A Multi-Criteria Framework for Comparative Evaluation and Robust Ranking of Fiber-Optic Gyroscopes
Nurzhigit Smailov, Yerlan Tashtay, Maral Abulkhanova, Daulet Naubetov, Kanat Zhunussov, Sauletbek Koshkinbayev, Beibarys Sekenov, Aziskhan AmirComparative evaluation of commercially available fiber-optic gyroscopes (FOGs) is complicated by heterogeneous technical specifications and the methodological assumptions underlying multi-criteria ranking. This study develops and systematically evaluates the Fiber Optic Gyroscope Performance Index (FOGPI), a six-criterion, specification-based framework integrating Bias Stability, Angle Random Walk, Maximum Input Rate, Bandwidth, Operating Temperature Range Width, and Power Consumption. The framework employs normalized technical characteristics and explicitly defined engineering preference weights and is applied to eleven commercial FOG models. Its methodological sensitivity is examined through linear, logarithmic, and fixed-reference normalization; local and global weight sensitivity analyses; mission-oriented Analytic Hierarchy Process (AHP) scenarios; intercriterion correlation and CRITIC weighting; leave-one-out analysis; hypothetical Monte Carlo input perturbations; and comparison with TOPSIS and VIKOR. Under baseline linear Min–Max normalization, DSP-1760 achieved the highest FOGPI score (0.816965). However, logarithmic normalization of accuracy-related criteria changed the highest-ranked device to S-F120HA, while increasing the Accuracy group weight beyond approximately 0.592 produced a similar rank reversal. Global weight-space analysis showed that DSP-1760 occupied first place in 50.72% of uniformly sampled configurations, compared with 87.39% under baseline-centered sampling. FOGPI and VIKOR produced identical rankings, although their agreement does not constitute independent validation because of their mathematical relationship. Application-specific screening further demonstrated that aggregate rankings cannot replace mandatory technical requirements. The findings establish FOGPI as a transparent decision-support framework whose rankings depend on normalization, weighting assumptions, comparison-set composition, and the comparability of manufacturer-reported specifications, rather than as an absolute measure of gyroscope performance.