Reverse Engineering Through a Product Teardown Activity and Component-Function Identification
Abstract Engineering educators have used reverse engineering activities as a pedagogical tool for decades. Product teardowns allow students to experientially learn how a product works and what components lie hidden inside of an engineered product. These activities help shape students’ mental models and bolster their systems thinking abilities. This study examines the impact of a product teardown activity on upper-level engineering students’ mental models of everyday products. Students’ mental models of three common products were measured through a direct elicitation method before and after taking apart a hair dryer. In addition, students identified the system’s components and assigned functionality to each. Results suggest no change in observed score between pre and post mental models for any of the three tested products, which implies that knowledge transfer is not occurring. In addition, the product teardown activity is shown to have a positive impact on component identification, but a negative impact on functional reasoning. Specifically, improvements in motor inclusion are observed, which suggests that a product teardown activity helps break from existing schema (treating a fan-motor assembly as a single component) that lead to erroneous mental models. These findings illustrate the importance of reverse engineering on the development of robust mental models of engineered systems, but also show a negative impact on functional reasoning and no evidence of knowledge transfer between systems as was otherwise expected. The results of the study build on prior work by providing a more nuanced analysis of the specific components and functions included on mental model representations of common products. The implications of these findings, comparisons to prior literature, and a description of future work are discussed.
Authors
- Alexander R. Murphy (ORCID: https://orcid.org/0000-0001-8806-6378)
- Mikala Y. Furiato
Institutions
- Florida Polytechnic University (US)
Publication Details
- Published
- 2024-08-25
- DOI
- https://doi.org/10.1115/detc2024-143793
- Primary Topic
- Manufacturing Process and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00