Analytical model for production decisions in a high-end server manufacturing environment

Chanchal Saha, Warren Boldrin, Faisal Aqlan, Sreekanth Ramakrishnan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Today's market dynamics and increased customer expectations have made manufacturing environments extremely complex. Advanced production planning and scheduling decisions are made based on analytical models and extensive information processing. In this research, an analytical model is developed to improve production decisions in a high-end server manufacturing environment. The production decisions include assembly and disposition decisions of customer orders for a pro-active order fulfillment scenario to assist assembly line operators. The objective is to minimize the teardown volumes of assembled orders and eliminate the Work-in-process (WIP) accumulation. The proposed framework was implemented in a clear-to-build type high-end server manufacturing environment. In addition to minimizing the teardown volumes and WIP, the proposed framework reduces workload of manual processes by reducing cycle time of rework. It also enables real-time reapplication decisions for assembled but cancelled customer orders.

Original languageEnglish (US)
Title of host publication67th Annual Conference and Expo of the Institute of Industrial Engineers 2017
EditorsHarriet B. Nembhard, Katie Coperich, Elizabeth Cudney
PublisherInstitute of Industrial Engineers
Pages704-709
Number of pages6
ISBN (Electronic)9780983762461
StatePublished - Jan 1 2017
Event67th Annual Conference and Expo of the Institute of Industrial Engineers 2017 - Pittsburgh, United States
Duration: May 20 2017May 23 2017

Publication series

Name67th Annual Conference and Expo of the Institute of Industrial Engineers 2017

Other

Other67th Annual Conference and Expo of the Institute of Industrial Engineers 2017
Country/TerritoryUnited States
CityPittsburgh
Period5/20/175/23/17

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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