Simulating Robust Processing with Design of Experiments, part 1

Guest Blogger 24 October, 2014

by Jasmin Wong, guest blogger

The combination of statistical methods and injection moulding simulation software gives manufacturers a powerful way to predict moulding defects and to develop a robust moulding process at the part design phase. 

CAE (computer-aided engineering) is widely used in the injection moulding industry today to improve product and mould designs as well as to resolve or troubleshoot engineering problems. But CAE can also be used to carry out in-depth processing simulations, allowing the critical process parameters that influence part quality to be identified and to enable determination of an appropriate and achievable process window at the earliest stage of the development process.

injection-molded dispenser pump

Warpage and tube concentricity were the key
quality criteria in this mold-injected hand dispenser pump.

In order to produce good quality injection mouldings with high consistency, a well-designed part and mould is critical, along with the selection of the right material and processing parameters. Changes to any of these four factors can have a significant effect on the moulded part.

With regard to defining process parameters, the injection moulding industry has been dependent on experienced process engineers using trial-and-error methods. Without the insight into polymer behaviour inside the mould, more often than not engineers would ‘process the part dimensions in.’ Such an approach typically leads to a narrow process window, where just a slight change in processing conditions can cause part dimensions to fall outside of the specification limit. This trial-and-error method is also laborious, expensive, and frequently ineffective, making it unsuitable for today’s fast-moving plastics processing industry.

Plastic injection moulding simulation software such as Moldex 3D from CoreTech System can help in the validation and optimisation of the part and/or mould design by identifying potential moulding defects before the tool is manufactured. The software can reduce the need for expensive prototypes, minimise the cost of tooling (since less rework needs to be done), and shorten validation time. When combined with the Design of Experiments techniques available in statistical software such as Minitab, doing simulation ahead of real world mould trials can also be used to speed mould approval. 

The Design of Experiments (DOE) Approach

Design of Experiments, or DOE, involves performing a series of carefully planned, systematic tests while controlling the inputs and monitoring the outputs. In the context of injection moulding, the process parameters are usually referred to as the factors or inputs, while the customer requirements (part quality/dimensions or other part specifications) are referred to as responses or outputs. By analysing the results from these tests, moulders can characterise, optimise and/or troubleshoot the injection moulding process effectively and efficiently.

By applying DOE in an injection moulding simulation, designers and/or moulders can study the relationship between the moulding factors (inputs) and response (outputs) prior to the actual trial on the mould floor. This means that they can have a good understanding of which factors will affect the quality or certain part specifications as early as possible in the development process. Optimal moulding process conditions for the specific part design can then be identified so the focus can be directed to the conditions that have the biggest influence on the customer’s requirements. This can save time and increase productivity.

When Should Simulation Be Performed?

Ideally, CAE simulation should be carried out before the actual mould trial so potential mould defects—such as sink marks, weld lines, short shots, etc.—can be predicted and rectified in the original mould design.

The most challenging problem is often warpage. Due to temperature variations and differences in volumetric shrinkage, it is almost impossible to get a part which is exactly the same as the CAD model. It is, therefore, important to conduct a DOE to understand the impact certain processing parameters have and to define the optimum processing settings.

Before the DOE is conducted, however, it is important to carry out a preliminary simulation to understand the root cause of mould defects. Changes to the part are sometimes inevitable to avoid having too narrow a process window to work within. If the fill pattern is not balanced, for example, there is a high possibility of warpage occurring regardless of the process parameters.


The second half of this two-part post includes a detailed case study illustrating how moulding simulation software and design of experiments can be combined to speed part design and approval


About the guest blogger

Jasmin Wong is project engineer at UK-based Plazology, which provides product design optimisation, injection moulding flow simulation, mould design, mould procurement, and moulding process validation services to global manufacturing customers. She is an MSc graduate in polymer composite science and engineering and recently gained Moldex3D Analyst Certification.


A version of this article originally appeared in the October 2012 issue of Injection World magazine.