MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541122621 A) filed by Malla Reddy (MR) Deemed to be University; Malla Reddy Vishwavidyapeeth; Malla Reddy University; Malla Reddy Engineering College For Women; and Malla Reddy College Of Engineering And Technology, Medchal-Malkajgiri, Telangana, on Dec. 5, 2025, for 'supply chain bottleneck detection system using real-time data streams.'
Inventor(s) include Dr. K. Maddileti; Dr. Syed Mohd Faisal; Dr. G. Mohan Ram; Mr. Votte Rajashekhar; and Dr A Nagaraju.
The application for the patent was published on Jan. 2, under issue no. 01/2026.
According to the abstract released by the Intellectual Property India: "This is a system disclosure related to an existing system that identifies emerging bottlenecks through various multi-tier supply chains analyzing live operational indicators. The conventional approach to planning uses batch data and fixed lead times and entails long delays in the awareness of congestion, material shortages, or logistics dividends. The suggested system processes the enterprise application and Internet of Things endpoints with high-frequency telemetry and transforms them to event streams and measures resources against capacity and service requirements. An operational streaming analytics layer are combined in operation with purchase orders, production signals, warehouse telemetry, and transport milestones, as well as having third-party risk indicators. Engine calculates queuingtime buildup, drift deviation and service level shirkage per node, per lane. Ranked alert types find the most impactful constraints, take measurements of impact window and propose mitigating levers. Primary causes are separated into a causality module such as causing drift in supplier cycles, disruption of equipment, or congestive port and separated by secondary effects such as propagation of the backlog. Outputs are described using traceable pieces of evidence: lated ASN pattern, missed scans of handoffs or capacity curves depletion. This facilitates quick cross- functional response and escalation. Changing current retrospective reporting to a more evidence-based detection that is constant in time turns the invention into a shortening of the time-to-awareness, stabilizes throughput, and decreases the expenditure of expediency in multi-enterprise, complicated networks."
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