Publisher URL: | https://www.epubli.de/shop/buch/Artificial-Intelligence-and-Digital-Transformation-in-Supply-Chain-Management-Christian-M-Ringle-Thorsten-Blecker-Wolfgang-Kersten-9783750249479/92095 http://hdl.handle.net/11420/3718 |
Publisher DOI: | 10.15480/882.2463 | Title: | Breaking through the bottlenecks using artificial intelligence | Language: | English | Authors: | Feldt, Julia Kontny, Henning Wagenitz, Axel |
Editor: | Kersten, Wolfgang Blecker, Thorsten Ringle, Christian M. |
Keywords: | Artificial intelligence; Assembly-to-order; Bottlenecks; Supply chain | Issue Date: | 26-Sep-2019 | Publisher: | epubli | Book title: | Artificial intelligence and digital transformation in supply chain management : innovative approaches for supply chains | Volume number: | 27 | Journal or Series Name: | Proceedings of the Hamburg International Conference of Logistics (HICL) | Startpage: | 29 | Endpage: | 56 | Conference: | Hamburg International Conference of Logistics 2019 | Abstract: | Purpose: Performance of Supply Chain is highly dependent on weak spots, so-called bottlenecks. This research paper presents the findings from the analysis of operation processes of a mid-sized producing company and the digital solution for opening up the bottlenecks in order to achieve effectiveness by cutting down the order lead time. Methodology: The study is employing several rounds of simulation based on processes and data from a manufacturing company. Findings: Simulation results demonstrate that by allowing a system to take autonomous decisions for production planning based on current changes in environment such as new customer order or available capacity, the order lead time can be shortened significantly, while granting additional flexibility and robustness to the whole supply chain. Originality: The findings of this research reveal new insights on potentials of artificial intelligence in solving of existing issues within supply chain IT systems. |
URI: | http://hdl.handle.net/20.500.12738/5085 | ISBN: | 978-3-750249-47-9 | ISSN: | 2365-5070 | Review status: | This version was reviewed (alternative review procedure) | Institute: | Department Wirtschaft Fakultät Wirtschaft und Soziales Forschungs- und Transferzentrum Business Innovation Lab |
Type: | Chapter/Article (Proceedings) |
Appears in Collections: | Publications without full text |
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