• Satish Kumar Nalluri
• Varun Teja Bathini
• Adeoye Ibrahim

The integration of Robotic Process Automation (RPA) and Microsoft Power Automate with Siemens’ Camstar Manufacturing Execution System (MES) is transforming manufacturing workflows by streamlining operations, enhancing productivity, and reducing operational costs. This study investigates the impact of this integration on manufacturing efficiency, cost savings, and scalability. A mixed-methods approach is employed, combining qualitative case studies and quantitative performance metrics analysis from various industries. The research demonstrates that the integration of RPA and Power Automate with Camstar MES improves data accuracy, reduces manual intervention, and accelerates production processes. Results from case studies indicate significant cost savings, enhanced system scalability, and improved decision-making due to real-time data analytics. While the integration presents challenges, such as system compatibility and employee training, the benefits of streamlined workflows and operational agility outweigh these obstacles. This paper concludes with recommendations for manufacturers seeking to adopt automation technologies, emphasizing the need for careful planning, stakeholder engagement, and continuous monitoring to ensure successful implementation. By adopting RPA and Power Automate, manufacturers can achieve a more agile, efficient, and cost-effective production environment

MES(Manufacturing Execution Systems), Camstar, RPA, Power Automate, Analysis, research.

"Streamlining Manufacturing Workflows: Integrating RPA and Power Automate with Camstar MES ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.d738-d746, May-2025, Available :http://www.jetir.org/papers/JETIR2505428.pdf

"Streamlining Manufacturing Workflows: Integrating RPA and Power Automate with Camstar MES ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppd738-d746, May-2025, Available at : http://www.jetir.org/papers/JETIR2505428.pdf