The Complexity of Data-Driven in Engineer-To-Order Enterprise Supply-Chains

Richard Addo-Tenkorang, Petri Helo, Ari Sivula, Norman Gwangwava

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

Abstract

The complexity of data-driven engineer-to-order manufacturing enterprise supply-chains for effective and efficient decision making has received a lot of attention both within the original equipment manufacturing industrial research and development circle and supply-chains operations research and management circles. However, despite these complexities, most of the published supply-chains research in operations research and management have neglected the ‘engineer-to-order perspective within the original equipment manufacturing supply-chains sector. This research employs a comprehensive study of complex supply-chains management activities to attempt to propose feasible and measurable essential propositions and/or framework for “best practices” in data-driven engineer-to-order supply-chains. There seems to be no specific comprehensive study on the complexity of data-driven engineer-to-order supply-chains within the original equipment manufacturing sectors for complex products such as the aerospace, marine, and/or power plant industries, etc. However, because this area of complexity of data-driven engineer-to-order within enterprise supply-chains have not been much researched or explored; there is an expected challenge of finding enough available literature to draw-on or makes an inference to. Hence, this study will take solace from mostly real-life industrial case(s) and/or activities, etc. Therefore, this paper presents a comprehensive study of the complexity of data-driven engineer-to-order enterprise supply-chains as well as outlining essential propositions and/or framework to enhance effective and efficient resilient complex engineer-to-order supply-chains. This paper will thus, contribute to the development of a more robust and resilient framework when dealing with the complexity of data-driven engineer-to-order enterprise supply-chains.

Original languageEnglish
Title of host publicationAdvances in Manufacturing Processes, Intelligent Methods and Systems in Production Engineering - Progress in Application of Intelligent Methods and Systems in Production Engineering
EditorsAndre Batako, Anna Burduk, Kanisius Karyono, Xun Chen, Ryszard Wyczólkowski
PublisherSpringer Science and Business Media Deutschland GmbH
Pages517-532
Number of pages16
ISBN (Print)9783030905316
DOIs
Publication statusPublished - 2022
Externally publishedYes
EventGlobal Congress on Manufacturing and Management, GCMM 2021 - Virtual, Online
Duration: 7 Jun 20219 Jun 2021

Publication series

NameLecture Notes in Networks and Systems
Volume335 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

ConferenceGlobal Congress on Manufacturing and Management, GCMM 2021
CityVirtual, Online
Period7/06/219/06/21

Keywords

  • Bigdata
  • Complexity
  • Engineer-to-Order
  • Original-equipment-manufacturer
  • Supply-chains

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