Dynamic Resource Allocation Engine for System Efficiency
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Solution Overview
Problem
Existing resource allocation methods fail to effectively evaluate the impact of new devices, processes, and personnel on overall system efficiency, often leading to unintended inefficiencies and suboptimal improvements.
Innovation Solution
A dynamic resource allocation engine that combines device and personnel data into a normalized format to identify commonalities and evaluate the efficiency of new resources, allowing for automated simulation and self-modification based on performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If new devices, processes, and personnel are introduced into a system, then the benefits of those new business solutions are touted as being highly superior, but the overall system efficiency fails to improve due to unplanned inefficiencies introduced by the new solution
Solution Approach 1:
The system performs preliminary simulation and analysis before implementing new resources. The resource allocation engine creates virtual models of proposed devices, processes, or personnel and simulates their impact on the entire system beforehand, allowing planners to identify potential inefficiencies before they are introduced into the actual system.
Solution Approach 2:
The system implements continuous feedback loops where the resource allocation engine monitors actual system performance after introducing new resources, compares it against simulated predictions, and uses this feedback to refine future simulations and allocations. This closed-loop approach prevents unplanned inefficiencies from persisting in the system.
2Productivity
If multiple changes are being made to resources, then each change might affect the other changes, but it is difficult to identify and select the most efficient set of changes
Solution Approach 1:
The resource allocation engine merges multiple individual resource allocation decisions into a single integrated optimization problem. Instead of evaluating changes separately, the system combines device allocations, process modifications, and personnel assignments into a unified simulation model that evaluates their combined impact and identifies the most efficient set of changes collectively.
Solution Approach 2:
The system employs dynamic simulation that can evaluate multiple scenarios and adjust allocations in real-time based on interdependencies. The engine dynamically modifies resource assignments across different categories (devices, processes, personnel) simultaneously, allowing it to capture the interactive effects of multiple changes and identify optimal combinations that static analysis would miss.
3Measurement precision
If traditional resource allocation methods are used, then implementation is simple, but the ability to evaluate the impact of new resources on overall system efficiency is insufficient
Solution Approach 1:
The system creates virtual copies or digital twins of the physical distribution system, including devices, processes, and personnel. These simulated models replicate system behavior and can be manipulated without affecting actual operations, allowing for precise evaluation of new resource impacts through simulation before real-world implementation.
Solution Approach 2:
The resource allocation engine systematically varies key parameters such as resource quantities, allocation patterns, and operational constraints in the simulation to measure their impact on system efficiency. By changing parameters in controlled ways within the virtual model, the system can precisely quantify the effects of introducing new resources or modifying existing ones.
Data Source
AI summary
A dynamic resource allocation engine which can assist in automating activities and processes within an organization. More specifically, the concepts disclosed herein can reduce operational costs by eliminating unnecessary devices, processes, and/or personnel, while also providing an efficient mechanism for testing the effects of new resources on the entire system. This is done by first combining data associated with devices, processes, and personnel, in a common (normalized) data format. This combination represents a simulation of the business or enterprise associated with the data, and can be referred to as a “resource allocation engine.” The resource allocation engine provides information about how resources are being used within the organization.