Level: Intermediate
Donald McCormack, JMP Technical Enablement Engineer, SAS
Hadley Myers, JMP Systems Engineer, SAS
Christian Kaufmann, Principal Scientist, Competence Centre Thin-Film and Nanotechnology for Photovoltaics
Muhammad Saif Ullah, Researcher, Pakistan Institute of Nuclear Science & Technology
Tobias Bertram, Postdoctoral Researcher, PVcomB
Rutger Schlatmann, Professor, Hochschule für Technik und Wirtschaft
Data taken across continuous measurement ranges are usually expressed as sets of summary statistics, surrogates for real-valued continuous relationships. Attempts made at understanding complex processes through standard modeling techniques linking predictors and responses are then complicated by the abstraction caused by these surrogates. This risks omitting critical features and leaves no ability to draw temporal- or spectral-dependent conclusions. Many such examples are found in semiconductor and photovoltaic manufacturing, where advancements are largely dependent on gained knowledge from measurement and metrology techniques involving a continuous sweep of any physical phenomenon, including voltage, wavelength, temperature, sputtering depth, magnetic field strength, diffraction angle, etc. The Functional Data Explorer in JMP Pro offers a solution in which scalars can be extracted from continuous data to be used in subsequent modeling steps that somehow retain the functional aspect of the data. This presentation explores a use case where FDE was used in the study of photovoltaic devices, thus revealing insights which were previously unknown and could not have been uncovered using traditional analysis methods.