System and methods for excess capacity in dynamic production systems
View Patent ↗The present application presents a new and improved system and method of enhanced Lean Document Production (LDP), which employs cellular manufacturing concepts. The LDP process utilizes a processor to compute a dynamic production algorithm to generate an indication of a manufacturing or print shop excess capacity level.
1. A method for determining the excess capacity of a cellular manufacturing environment, the method comprising:
providing an overall job mix including at least existing jobs to be processed;
determining feasibility, at a fixed time interval, of adding at least one excess job to the overall job mix; and
adding the at least one excess job to an excess-capacity jobs list, if and only if the at least one excess job is determined feasible, wherein feasibility is based on determining if adding the at least one excess job instance delays at least one job in the overall job mix, and the method is performed by at least one processing device.
2. A method for determining the excess capacity of a cellular manufacturing environment, the method comprising:
clearing an excess capacity list;
specifying a time interval minimum and maximum for how often to test feasibility of adding at least one excess job to an overall job mix;
compiling a list of at least one excess job mix instance;
determining the feasibility of adding the at least one excess job mix instance to an overall job mix list;
adding the at least one excess job instance to an excess-capacity jobs list, if the at least one excess job instance is determined feasible;
wherein the feasibility is determined at fixed time intervals within the time interval minimum and maximum,
and wherein the method is performed by at least one electronic processing device.
3. The method according to claim 2 , further comprising increasing the fixed time interval when it is determined not feasible to add at least one excess job instance to an excess-capacity jobs list.
4. The method according to claim 3 , further comprising increasing the fixed time interval using a step function.
5. The method according to claim 2 , further comprising decreasing the fixed time interval when it is determined feasible to add at least one excess job instance to an excess-capacity jobs list.
6. The method according to claim 5 , further comprising decreasing the fixed time interval using a step function.
7. The method according to claim 2 , further comprising allocating resources for the at least one excess job when the at least one excess job instance is determined feasible.
8. The method according to claim 2 , further comprising determining when the at least one excess job instance in the excess-capacity jobs list is feasible to implement.
9. The method according to claim 8 , further comprising presenting the number of excess job instances in the excess-capacity jobs list and when it is feasible to implement the at least one excess job instance.
10. The method according to claim 2 , further comprising determining the feasibility based on at least one of the average turnaround time, maximum lateness, and average lateness.
11. The method according to claim 2 , further comprising determining on a first processor the feasibility of adding the at least one excess job mix instance to an overall job mix list and determining on a second processor the feasibility of adding the at least one excess job mix instance to an overall job mix list.
12. The method according to claim 11 , wherein the first processor and second processor determines the feasibility in parallel.
13. The method according to claim 2 , further comprising:
a job mix instance slack time;
wherein the slack time comprises a fixed time interval between when a job mix instance arrives and the job mix instance is due for completion; and
wherein the determining assumes each of the at least one excess job instance has a slack time.
14. The method according to claim 2 , further comprising adding the at least one excess job instance an excess-capacity jobs list, if the at least one excess job instance is infeasible.
15. The method according to claim 2 , wherein determining feasibility is based on determining if adding the at least one excess job instance delays at least one job in the overall job mix.
16. The method according to claim 2 , wherein the time interval minimum and maximum is a percentage of an average throughput of jobs in the overall job mix.
17. A system for determining excess capacity of a cellular manufacturing environment, the system comprising:
an excess job mix compiler for compiling a list of at least one excess job mix instance;
a feasibility testing module for determining the feasibility at fixed time intervals of adding the at least one excess job to an overall job mix using a computer operable processor;
a dynamic time step value;
an excess job list updater for adding the at least one excess job instance to an excess-capacity jobs list, if the at least one excess job instance is determined feasible;
wherein the feasibility testing module determines the feasibility at a fixed time interval; and
wherein the fixed time interval is adjusted based on the dynamic time step value; and
wherein feasibility is based on determining if adding the at least one excess job instance delays at least one job in the overall job mix.
18. The system according to claim 17 , further comprising a translating module for translating the feasibility of adding at least one excess job to an overall job mix into at least one of revenue or profit loss terms.
19. The system according to claim 17 , wherein the dynamic step value is halved if the feasibility testing module determines it is feasible to add the at least one excess job to the overall job mix.
20. The system according to claim 17 , wherein the dynamic step value is doubled if the feasibility testing module determines it is not feasible to add the at least one excess job to the overall job mix.