Feldt, JuliaJuliaFeldtKontny, HenningHenningKontnyWagenitz, AxelAxelWagenitz2019-11-062019-11-062019-09-26Hamburg International Conference of Logistics (HICL) 27: 29-56 (2019)http://hdl.handle.net/11420/3718Purpose: 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.en2365-507020192956epublihttps://creativecommons.org/licenses/by-sa/4.0/Artificial intelligenceAssembly-to-orderBottlenecksSupply chainWirtschaftConference Paperurn:nbn:de:gbv:830-882.05405310.15480/882.2463https://www.epubli.de/shop/buch/Artificial-Intelligence-and-Digital-Transformation-in-Supply-Chain-Management-Christian-M-Ringle-Thorsten-Blecker-Wolfgang-Kersten-9783750249479/9209510.15480/882.2463Conference Paper