Authors: Cooley/Group Process Engineer | Pranav Kolapkar
Source: Frontiers in Emerging Engineering & Technologies (article, 2026-01-01)
Field: Materials Science — Polymers and Plastics

An Integrated Framework for High-Performance Rapier Loom Weaving: Mechanics, Automation, and Quality Analytics The increasing digitalization and automation and decreasing mechanization and human controlled operation of textile manufacturing shows need for weaving systems that synthesize mechanical precision with advanced monitoring and analytical capabilities. Among contemporary weaving technologies, rapier looms, especially Dornier models exhibit distinctive advantages in weft insertion accuracy, shedding stability, and compatibility with high performance technical yarns. Furthermore, sustaining fabric quality at elevated production velocities requires a holistic optimization paradigm that accounts for the interdependence of loom mechanics, operational data, and constructional parameters. This study proposes a comprehensive and integrative framework for performance optimization of Dornier rapier looms, unifying mechanical modeling, program calibration, cyber-physical monitoring, and predictive analytics. It also shows Overall equipment effectiveness increases from 59.5% to 80.3%, and Grade-A roll output increased from 71% to 96% primarily attributable to reduced setup time, stabilized mechanical operating envelopes, and early defect anticipation. The framework formally characterizes critical mechanical subsystems—including rapier kinematics, beat-up force dynamics, warp-tension behavior, and shedding motion trajectories—and evaluates their implications for fabric stability, defect generation, and process robustness. Complementing this mechanical analysis, the research incorporates supervisory control and data acquisition (SCADA) dashboards and overall equipment effectiveness (OEE) metrics to quantify real-time operational efficiency, diagnose bottlenecks, and facilitate condition-based maintenance strategies. Furthermore, a statistical defect-prediction model is employed to anticipate recurrent weaving faults such as mispicks, double picks, warp breaks, width variation, slubs, rapier miss, color breaks and mass irregularities, enabling anticipatory process correction rather than reactive troubleshooting. The proposed framework is validated through the integration of simulation outputs, engineering diagrams, OEE visualizations, and the complete weaving specification for construction FN52151680D90W-74(Fuel tank product). Empirical results demonstrate significant improvements in loom efficiency, defect minimization, and operational repeatability when employing the unified methodology. By shifting from heuristic, operator-dependent tuning to a scientifically grounded, data-augmented approach, this research provides a pathway for modern weaving enterprises to enhance performance consistency, accelerate setup cycles, reduce waste, and strengthen the resilience of high-speed weaving operations. Construction FN52151680D90W-74 and application context. The construction code FN52151680D90W-74 denotes a proprietary technical-textile weaving specification used for an automotive fuel tank reinforcement (fuel tank bladder) application. The code encapsulates application family, yarn configuration, reinforcement level, weave architecture, and target dimensional characteristics, serving as an internal manufacturing identifier that links fabric design intent to loom setup parameters and quality criteria. In fuel-system applications, woven fabrics function as structural reinforcement layers within flexible or semi-flexible fuel tank assemblies, where tight control of weave geometry, areal mass uniformity, width stability, and defect incidence is required to support downstream compliance with automotive fuel-system safety and durability requirements. LOOM ; Weaving ; Process (computing) ; Automation ; Analytics ; Data acquisition ; Quality (philosophy) ; Overall equipment effectiveness ; Data modeling Textile materials and evaluations ; Structural Analysis and Optimization ; Mechanical Behavior of Composites