Open and inexpensive hardware has the potential to revolutionize the creation and deployment of sensors and other scientific instruments, expanding access and lowering barriers to innovation in data-driven research methods. Much of the activity within the open hardware movement has been on expanding the distributed production of hardware, through tools like the open licensing of hardware design and the creation of open 3-D printing templates for instrument parts. There has been comparatively less emphasis, however, on how to measure and ensure quality control in a distributed production process. The widespread availability of inexpensive sensors will only revolutionize science, after all, if the sensors actually work.
This project by University of Washington researcher Nadya Peek will improve our understanding of quality control in distributed manufacturing processes. Over the course of the grant, Peek will engage in four streams of activity aimed at filling gaps in current open hardware calibration practices. First, she will develop a generalizable format for documenting the theoretical capabilities of a production machine like a consumer-grade 3D printer. Second, once this format is created, Peek will use it to develop calibration software capable of verifying that a specific instance of that machine is performing to expectations and within acceptable error parameters. Third, Peek will develop new software to monitor such machines in real time, ensuring that they are maintaining precision and calibration through the production process. Fourth, she will develop low-barrier procedures for testing the precision and quality of the final output. In addition, Peek will also field a survey questioning how researchers in the open hardware community are adapting their distributed production processes in response to the shutdowns caused by the COVID-19 pandemic.