Astrid Carolina Aguilar Fajardo
DMAIC, Data-Driven Quality Strategy Applied: Improvement of Mechanical-Labor Operations and Organizational KPIs.
Rel. Domenico Augusto Francesco Maisano. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management), 2023
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Abstract: |
This report presents the application of the DMAIC methodology in a company in the e-commerce industry where it intended to solve a problem present in a fulfillment center affecting the outbound processes (packing and shipping of orders). A supportive process performed by a special machine, referred to as Tote Distributor, received containers called totes with picked items from the inventory storage and distributed them into the different lines installed for packing and shipping. The Tote Distributor was having high levels of recirculation percentage, which indicated the number of defects in the process; a defect being the result of an attempt to distribute a tote but for one or a series of reasons, the machine was not able to perform the task. This elevated number of defects was causing several problems downstream, affecting the packing processes and reducing efficiency in the workflow and its management. It was necessary to first identify the root causes for the elevated recirculation percentage, since the causes were not clear. Then, assess the recirculation’s impact over the outbound processes, and based on data-driven analysis propose and make trials of solutions and improvements to the operational and mechanical processes, and implement the actions that improve the mechanical performance and the efficiency of the outbound processes. Moreover, due to the high level of digitalization, with automation and robotics present, the company can be qualified to have integrated Industry 4.0 in its logistics processes. Based on the interaction of these three factors: the objective to solve a complex problem, the setting in the e-commerce industry, and its advancements in Industry 4.0, Six Sigma’s DMAIC complemented with Lean Manufacturing tools for process optimization and enhanced with I4.0 analytics capabilities (like data-mining to generate information) was the quality strategy selected as fit for the action research project. The author intends to present how to apply these concepts and techniques in the setting of operational-mechanical processes in the e-commerce industry. |
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Relators: | Domenico Augusto Francesco Maisano |
Academic year: | 2022/23 |
Publication type: | Electronic |
Number of Pages: | 82 |
Subjects: | |
Corso di laurea: | Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management) |
Classe di laurea: | New organization > Master science > LM-31 - MANAGEMENT ENGINEERING |
Aziende collaboratrici: | AMAZON ITALIA LOGISTICA SRL |
URI: | http://webthesis.biblio.polito.it/id/eprint/26448 |
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