Dell products l.p. (20240303714). METHOD AND SYSTEM FOR GENERATING SUPPLY RECOMMENDATIONS simplified abstract
Contents
METHOD AND SYSTEM FOR GENERATING SUPPLY RECOMMENDATIONS
Organization Name
Inventor(s)
Indranil Chakraborty of Bangalore (IN)
Madan Kumar Manjunath of Singapore (SG)
Vignesh Sundararaj of Guelph (CA)
Madhura Ganguly of Singapore (SG)
James Chen of Taipei City (TW)
METHOD AND SYSTEM FOR GENERATING SUPPLY RECOMMENDATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240303714 titled 'METHOD AND SYSTEM FOR GENERATING SUPPLY RECOMMENDATIONS
The method described in the abstract is about generating supply recommendations based on constraint configurations and part information.
- Identification of recommendation generation events associated with a part
- Obtaining part information and constraint configurations
- Generating recommendations based on the constraints and part information
- Performing supply actions based on the generated recommendations
Potential Applications: - Supply chain management - Inventory optimization - Manufacturing process improvement
Problems Solved: - Inefficient supply chain management - Lack of optimized inventory levels - Suboptimal manufacturing processes
Benefits: - Improved efficiency in supply chain operations - Cost savings through optimized inventory levels - Enhanced manufacturing productivity
Commercial Applications: Title: Supply Chain Optimization Technology This technology can be used in various industries such as retail, manufacturing, and logistics to streamline operations, reduce costs, and improve overall efficiency.
Questions about Supply Chain Optimization Technology: 1. How does this technology impact overall supply chain performance? This technology can significantly improve supply chain performance by providing optimized recommendations for inventory management and manufacturing processes.
2. What are the key features that set this technology apart from traditional supply chain management systems? This technology stands out due to its ability to generate recommendations based on constraint configurations, leading to more tailored and efficient supply chain operations.
Original Abstract Submitted
techniques described herein relate to a method for generating supply recommendations. the method includes identifying, by a supply recommendation engine, a recommendation generation event associated with a part; in response to identifying the recommendation generation event: obtaining part information associated with the recommendation generation event; obtaining a first constraint configuration; and generating a first recommendation based on the first constraint configuration and the part information; obtaining a second constraint configuration; in response to obtaining the second constraint configuration; generating a second recommendation based on the second constraint configuration and the part information; and performing supply actions based on the first optimization recommendations and the second optimization recommendations.
