Waste Reduction in Amazon Robotics Sortable High Velocity Fulfilment Using Six-Sigma and Product Design Methods
Amazon Robotics Sortable High Velocity Fulfilment or ARS-HVF is a program designed to mitigate waste generation associated with high velocity (high rate of sales over time) items’ fulfillment. Large variability in items’ velocities in the ARS network causes the existing process to generate waste whe...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2023
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| Online Access: | https://hdl.handle.net/1721.1/150721 |
| _version_ | 1826201319150452736 |
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| author | Peleg, Tamir |
| author2 | Yang, Maria |
| author_facet | Yang, Maria Peleg, Tamir |
| author_sort | Peleg, Tamir |
| collection | MIT |
| description | Amazon Robotics Sortable High Velocity Fulfilment or ARS-HVF is a program designed to mitigate waste generation associated with high velocity (high rate of sales over time) items’ fulfillment. Large variability in items’ velocities in the ARS network causes the existing process to generate waste when dealing with High-Velocity items. Three forms of this waste are packaging material waste, delivery expenses, and non-value-adding labor. Looking at the four leading Amazon Devices in 2020, the generated waste associated with these products amounts to over 100k [m^3] of packaging, comparable to 40 Olympic swimming pools, millions of dollars in excess delivery expenses as well as carbon emissions from unnecessary van rides due to volume added by over-boxing, and over 100k hours of non-value-adding labor. Together, these waste forms pose a potential savings amount of $20M, for the year 2022 over these four products alone. Six-Sigma and product design and development methods were used in this work to methodically evaluate and solve the problem of waste generation in the current Amazon FC process. Internal Subject Matter Experts (SMEs) and external vendors were utilized to inform the design process, provide feedback on designs, manufacture samples, and provide industrial grade solutions. Waste generation reduction is an opportunity to design a new fulfillment path. The designed path is built from three components: package, process, and machine. These are tailored together to remove the use of over-box, eliminate excess delivery expenses, and reduce non-value-adding labor by more than 95%. The new e-commerce primary package design is compatible with physical stores presence, fully recyclable, and can be shipped as is, eliminating the need for over-box, and downsizing shipped packages' volume to the actual size of the item’s unit. It also serves as an enabler for the new process that bypasses the current ARS Fulfilment center (FC) process's three waste generating stations, Stow, Pick and Pack. The process design includes a new multi unit package, known as a master-shipper, which together with the newly designed fulfilment dispenser machine, realizes cycle-time reduction by pooling multiple units into one task instead of performing multiple tasks processing one unit. The three components together result in an average cost per unit reduction of $0.8-1.5. With potential expansion to additional high velocity items, the estimated savings potential amounts to $75-110M for 2022, with expected growth of 30% YoY. These results illustrate that sustainability efforts can highly benefit all involved stakeholders, including the company, its customers and the communities which they both live in. |
| first_indexed | 2024-09-23T11:50:03Z |
| format | Thesis |
| id | mit-1721.1/150721 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T11:50:03Z |
| publishDate | 2023 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1507212023-05-16T03:32:02Z Waste Reduction in Amazon Robotics Sortable High Velocity Fulfilment Using Six-Sigma and Product Design Methods Peleg, Tamir Yang, Maria Spear, Steven J. Massachusetts Institute of Technology. Department of Mechanical Engineering Sloan School of Management Amazon Robotics Sortable High Velocity Fulfilment or ARS-HVF is a program designed to mitigate waste generation associated with high velocity (high rate of sales over time) items’ fulfillment. Large variability in items’ velocities in the ARS network causes the existing process to generate waste when dealing with High-Velocity items. Three forms of this waste are packaging material waste, delivery expenses, and non-value-adding labor. Looking at the four leading Amazon Devices in 2020, the generated waste associated with these products amounts to over 100k [m^3] of packaging, comparable to 40 Olympic swimming pools, millions of dollars in excess delivery expenses as well as carbon emissions from unnecessary van rides due to volume added by over-boxing, and over 100k hours of non-value-adding labor. Together, these waste forms pose a potential savings amount of $20M, for the year 2022 over these four products alone. Six-Sigma and product design and development methods were used in this work to methodically evaluate and solve the problem of waste generation in the current Amazon FC process. Internal Subject Matter Experts (SMEs) and external vendors were utilized to inform the design process, provide feedback on designs, manufacture samples, and provide industrial grade solutions. Waste generation reduction is an opportunity to design a new fulfillment path. The designed path is built from three components: package, process, and machine. These are tailored together to remove the use of over-box, eliminate excess delivery expenses, and reduce non-value-adding labor by more than 95%. The new e-commerce primary package design is compatible with physical stores presence, fully recyclable, and can be shipped as is, eliminating the need for over-box, and downsizing shipped packages' volume to the actual size of the item’s unit. It also serves as an enabler for the new process that bypasses the current ARS Fulfilment center (FC) process's three waste generating stations, Stow, Pick and Pack. The process design includes a new multi unit package, known as a master-shipper, which together with the newly designed fulfilment dispenser machine, realizes cycle-time reduction by pooling multiple units into one task instead of performing multiple tasks processing one unit. The three components together result in an average cost per unit reduction of $0.8-1.5. With potential expansion to additional high velocity items, the estimated savings potential amounts to $75-110M for 2022, with expected growth of 30% YoY. These results illustrate that sustainability efforts can highly benefit all involved stakeholders, including the company, its customers and the communities which they both live in. S.M. M.B.A. 2023-05-15T19:34:59Z 2023-05-15T19:34:59Z 2022-05 2023-05-10T20:35:33.398Z Thesis https://hdl.handle.net/1721.1/150721 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Peleg, Tamir Waste Reduction in Amazon Robotics Sortable High Velocity Fulfilment Using Six-Sigma and Product Design Methods |
| title | Waste Reduction in Amazon Robotics Sortable High Velocity Fulfilment Using Six-Sigma and Product Design Methods |
| title_full | Waste Reduction in Amazon Robotics Sortable High Velocity Fulfilment Using Six-Sigma and Product Design Methods |
| title_fullStr | Waste Reduction in Amazon Robotics Sortable High Velocity Fulfilment Using Six-Sigma and Product Design Methods |
| title_full_unstemmed | Waste Reduction in Amazon Robotics Sortable High Velocity Fulfilment Using Six-Sigma and Product Design Methods |
| title_short | Waste Reduction in Amazon Robotics Sortable High Velocity Fulfilment Using Six-Sigma and Product Design Methods |
| title_sort | waste reduction in amazon robotics sortable high velocity fulfilment using six sigma and product design methods |
| url | https://hdl.handle.net/1721.1/150721 |
| work_keys_str_mv | AT pelegtamir wastereductioninamazonroboticssortablehighvelocityfulfilmentusingsixsigmaandproductdesignmethods |