Microcontroller-Based Variable-Spectrum LED Illumination for Industrial Ergonomic Optimization: A Controlled Experimental Investigation of Spectral Effects on Worker Productivity and Visual Comfort

Abstract

Industrial lighting systems have historically been engineered to satisfy photometric quantity requirements without
systematic consideration of spectral quality's influence on worker cognitive performance and visual fatigue. This study presents the
design, fabrication, and empirical validation of a microcontroller-governed, programmable variable-spectrum LED illumination
source and investigates its effects on two operationally representative industrial task paradigms: fine electronic component sorting
and screen-based data verification. Six distinct spectral conditions—Blue (450 nm), Green (530 nm), Red (640 nm), broadband
White (RGB), Purple (410–450 nm), and Yellow (575 nm)—were systematically administered to 18–20 adult participants per trial
within a photometrically controlled dark-room environment. Outcome variables included task completion time, accuracy rate, error
frequency, and subjective visual comfort ratings. Results demonstrated that broadband White (RGB) illumination produced superior
performance in precision-oriented tasks, achieving a mean completion time of 0:40 min:sec with 100% accuracy. Yellow
illumination yielded the lowest reported eye strain scores (1.8/10), identifying it as the preferred spectrum for prolonged-duration
sustained work. Blue monochromatic illumination consistently produced the weakest performance outcomes, including an 18.3%
accuracy deficit and completion times 132.5% longer than White (RGB) conditions for component sorting. These findings provide
a quantitative empirical framework supporting the adoption of adaptive, task-responsive spectral LED systems in precision
manufacturing environments and offer an evidence base for the revision of industrial lighting standards toward spectral quality
metrics.