{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/59174"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/59174","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Crisplant defects quantification and reduction at an amazon.com distribution center","abstract":"Crisplant is a tilt-tray sortation system used in Reno (RNO 1) fulfillment center (FC) to group items by customer orders. On average., crisplant processes about 80% of the total outbound volume through its multipart operation flow. Because of high volume and complex process flow, the majority of defects, in RNO 1 FC. are seen in crisplant costing distribution center (RNO 1) significantly in labor hours. This research paper identifies and quantifies the major defects in crisplant, and outlines the solutions to reduce the cost of handling these defects in RNO 1. The project work thoroughly assesses the entire RNO 1 crisplant operations (induct, sort, pack, SLAM, and problem solve) through four-phase approach: Understand the crisplant Process Flow, Develop a Data Collection Framework, Collect and Analyze Data, and Identify/Implement Data Driven Solutions. Lean principles and methodologies were used throughout the project work especially when identifying solutions. For example, opportunities that improved the packing process were identified based on a deep-dive analysis as a part of the Kaizen study. The project results demonstrated 50% reduction in cost of handling crisplant defects in RNO l. Furthermore, it highlighted opportunities for additional savings by identifying solutions that can also be implemented in other FCs (i.e. SDF 1, TUL 1) with similar operation as RNO 1.","abstract_html":"Crisplant is a tilt-tray sortation system used in Reno (RNO 1) fulfillment center (FC) to group items by customer orders. On average., crisplant processes about 80% of the total outbound volume through its multipart operation flow. Because of high volume and complex process flow, the majority of defects, in RNO 1 FC. are seen in crisplant costing distribution center (RNO 1) significantly in labor hours. This research paper identifies and quantifies the major defects in crisplant, and outlines the solutions to reduce the cost of handling these defects in RNO 1. The project work thoroughly assesses the entire RNO 1 crisplant operations (induct, sort, pack, SLAM, and problem solve) through four-phase approach: Understand the crisplant Process Flow, Develop a Data Collection Framework, Collect and Analyze Data, and Identify/Implement Data Driven Solutions. Lean principles and methodologies were used throughout the project work especially when identifying solutions. For example, opportunities that improved the packing process were identified based on a deep-dive analysis as a part of the Kaizen study. The project results demonstrated 50% reduction in cost of handling crisplant defects in RNO l. Furthermore, it highlighted opportunities for additional savings by identifying solutions that can also be implemented in other FCs (i.e. SDF 1, TUL 1) with similar operation as RNO 1.","abstract_has_math":false,"creators":["Patel, Kashyap (Kashyap C.)"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Leaders for Global Operations Program at MIT","school":null,"contributors":[],"advisors":["Roy Welsch and Stanley Gershwin."],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010","date_published":"2010","updated_at":"2026-07-22T22:22:14Z","subjects":["Sloan School of Management.","Mechanical Engineering.","Leaders for Global Operations Program."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/59174","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Roy Welsch and Stanley Gershwin."]},{"key":"dc:contributor.department","label":"Department","values":["Leaders for Global Operations Program at MIT","Massachusetts Institute of Technology. Department of Mechanical Engineering","Sloan School of Management"]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Leaders for Global Operations Program."]},{"key":"dc:creator","label":"Author","values":["Patel, Kashyap (Kashyap C.)"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2010-10-12T18:01:09Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2010-10-12T18:01:09Z"]},{"key":"dc:date.issued","label":"Date","values":["2010"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Sloan School of Management.","Mechanical Engineering.","Leaders for Global Operations Program."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/59174"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2010.","Cataloged from PDF version of thesis.","Includes bibliographical references (p. 59-60)."]},{"key":"dc:description.abstract","label":"Abstract","values":["Crisplant is a tilt-tray sortation system used in Reno (RNO 1) fulfillment center (FC) to group items by customer orders. On average., crisplant processes about 80% of the total outbound volume through its multipart operation flow. Because of high volume and complex process flow, the majority of defects, in RNO 1 FC. are seen in crisplant costing distribution center (RNO 1) significantly in labor hours. This research paper identifies and quantifies the major defects in crisplant, and outlines the solutions to reduce the cost of handling these defects in RNO 1. The project work thoroughly assesses the entire RNO 1 crisplant operations (induct, sort, pack, SLAM, and problem solve) through four-phase approach: Understand the crisplant Process Flow, Develop a Data Collection Framework, Collect and Analyze Data, and Identify/Implement Data Driven Solutions. Lean principles and methodologies were used throughout the project work especially when identifying solutions. For example, opportunities that improved the packing process were identified based on a deep-dive analysis as a part of the Kaizen study. The project results demonstrated 50% reduction in cost of handling crisplant defects in RNO l. Furthermore, it highlighted opportunities for additional savings by identifying solutions that can also be implemented in other FCs (i.e. SDF 1, TUL 1) with similar operation as RNO 1."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M.","M.B.A."]},{"key":"dc:title","label":"Title","values":["Crisplant defects quantification and reduction at an amazon.com distribution center"]}]}],"canonical_facts":{"dc:contributor.advisor":["Roy Welsch and Stanley Gershwin."],"dc:contributor.department":["Leaders for Global Operations Program at MIT","Massachusetts Institute of Technology. Department of Mechanical Engineering","Sloan School of Management"],"dc:contributor.other":["Leaders for Global Operations Program."],"dc:creator":["Patel, Kashyap (Kashyap C.)"],"dc:date.accessioned":["2010-10-12T18:01:09Z"],"dc:date.available":["2010-10-12T18:01:09Z"],"dc:date.issued":["2010"],"dc:description":["Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2010.","Cataloged from PDF version of thesis.","Includes bibliographical references (p. 59-60)."],"dc:description.abstract":["Crisplant is a tilt-tray sortation system used in Reno (RNO 1) fulfillment center (FC) to group items by customer orders. On average., crisplant processes about 80% of the total outbound volume through its multipart operation flow. Because of high volume and complex process flow, the majority of defects, in RNO 1 FC. are seen in crisplant costing distribution center (RNO 1) significantly in labor hours. This research paper identifies and quantifies the major defects in crisplant, and outlines the solutions to reduce the cost of handling these defects in RNO 1. The project work thoroughly assesses the entire RNO 1 crisplant operations (induct, sort, pack, SLAM, and problem solve) through four-phase approach: Understand the crisplant Process Flow, Develop a Data Collection Framework, Collect and Analyze Data, and Identify/Implement Data Driven Solutions. Lean principles and methodologies were used throughout the project work especially when identifying solutions. For example, opportunities that improved the packing process were identified based on a deep-dive analysis as a part of the Kaizen study. The project results demonstrated 50% reduction in cost of handling crisplant defects in RNO l. Furthermore, it highlighted opportunities for additional savings by identifying solutions that can also be implemented in other FCs (i.e. SDF 1, TUL 1) with similar operation as RNO 1."],"dc:description.degree":["S.M.","M.B.A."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/59174"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Sloan School of Management.","Mechanical Engineering.","Leaders for Global Operations Program."],"dc:title":["Crisplant defects quantification and reduction at an amazon.com distribution center"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:22:14Z"}