An Analytical Approach to Inventory Management for Telecommunications Network Equipment

Verizon’s core network relies on routers that use expensive plug-in cards (PICs) to function. PIC failures can cause disruptions to FiOS or wireless service in the surrounding area. Maintaining an appropriate level of spare PICs is important to maintaining high service levels. Due to the high cost a...

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Bibliographic Details
Main Author: Cutlip, Margaret G.
Other Authors: Welsch, Roy
Format: Thesis
Published: Massachusetts Institute of Technology 2022
Online Access:https://hdl.handle.net/1721.1/139546
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author Cutlip, Margaret G.
author2 Welsch, Roy
author_facet Welsch, Roy
Cutlip, Margaret G.
author_sort Cutlip, Margaret G.
collection MIT
description Verizon’s core network relies on routers that use expensive plug-in cards (PICs) to function. PIC failures can cause disruptions to FiOS or wireless service in the surrounding area. Maintaining an appropriate level of spare PICs is important to maintaining high service levels. Due to the high cost and volume of PICs used in Verizon's networks, it becomes expensive to hold excessive inventory onsite, without exponentially increasing working capital. This project takes two approaches to aiding in inventory management: first, building predictive models for PICs failures in FiOS routers based on previously recorded failures; second, developing a holistic Central Office (CO, where telecommunications data is routed) prioritization system to determine where to place constrained inventory. While developing predictive models for PICs failures proved unsuccessful, the CO prioritization approach resulted in reductions in outage customer impact and traffic impact of more than 40% across all test cases.
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spelling mit-1721.1/1395462022-01-15T03:06:49Z An Analytical Approach to Inventory Management for Telecommunications Network Equipment Cutlip, Margaret G. Welsch, Roy Anthony, Brian W. Massachusetts Institute of Technology. Department of Mechanical Engineering Sloan School of Management Verizon’s core network relies on routers that use expensive plug-in cards (PICs) to function. PIC failures can cause disruptions to FiOS or wireless service in the surrounding area. Maintaining an appropriate level of spare PICs is important to maintaining high service levels. Due to the high cost and volume of PICs used in Verizon's networks, it becomes expensive to hold excessive inventory onsite, without exponentially increasing working capital. This project takes two approaches to aiding in inventory management: first, building predictive models for PICs failures in FiOS routers based on previously recorded failures; second, developing a holistic Central Office (CO, where telecommunications data is routed) prioritization system to determine where to place constrained inventory. While developing predictive models for PICs failures proved unsuccessful, the CO prioritization approach resulted in reductions in outage customer impact and traffic impact of more than 40% across all test cases. S.M. M.B.A. 2022-01-14T15:18:58Z 2022-01-14T15:18:58Z 2021-06 2021-06-10T19:13:02.390Z Thesis https://hdl.handle.net/1721.1/139546 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 Cutlip, Margaret G.
An Analytical Approach to Inventory Management for Telecommunications Network Equipment
title An Analytical Approach to Inventory Management for Telecommunications Network Equipment
title_full An Analytical Approach to Inventory Management for Telecommunications Network Equipment
title_fullStr An Analytical Approach to Inventory Management for Telecommunications Network Equipment
title_full_unstemmed An Analytical Approach to Inventory Management for Telecommunications Network Equipment
title_short An Analytical Approach to Inventory Management for Telecommunications Network Equipment
title_sort analytical approach to inventory management for telecommunications network equipment
url https://hdl.handle.net/1721.1/139546
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