US 12,282,874 B2
Scheduling project activities using twin computing simulation
Shailendra Moyal, Pune (IN); Nitika Sharma, Zirakpur (IN); Sarbajit K. Rakshit, Kolkata (IN); and Akash U. Dhoot, Pune (IN)
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed by INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed on Nov. 14, 2022, as Appl. No. 17/986,449.
Prior Publication US 2024/0161032 A1, May 16, 2024
Int. Cl. G06Q 10/0631 (2023.01); G06Q 10/0633 (2023.01); G06Q 10/067 (2023.01)
CPC G06Q 10/06312 (2013.01) [G06Q 10/063114 (2013.01); G06Q 10/0633 (2013.01); G06Q 10/067 (2013.01)] 15 Claims
OG exemplary drawing
 
1. A computer-implemented method for critical path based proactive optimization comprising:
receiving data, at a computer, on tasks of a contextual situation for performing a process;
training a twin computing simulation model using the collected data for each task in the process;
running a contextual situation simulation using the simulation models for each task in the process to determine a critical path that causes delay in the process;
determining an optimized task from the tasks of the contextual situation using machine learning employing the collected data, wherein the optimized task mitigates delay in the process from the critical path; and
actuating the optimized task, wherein the actuating the optimized task comprises at least one of actuating autonomous manufacturing machines, actuating autonomous assembly machines, actuating autonomous vehicles or a combination thereof.