关注
Mirko Kück
Mirko Kück
Data Scientist / Project Leader / Lecturer, Mercedes-Benz AG
在 mercedes-benz.com 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Solving the Job-Shop Scheduling Problem in the Industry 4.0 Era
M Leusin, E Frazzon, M Uriona Maldonado, M Kück, M Freitag
Technologies 6 (4), 107, 2018
1182018
Data-driven production control for complex and dynamic manufacturing systems
EM Frazzon, M Kück, M Freitag
CIRP Annals 67 (1), 515-518, 2018
1162018
Hybrid approach for the integrated scheduling of production and transport processes along supply chains
EM Frazzon, A Albrecht, M Pires, E Israel, M Kück, M Freitag
International Journal of Production Research 56 (5), 2019-2035, 2018
992018
Forecasting of customer demands for production planning by local k-nearest neighbor models
M Kück, M Freitag
International Journal of Production Economics 231, 107837, 2021
862021
Potential of data-driven simulation-based optimization for adaptive scheduling and control of dynamic manufacturing systems
M Kück, J Ehm, T Hildebrandt, M Freitag, EM Frazzon
2016 Winter Simulation Conference (WSC), 2820-2831, 2016
602016
Potential of a Multi-Agent System Approach for Production Control in Smart Factories
ME Leusin, M Kück, EM Frazzon, MU Maldonado, M Freitag
IFAC-PapersOnLine 51 (11), 1459-1464, 2018
582018
Meta-learning with neural networks and landmarking for forecasting model selection an empirical evaluation of different feature sets applied to industry data
M Kück, SF Crone, M Freitag
2016 international joint conference on neural networks (IJCNN), 1499-1506, 2016
522016
A Data-Driven Simulation-Based Optimisation Approach for Adaptive Scheduling and Control of Dynamic Manufacturing Systems
M Kück, J Ehm, M Freitag, EM Frazzon, R Pimentel
Advanced Materials Research 1140, 449-456, 2016
352016
Evaluating the Robustness of Production Schedules using Discrete-Event Simulation
GE Vieira, M Kück, E Frazzon, M Freitag
IFAC-PapersOnLine 50 (1), 7953-7958, 2017
342017
Prediction of customer demands for production planning–Automated selection and configuration of suitable prediction methods
B Scholz-Reiter, M Kück, D Lappe
CIRP Annals-Manufacturing Technology 63 (1), 417-420, 2014
342014
Towards adaptive simulation-based optimization to select individual dispatching rules for production control
M Kück, E Broda, M Freitag, T Hildebrandt, EM Frazzon
Winter Simulation Conference (WSC), 2017, 3852-3863, 2017
312017
Potenziale von Data Science in Produktion und Logistik: Teil 2 - Vorgehensweise zur Datenanalyse und Anwendungsbeispiele
M Freitag, M Kück, A Ait Alla, M Lütjen
Industrie 4.0 Management 31 (6), 39-46, 2015
27*2015
Potenziale von Data Science in Produktion und Logistik: Teil 1 - Eine Einführung in aktuelle Ansätze der Data Science
M Freitag, M Kück, A Ait Alla, M Lütjen
Industrie 4.0 Management 31 (5), 22-26, 2015
24*2015
Towards a simulation-based optimization approach to integrate supply chain planning and control
MC Pires, EM Frazzon, AMC Danielli, M Kück, M Freitag
Procedia CIRP 72, 520-525, 2018
222018
Towards Networking Logistics Resources to enable a Demand-Driven Material Supply for Lean Production Systems–Basic Concept and Potential of a Cyber-Physical Logistics System
KD Thoben, M Veigt, D Lappe, M Franke, M Kück, R Zimmerling, J Schlick, ...
Proceedings of the 7. BVL Scientific Symposium on Logistics, BVL Int …, 2014
212014
A genetic algorithm to optimize lazy learning parameters for the prediction of customer demands
M Kück, B Scholz-Reiter
Machine Learning and Applications (ICMLA), 2013 12th International …, 2013
152013
Potentials and Risks of Resource Sharing in Production and Logistics
M Freitag, M Kück, T Becker
Proceedings of the 8th International Scientific Symposium on Logistics, 199-209, 2016
11*2016
Emergence of Non-predictable Dynamics Caused by Shared Resources in Production Networks
M Kück, T Becker, M Freitag
Procedia CIRP 41, 520-525, 2016
92016
Using Industry 4.0’s Big Data and IoT to Perform Feature-Based and Past Data-Based Energy Consumption Predictions
J Gumz, DC Fettermann, EM Frazzon, M Kück
Sustainability 14 (20), 13642, 2022
62022
Robust Methods for the Prediction of Customer Demands based on Nonlinear Dynamical Systems
M Kück, B Scholz-Reiter, M Freitag
Procedia CIRP 19, 93-98, 2014
42014
系统目前无法执行此操作,请稍后再试。
文章 1–20