18178465. SYSTEMS AND METHODS FOR TASK PREDICTION AND CONSTRAINT MODELING simplified abstract (Honeywell International Inc.)
Contents
- 1 SYSTEMS AND METHODS FOR TASK PREDICTION AND CONSTRAINT MODELING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SYSTEMS AND METHODS FOR TASK PREDICTION AND CONSTRAINT MODELING - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
SYSTEMS AND METHODS FOR TASK PREDICTION AND CONSTRAINT MODELING
Organization Name
Inventor(s)
Kalimulla Khan of Morris Plains NJ (US)
Srihari Jayathirtha of Bangalore (IN)
Wade Lindsey of Canton GA (US)
Venkata Pradeep Kolla of Cumming GA (US)
SYSTEMS AND METHODS FOR TASK PREDICTION AND CONSTRAINT MODELING - A simplified explanation of the abstract
This abstract first appeared for US patent application 18178465 titled 'SYSTEMS AND METHODS FOR TASK PREDICTION AND CONSTRAINT MODELING
Simplified Explanation
The patent application describes a method and system for optimizing operations data for a facility by generating an optimization model based on the data, calculating solution values, and transmitting them to a scheduling device for task scheduling.
- Obtaining a set of operations data for a facility, including tasks and operational constraints.
- Generating an optimization model with variables corresponding to facility operations and constraints.
- Calculating solution values using the optimization model.
- Transmitting the solution values to a scheduling device for task scheduling.
- Altering operational constraints changes the optimization model and recalculates solution values.
Potential Applications
This technology can be applied in various industries such as manufacturing, logistics, healthcare, and transportation to optimize operations and improve efficiency.
Problems Solved
This technology helps in optimizing task schedules, improving resource allocation, and enhancing overall operational efficiency of a facility.
Benefits
The benefits of this technology include increased productivity, reduced costs, improved resource utilization, and better decision-making based on optimized data.
Potential Commercial Applications
Potential commercial applications of this technology include software solutions for operations management, consulting services for process optimization, and integrated systems for facility management.
Possible Prior Art
One possible prior art for this technology could be existing optimization algorithms used in operations research and supply chain management to improve efficiency and decision-making processes.
Unanswered Questions
How does this technology handle real-time changes in operational constraints during task scheduling?
The patent application does not specify how the system adapts to real-time changes in operational constraints and recalculates solution values accordingly.
What types of facilities or industries can benefit the most from this optimization technology?
The patent application does not provide specific examples of facilities or industries that can benefit the most from this optimization technology.
Original Abstract Submitted
A method is disclosed, and a system for performing the method, the method comprising: obtaining a set of operations data for a facility, the set of operations data including a plurality of tasks scheduled to be completed, and a plurality of operational constraints; generating an optimization model based on the set of operations data, wherein the optimization model defines a plurality of variables corresponding to operations of the facility and the plurality of operational constraints; calculating, using the optimization model, a set of solution values, wherein each of the set of solution values corresponds to one or more of the plurality of variables; and transmitting the set of solution values to a scheduling device configured to generate a task schedule for the facility, wherein altering the value of one of the operational constraints alters the optimization model and an altered set of solution values is calculated.
