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Optimizing Boiler Manufacturing Lead Time: AI-Powered CRM for Streamlined Order Processing and Supply Chain Coordination

Venkata Saiteja Kalluri

Abstract


In the dynamic and competitive landscape of manufacturing, boiler production remains a time-sensitive and highly customized domain where reducing lead time is crucial for maintaining competitiveness. This study investigates the integration of Artificial Intelligence (AI) and Customer Relationship Management (CRM) systems as a strategy to streamline order processing and supply chain coordination in boiler manufacturing. By examining real-time data analytics, predictive maintenance, AI-based scheduling, and CRM-enabled customer intelligence, the research explores how lead time can be significantly optimized. Drawing on extensive literature and emerging best practices, the paper proposes a comprehensive AI-CRM model that connects operational and customer-facing systems for end-to-end efficiency. The outcomes reveal notable improvements in procurement timing, production agility, order fulfillment accuracy, and customer responsiveness. The findings contribute to developing scalable, intelligent frameworks for manufacturers seeking digital transformation.


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References


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