Determining capacities of work buffers

• US 9,342,063 B1
• Filed: 09/19/2013
• Issued: 05/17/2016
• Est. Priority Date: 09/19/2013
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Iakhnine, Serguei, McTavish, James, Volgin, Kirill, Bachmutsky, Vadim, Fedorenko, Vitalii, Thinakaran, Kreethigha
• Primary Examiner(s): Masinick, Michael D
• Application Number:
  US14/031,890
• Time in Patent Office: 971 Days
• Field of Search: 700/97, 700/99
• US Class Current: 1/1
• CPC Class Codes: G05B 19/41865 characterised by job scheduling, process planning, material flow
• CPC Class Codes: G05B 2219/31376 MFL material flow
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

Disclosed are various embodiments for determining capacities for work buffers. Data is received that indicates past work cycles for a first stage and a second stage of a pipelined process. The pipelined process includes a work buffer between the first stage and the second stage. Staffing levels for the first stage and the second stage are received. An optimal buffer capacity for the work buffer is generated based at least in part on a predicted workflow variance for the pipelined process, the staffing levels, and the past work cycles.

Claims

1. A non-transitory computer-readable medium embodying a program executable in at least one computing device, comprising:

code that determines respective past work cycles for individual ones of a plurality of stages in a pipelined materials handling process in a fulfillment center, the pipelined materials handling process including respective work buffers between successive ones of the plurality of stages;

code that determines respective staffing levels for the individual ones of the plurality of stages;

code that predicts a workflow variance for the pipelined materials handling process;

code that generates respective optimal buffer capacities for individual ones of the respective work buffers based at least in part on a target buffer capacity confidence, the predicted workflow variance, the respective staffing levels, and the respective past work cycles; and

code that generates a report indicating the respective optimal buffer capacities.

2. The non-transitory computer-readable medium of claim 1, wherein at least one of the respective optimal buffer capacities comprises a size of an area within the fulfillment center in which at least a portion of the pipelined materials handling process is performed.

3. The non-transitory computer-readable medium of claim 1, wherein at least one of the respective optimal buffer capacities comprises a container specification for transferring materials between a first one of the plurality of stages and a second one of the plurality of stages.

4. The non-transitory computer-readable medium of claim 1, further comprising code that generates a directive to modify a respective current output of at least one of the plurality of stages responsive to implementing at least one of the respective optimal buffer capacities.

5. The non-transitory computer-readable medium of claim 1, further comprising code that generates a directive to modify a respective current capacity of at least one of the respective work buffers to implement at least one of the respective optimal buffer capacities.

6. A system, comprising:

at least one computing device; and

a buffer optimization application executed in the at least one computing device, the buffer optimization application comprising;

logic that receives data indicating respective past work cycles for individual ones of a plurality of stages in a pipelined process, the pipelined process including respective work buffers between successive ones of the plurality of stages;

logic that receives respective staffing levels for individual ones of the plurality of stages and a predicted workflow variance; and

logic that generates respective optimal buffer capacities for individual ones of the respective work buffers based at least in part on the predicted workflow variance, the respective staffing levels, and the respective past work cycles.

7. The system of claim 6, wherein the buffer optimization application further comprises:

logic that receives a target buffer capacity confidence; and

wherein the respective optimal buffer capacities are generated further based at least in part on the target buffer capacity confidence.

8. The system of claim 6, wherein the buffer optimization application further comprises logic that generates a report indicating the respective optimal buffer capacities.

9. The system of claim 6, wherein the buffer optimization application further comprises:

logic that determines whether a particular optimal buffer capacity for a particular work buffer is below a current buffer capacity of the particular work buffer; and

logic that generates a directive to reduce the current buffer capacity of the particular work buffer when the particular optimal buffer capacity is below the current buffer capacity.

10. The system of claim 6, wherein the buffer optimization application further comprises:

logic that determines whether a particular optimal buffer capacity for a particular work buffer is above a current buffer capacity of the particular work buffer; and

logic that generates a directive to enlarge the current buffer capacity of the particular work buffer when the particular optimal buffer capacity is above the current buffer capacity.

11. The system of claim 6, wherein at least one of the respective optimal buffer capacities comprises a size of an area within a building in which at least a portion of the pipelined process is performed.

12. The system of claim 6, wherein the predicted workflow variance is received from a user.

13. The system of claim 6, wherein the buffer optimization application further comprises logic that determines the predicted workflow variance based at least in part on data indicating a plurality of past workflows for the pipelined process.

14. The system of claim 13, wherein the predicted workflow variance is determined further based at least in part on a time period of validity for the respective optimal buffer capacities.

15. A method, comprising:

receiving, by at least one computing device, data indicating respective past work cycles for a first stage and a second stage of a pipelined process, the pipelined process including a work buffer between the first stage and the second stage;

receiving, by the at least one computing device, respective staffing levels for the first stage and the second stage; and

generating, by the at least one computing device, an optimal buffer capacity for the work buffer based at least in part on a predicted workflow variance for the pipelined process, the respective staffing levels, and the respective past work cycles.

16. The method of claim 15, further comprising generating, by the at least one computing device, the predicted workflow variance based at least in part on past workflow volume data for the pipelined process.

17. The method of claim 15, wherein the pipelined process comprises a processing workflow of a fulfillment center.

18. The method of claim 17, wherein the processing workflow comprises an inbound processing workflow or an outbound processing workflow.

19. The method of claim 15, wherein the work buffer is configured to receive an output of the first stage and provide an input to the second stage.

20. The method of claim 15, further comprising generating, by the at least one computing device, an updated optimal buffer capacity for the work buffer based at least in part on updated respective staffing levels for the first stage and the second stage.