Models in Engineering Design as Decision-Making Aids
Bibliographic Data
| ID | 12973455 |
|---|---|
| Authors | Claudia Eckert (0000-0002-2201-3828, The Open University, corresponding author), Rafaela Hillerbrand (0000-0002-7890-3715) |
| Year | 2022 |
| Volume | 14 |
| Issue | 2 |
| Pages | 134-157 |
| Publication date | 2022-05-04 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Engineering Studies (JOURNAL) |
| Journal identifiers | ISSN: 1937-8629 • E-ISSN: 1940-8374 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/19378629.2022.2129061 |
| OpenAlex | W4298393524 |
| Language | EN |
| Citations received | 3 |
| References cited | 37 |
Although models and modeling are central to engineering design, they have received much less attention than models or modeling in the philosophy of science. This paper draws on insights from the philosophical literature on models in science to elucidate models in engineering. Many of the apparent differences are a matter of degree. Models in engineering design do not function solely as representational or more general epistemic vehicles. Rather, models are central to facilitating decision making. This seems to be less pronounced in laboratory practices for scientific research than in engineering design. In engineering, often only the designers understand and determine the relation between the model and its target system. In this, they serve as truth makers and truth keepers. This social process of design is essential to understanding the role of models and modeling from a meta perspective, but is also relevant to engineer when models are reused. A better understanding of these roles can help to illuminate the roles of models in engineering. To illustrate these points, this paper uses the design of a 3D printed kayak as an example that shows how even a fairly modest engineering design project requires the creation of a multitude of different models
Engineering design process · Epistemology · Function (biology · Management science · Multitude · Perspective (graphical · Process (computing · Relation (database · Systems engineering · Cognitive Science and Education Research · Computer Science · Design Education and Practice · Engineering · Philosophy and History of Science · Artificial Intelligence
Mimesis as make-believe
How the Laws of Physics Lie
Error and the Growth of Experimental Knowledge
Models as Mediators
Scientific representation
The reflective practitioner
Modeling Organs with Organs on Chips
Against Ambiguity
Mind the Gap
Informational versus functional theories of scientific representation
Models, Representation, and Mediation
Logic, Methodology and Philosophy of Science
Who is a Modeler
The Strong and Weak Senses of Theory-Ladenness of Experimentation
The dialectics of sketching
| Citations per year | 1 |
|---|---|
| Citation span | 2023 - 2026 (4) |
| Highly cited | No |