In recent years, intelligent reflecting surfaces (IRS) have emerged as a groundbreaking technology for enhancing spectral and energy efficiency in wireless communication, offering a cost-effective and energy-efficient solution. This study explores a simultaneous wireless information and power transfer (SWIPT) network employing time-switching (TS) receivers, where a base station (BS) transmits both data and energy signals to users with the assistance of an IRS. By appropriately tuning the phase shifts of IRS elements, transmission performance is optimized in terms of both energy harvesting and data efficiency. The primary objective is to maximize energy harvesting efficiency, defined as the ratio of total harvested energy at the users to the transmission power of the BS, while ensuring the required information rate, adhering to power constraints, and considering practical limitations on phase shifts. To tackle this challenge, an iterative algorithm incorporating non-convex approximations is developed to jointly optimize information beamformers, energy covariance matrix, and TS factors. Finally, numerical simulations validate the convergence and effectiveness of the proposed methodology.