The Complexity of Data-Driven in Engineer-To-Order Enterprise Supply-Chains
Addo-Tenkorang, Richard; Helo, Petri; Sivula, Ari; Gwangwava, Norman (2022-04-20)
Addo-Tenkorang, Richard
Helo, Petri
Sivula, Ari
Gwangwava, Norman
Editori(t)
Batako, Andre
Burduk, Anna
Karyono, Kanisius
Chen, Xun
Wyczółkowski, Ryszard
Springer
20.04.2022
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2022042831062
https://urn.fi/URN:NBN:fi-fe2022042831062
Kuvaus
vertaisarvioitu
©2022 Springer. This is a post-peer-review, pre-copyedit version of an article published in Advances in Manufacturing Processes, Intelligent Methods and Systems in Production Engineering: Progress in Application of Intelligent Methods and Systems in Production Engineering. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-90532-3_39
©2022 Springer. This is a post-peer-review, pre-copyedit version of an article published in Advances in Manufacturing Processes, Intelligent Methods and Systems in Production Engineering: Progress in Application of Intelligent Methods and Systems in Production Engineering. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-90532-3_39
Tiivistelmä
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.
Kokoelmat
- Artikkelit [3030]