<p>Textile industry has to often walk a tightrope between the efficiency and reliable production since from its evolution. Industrialists and entrepreneurs are spending a hefty amount to increase efficiency, reduced wastage and accelerate the production with optimum resources. The proposed research addresses the major road blocks related with the complexity and interconnectedness of combed-sliver production systems with a primary emphasis to build resilient infrastructure, fostering innovation and sustainable industrialization in the textile sector. Stochastic Petri nets is employed to model and simulate the dynamic interactions among subsystems, with computations performed using the licensed Petri module of the graphical interface for reliability forecasting (GRIF) software. Variations in failure and repair rates are used to analyze subsystem availability. Particle swarm optimization (PSO) technique is implemented for achieving the optimization and to leverage the specifically designed algorithm. By optimizing system availability, this research can contribute to reducing waste, improving overall efficiency, and enhancing the sustainability of the textile industry. The results find that the unilap machine is recognized as the most critical subsystem and carding machine is the least critical subsystem of the CSPS. The results of the present study have the potential to benefit textile manufacturers across the globe by providing practical guidelines for improving production system performance and reducing operational costs.</p>