Fusing High Performance and Manufacturability with SDfM

As virtual simulation advances, innovation gets faster and becomes less costly.

Altair Inspire Form SDfM software. (Image source: Altair.)

Altair Inspire Form SDfM software. (Image source: Altair.)

Simulation technology is continually advancing to model increasingly real-world product behavior; however, many companies lag in its adoption.

A recent survey found that only 37 percent of respondents said they applied manufacturing simulation during the product design phase. The vast majority were checking product manufacturability only once the design was completed. Sometimes simulation was used even later after a product failure occurred. Lack of adoption of simulation-driven design for manufacturing (SDfM) is often due to a company’s cost concerns and lack of training and resources, despite managers being cognizant of its advantages.

However, by eschewing SDfM, companies are missing out on the ability to reduce product manufacturing costs, streamline the design process, ramp up production schedules and more efficiently deliver products to customers. These advantages that SDfM provides come amid increasing product complexity and consumer demand for faster time-to-market intervals.

“The manufacturability of a product can greatly affect the cost,” said Altair Vice President of Marketing Simone Bonino, who spoke alongside other presenters at the Future.Industry 2021 event in October. “If you are simulating early and often, you are really accelerating design. That’s when you see the value of a simulation-driven design for manufacturability approach. It enables generative design for all manufacturing processes with ease. It allows you to analyze complex assemblies with great accuracy. And it optimizes the design for manufacturability by selecting the best process early.”

Bonino said that Altair began introducing the simulation-driven design concept nearly two decades ago. Today, SDfM solutions cover a broad range of processes like 3D printing, casting, metal forming, injection molding, extrusion, process manufacturing, polyurethane forming, circuit boards and electronics, and composites—each with a different software product to enable the specialized simulation, such as the recently launched Inspire Mold for injection molding and Inspire PolyFoam for polyurethane forming.

Additionally, engineers can utilize the Altair Material Data Center to search or browse for materials, visualize material properties, compare material types, and get help with choosing the relevant simulation software and export simulation data files.

By starting very early in the development cycle, an array of products is well-suited to simulation. In addition, using SDfM as a first step in the process results in better performance and manufacturability because team collaboration, evaluation and rapid convergence are still possible, Bonino said. The technology also enables the evaluation of single and coupled physics performance, can be used to generate original designs for innovative products, and yields greater insights into the overall manufacturing process.

To illustrate the potential of SDfM, Altair Application Engineer Chen Meng spoke about predicting manufacturing feasibility for sheet metal parts using virtual methods. She began with an example of a metal battery holder part. The goal was to optimize the holder to maintain performance requirements even under extreme scenarios such as 3.6 Gs of load applied to the part in a hard braking scenario. In addition, other constraints were set for conditions to maximize stiffness and optimization, such as applying no more than 50 MPa of stress and having the first bending mode be greater than 85 Hz.

Instead of conducting a physical trial and error process to manufacture a battery holder that meets the stated goals, Meng advocated performing a systemic simulation to check the manufacturing feasibility during the design process to create a high-performing and manufacturable product while saving time and costs in the development cycle.

The sheet metal manufacturing process entails forming phases where a flat metal sheet is transformed into the final product in multiple steps. Generally, the process begins with a baseline sketch of the design, optimization of the design, design interpretation, manufacturing feasibility analysis and rapid validation—all hopefully resulting in high-performing and manufacturable products.

How the materials behave during the forming process will determine if the part is manufacturable. The behavior is revealed through stress data based on the mechanical properties of materials measured in tensile tests. For example, when a machine stretches a sheet, the deformation is initially elastic and reversible; however, the change could become irreversible if the sheet is extended further. Finally, extreme stretching can cause the sheet to break.

Material tests can determine the deformation limit that leads to the three most common manufacturing defects during sheet metal forming: splits, springback and surface defects. Splits occur when the material is pushed beyond its limits and becomes strained or broken. At the same time, springback defects are mainly caused by imperfections in the behavior of the elastic qualities of the material. Finally, surface defects include slight concave or convex marks. Surface defects are especially relevant for external parts like car doors and are caused by several issues such as too much pressure applied to the part or poor application of tools during the process.

The traditional design process relies on trial and error and corrects the defects with tools and design changes until the product is manufacturable. However, the redesign and rebuilding of tools are time-intensive and expensive processes. Conversely, using virtual simulations to predict the outcome of the formation phases can streamline the process.

According to Meng, there are two main methods for virtual simulation in metal sheet forming: the one-step method and the incremental method. The one-step method, also known as the inverse method, is usually implemented during the early product design phase. It works inversely to the physical process as it begins with the final part shape and then virtually flattens the part to its initial sheet shape.

Incremental or tryout sheet metal forming simulation method. (Image source: Altair.)

Incremental or tryout sheet metal forming simulation method. (Image source: Altair.)

“The final shape and the initial shape are output from the method,” Meng said. “Incremental steps are not calculated. The simulations are running very fast and are available in seconds.”

In the case of the battery holder, the one-step method allows for analysis of the formability or stress strength values under certain conditions. In addition, Meng said that it helps to identify potential manufacturing concerns caused by the design immediately.

The second method is called the incremental method or the tryout method. Unlike the one-step method, the incremental method virtually replicates the whole forming process from the beginning of the development phase to the physical tryout, including all the intermediate steps. This method provides an entire formation history from the flat sheet to the final state and shows how the sheets behave in the production of the battery holder. In the post-processing of the incremental method, it’s possible to check for defects like splits, unwanted wrinkles or excessive springbacks.

“With a predictive model, we can quickly analyze if there are means to correct a design or if we need to optimize the process parameters to prevent defects from happening,” Meng said.

Meng discussed the production of a car fender, in which the physical tryout process revealed a split defect around a sharp corner. However, she noted that the defect was already predicted by the Altair Inspire Form sheet metal forming simulation software at the exact same location, which showed that forming limits were exceeded in the critical region.

Split in car fender predicted by Inspire Form SDfM software. (Image source: Altair.)

Split in car fender predicted by Inspire Form SDfM software. (Image source: Altair.)

Such product failures can be caused by many factors such as limitations of the design itself, the material’s properties or issues that arise during the forming process. Simulation software like Inspire Form allows engineers to input their ideas and product information to understand how all the various factors influence manufacturability and reduce the cost and time of development.

While the two simulation methods yield vital data about manufacturability, Meng explained that both are generally used at distinct junctures in the design-development phases using sheet metal. Although physical verification is still ultimately required, it’s minimal when paired with simulation, which reduces the amount of trial and error required.

“It’s time to use the simulations, to use virtual methods for predicting manufacturability in your product design and process engineering,” said Meng. “That will make your product development easier and more efficient.”