The wastewater amount generated by the semiconductor industry has come under strong environmental scrutiny recently. Micro/Nanoelectronic processes consume millions of gallons of water daily to rinse microscopic dirt and chemicals from the surface of chips. Land disposal of these types of waste are prohibited unless they are pretreated to the standards. Current emphasis is being placed on reducing the amount of waste produced. However, until a more suitable means of production is established, the waste stream must be treated. Different conventional as well as membrane processes are being used. However, these processes are either energy inefficient or involve different chemicals. In order to overcome this problem, it has been proposed to use membrane distillation as an efficient technique for waste water treatment [1]. The present work purposes to identify if Membrane Distillation (MD) can substitute present separation technologies for waste water treatment in semiconductor industries or can be implied as a needed add-on. It is tested for recovery of valuable/rare metals from waste as well as to achieve a clean product. For experimental analysis, Xzero’s AGMD modules have been used in order to find out the feasibility of this advanced wastewater treatment technique. Industrial data and waste water samples have been collected from imec. Wastewater typically includes varying amounts of surfactants, photoresists (polymers and sensitizers), cleaning agents (isopropyl alcohol), stripping agents (2-propanol amine), developing agents (methanol amine and glycol ether) and other organics (methanol and dyes). Critical operating parameters (flowrates, temperatures) are varied in order to analyze the quality and flowrate of distilled water. By following the results, bottle necks are identified for modification and optimization purposes. It is recommended to integrate MD module with solar energy to make the process more sustainable, environmental friendly and energy and cost efficient. Future work will be focused on techno-economic evaluation of solar energy integrated MD modules using Aspen Plus.