool to help users calculate the maximum deviation of the part from a flat plane. The user selects a flat surface (which we highlight by default), and we display the results in a colour map, allowing users to identify areas on the flat surface where warping is likely to occur. 

Compare View

Users require an effective way to assess the various simulation result scenarios and compare their differences to aid in making informed decisions.

The compare view allows users to compare multiple scenarios; users can spot trends in the simulation results, identifying the causes of any issues that may arise. Users can select 2-4 split screens and select results independently through the top switcher. The active window is highlighted in blue, enabling the user to apply controls, such as synchronizing inspection tools, to all windows.

Learnings

Rather than creating a barrier to entry by offering complex solutions exclusively to advanced users, we should aim for inclusive experiences that allow users to choose the level of information they need.

The success of this large-scale project heavily depended on effective collaboration, where team members were encouraged to think freely and create an environment that promoted stakeholder trust and transparency.

Vielen Dank!