Damien Motte’s research while affiliated with Lund University and other places

We have, so far, mostly been talking about using AM for direct part production. However, many industries are now starting to use AM as a way of manufacturing the tooling for conventionally injection molded, cast, extruded, or sheet-metal parts. This means that the final parts are exactly the same as those that they would have previously made with conventional tooling, and only that the tooling, itself, was produced with AM. This makes it relatively easy for engineers to accept the technology, as the produced parts are identical (or better) to the parts they are used to.

This chapter covers activities that are, typically, outside the designer’s influence, but impact the quality of the final part produced.

The design guidelines below apply to laser powder bed fusion metal processes. The guidelines will vary from machine manufacturer and model to machine manufacturer and model so, if in doubt it is recommended to print a test piece to verify each set of design parameters.

Always design with the following thought in mind: With the function I am trying to achieve, what is the simplest possible configuration of part(s) that I can print in an orientation to avoid anisotropy? This thought often leads to good possibilities for part consolidation.

There are several possible purposes for using simulation tools related to AM. The first aim, just as with traditional design analysis, is to simulate the behaviour and performance of a virtual design, and to use this information to either manually or automatically improve the design according to some given criteria. This avoids the time-consuming and costly step of manufacturing a prototype and setting up test rigs, thus enabling rapid iteration in the design process. The second aim is to simulate the physical build process to aid in finding an optimal build orientation, support structures, material properties or to compensate for distortions.

The design guidelines in this section apply to almost all polymer AM technologies. Some technologies have specific guidelines that apply only to that technology, and these are discussed in the chapter on design guidelines for specific AM processes.

Design for additive manufacturing (DfAM) is when designers seek to create a product design that takes advantage of the unique capabilities of AM. DfAM also respects the specific process constraints of the AM technology that will be used to produce the product. This goes beyond merely re-designing existing parts for AM. Re-design for AM is useful because it can yield benefits such as a reduction in the use of material or the consolidation of several parts into one. However, what it fails to do is to consider the added benefits that AM can bring to an entire product through improvements in form, fit, and function. This book seeks to encourage engineers and designers to consider the strategic benefits of AM before concentrating on detailed design. Design for AM is definitely more of a thought process in which conscious decisions are made (often compromises) rather than just blindly following a set of design rules.

Additive manufacturing is developing very rapidly. Every few months we see new technologies, new materials, new software, and new AM products coming to market. It is of great importance to those with an interest in AM to keep abreast of some of the upcoming developments as they will, without doubt, affect how we develop future products.

Additive Manufacturing (AM) is a technology that, while removing many of the constraints of traditional manufacturing, imposes some new constraints of its own. Because of this, engineers and designers need to be taught a new set of skills in design for additive manufacturing (DfAM) in order to become competent in designing parts that maximize the benefits offered by AM. Around the world, universities and organizations are beginning to offer courses in DfAM to improve the skills of modern engineers and designers. Staff at Lund University, in Sweden, have begun to offer such DfAM courses to industry that use problem-based learning (PBL) as the pedagogical approach to teaching DfAM in a more effective way. This chapter describes how these courses have been implemented, and how they have benefitted from the PBL teaching approach.

In most industrial product development projects, computer-based design analysis, or simply design analysis, is frequently utilized. Several design analysis process models exist in the literature for the planning, execution and follow-up of such design analysis tasks. Most of these process models deal explicitly with design analysis tasks within two specific contexts: the context of design evaluation, and the context of design optimization. There are, however, several more contexts within which design analysis tasks are executed. Originating from industrial practice, four contexts were found to represent a significant part of all design analysis tasks in industry. These are: 1. Explorative analysis, aiming at the determination of important design parameters associated with an existing or predefined design solution (of which design optimization is a part). 2. Evaluation, aiming at giving quantitative information on specific design parameters in support of further design decisions. 3. Physical testing, aiming at validating design analysis models through physical testing, that is, determining the degree to which models are accurate representations of the real world from the perspective of the intended uses of the models. 4. Method development, that is the development, verification and validation of specific guidelines, procedures or templates for the design analyst and/or the engineering designer to follow when performing a design analysis task. A design analysis process model needs to be able to deal with at least these four. In this work, a process model named the generic design analysis (GDA) process model, is applied to these four contexts. The principles for the adaptation of the GDA process model to different contexts are described. The use of the GDA process model in these contexts is exemplified with industrial cases: explorative analysis of design parameters of a bumper beam system, the final physical acceptance tests of a device transportation system (collision test, drop test, vibration test), and the method development of a template for analyzing a valve in a combustion engine. The “Evaluation” context is not exemplified as it is the most common one in industry. The GDA process model has been successfully used for the four contexts. Using the adaptation principles and industrial cases, the adaptation of the GDA process model to additional contexts is also possible.