Integration of job shop scheduling with discreet event simulation for manufacturing facilities

• US 7,702,411 B2
• Filed: 05/31/2007
• Issued: 04/20/2010
• Est. Priority Date: 05/31/2007
• Status: Active Grant

• Current Assignee: Twitter Inc (X Holdings Corp.)
• Original Assignee: International Business Machines Corporation
• Inventors: Ghosh, Soumyadip, Bagchi, Sugato, Kalagnanam, Jayant R.
• Primary Examiner(s): DeCady; Albert
• Assistant Examiner(s): Gami; Tejal
• Application Number:
  US11/756,356
• Publication Number:
  US 20080300705A1
• Time in Patent Office: 1,055 Days
• Field of Search: 700/100, 700/99, 700/96, 705/8
• US Class Current: 700/100
• CPC Class Codes: G05B 19/41865 characterised by job scheduling, process planning, material flow
• CPC Class Codes: G05B 19/41885 characterised by modeling, simulation of the manufacturing system
• CPC Class Codes: G05B 2219/32252 Scheduling production, machining, job shop
• CPC Class Codes: G05B 2219/32301 Simulate production, process stages, determine optimum scheduling rules
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06312 Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling

Abstract

A method and system for integrating job shop scheduling with discrete event simulation for manufacturing facilities are provided. In one aspect a simulator simulates discrete events of a facility using a job schedule generated by a scheduler. The simulator simulates the facility based on one or more local rules, one or more resources, and one or more parameters associated with said locals rules and said resources. The simulator further models said one or more parameters as random variables and using said random variables in its simulation of the facility. The scheduler receives feedback based on output from the simulating step. The feedback includes at least an instruction to the scheduler to include at least one of said one or more resource and to change said one or more parameters based on said modeling of said one or more parameters as random variables. The scheduler uses the feedback for generating an updated schedule.

Claims

1. A method of integrating job shop scheduling with discrete event simulation for manufacturing facilities, comprising:

simulating by a simulator discrete events of a facility using job schedule generated by a scheduler, the simulator simulating the facility based on one or more local rules, one or more resources, and one or more parameters associated with said locals rules and said resources, the simulator further modeling said one or more parameters as random variables and using said random variables in its simulation of the facility; and

providing a feedback to said scheduler based on output from the simulating step, said feedback including at least an instruction to said scheduler to include at least one of said one or more resource and to change said one or more parameters based on said modeling of said one or more parameters as random variables, said feedback for said scheduler to use for updating a scheduling model associated with said scheduler and generating an updated schedule,

said providing a feedback step further including determining whether the simulator followed timing and sequence prescribed in the job schedule and in response to determining that the simulator failed to follow the timing and sequence prescribed in the job schedule, comparing one or more factors that the scheduler used differently than the simulator and identifying root variability that caused the simulator to fail to follow the timing and sequence prescribed in the job schedule and the simulator instructing the schedule to at least model previously unmodeled resources in generating the updated schedule.

2. The method of claim 1, further including:

rerunning said scheduler with said feedback; and

generating a new job schedule.

3. The method of claim 2, further including:

repeating said steps of simulating, providing, rerunning and generating until said output from the simulating step indicates said new job schedule can be followed viably.

4. The method of claim 1, wherein said scheduler does not consider all of said one or more resources when initially generating said job schedule.

5. The method of claim 1, wherein said scheduler uses deterministic values for said one or more parameters.

6. A system for integrating job shop scheduling with discrete event simulation for manufacturing facilities, comprising:

a scheduler module provides a job schedule for a facility;

a simulator module simulates discrete events of a facility using the job schedule generated by the scheduler, the simulator simulating the facility based on one or more local rules, one or more resources, and one or more parameters associated with said locals rules and said resources, the simulator further modeling said one or more parameters as random variables and using said random variables in its simulation of the facility, an analysis module provides a feedback to said scheduler based on output from the simulator, said feedback including at least an instruction to the scheduler to include at least one of said one or more resource and to change said one or more parameters based on said modeling of said one or more parameters as random variables, said feedback for the scheduler to use for updating a scheduling model associated with said scheduler and generating an updated schedule, said analysis module provides a feedback further determining whether the simulator followed timing and sequence prescribed in the job schedule and in response to determining that the simulator failed to follow the timing and sequence prescribed in the job schedule, comparing one or more factors that the scheduler used differently than the simulator and identifying root variability that caused the simulator to fail to follow the timing and sequence prescribed in the job schedule, and the simulator instructing the schedule to at least model previously unmodeled one or more resources in generating the updated schedule.