This review discusses the current state of silicon solar cell manufacturing, focusing on the value chain from feedstock production to solar cell fabrication, including recycling and the use of artificial intelligence (AI). Silicon-based solar cells dominate the market, with over 90% of commercial solar cells being silicon-based. The review highlights the main manufacturing techniques for silicon ingots, specifically the Czochralski and directional solidification methods, and discusses the challenges in silicon ingot production, such as optimizing production yield, reducing costs, and improving efficiency. It also reviews recent developments in solar cell technology, including new trends and the role of recycling in sustainability. The review emphasizes the importance of AI and machine learning in addressing challenges in the PV industry, such as structure loss in silicon ingots, solar cell design optimization, and advanced defect characterization. AI and machine learning are shown to have significant potential in improving the efficiency and operational efficiency of the PV industry. The review concludes that silicon solar cells are continuously evolving, with a focus on improving cell efficiency and sustainability. AI is expected to play an increasingly important role in the PV industry and research.This review discusses the current state of silicon solar cell manufacturing, focusing on the value chain from feedstock production to solar cell fabrication, including recycling and the use of artificial intelligence (AI). Silicon-based solar cells dominate the market, with over 90% of commercial solar cells being silicon-based. The review highlights the main manufacturing techniques for silicon ingots, specifically the Czochralski and directional solidification methods, and discusses the challenges in silicon ingot production, such as optimizing production yield, reducing costs, and improving efficiency. It also reviews recent developments in solar cell technology, including new trends and the role of recycling in sustainability. The review emphasizes the importance of AI and machine learning in addressing challenges in the PV industry, such as structure loss in silicon ingots, solar cell design optimization, and advanced defect characterization. AI and machine learning are shown to have significant potential in improving the efficiency and operational efficiency of the PV industry. The review concludes that silicon solar cells are continuously evolving, with a focus on improving cell efficiency and sustainability. AI is expected to play an increasingly important role in the PV industry and research.