Showing results 32 to 51 of 88
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| Issue Date | Title | Author(s) |
| 2022-01-01 | Early Quality Prediction using Deep Learning on Time Series Sensor Data | Saadallah, A; Abdulaaty, O; Büscher, J; Panusch, T; Morik, K; Deuse, J |
| 2019-01-22 | Enabling of Predictive Maintenance in the Brownfield through Low-Cost Sensors, an IIoT-Architecture and Machine Learning | Strauß, P; Schmitz, M; Wöstmann, R; Deuse, J |
| 2016-01-01 | Enhanced predictability of agile procedures | Bellmann, A; Schneider, S; Schallow, J; Hartung, J; Litterscheidt, J; Deuse, J |
| 2019-02-01 | Evaluation model for the analysis of data maturity | Eickelmann, M; Wiegand, M; Deuse, J; Bernerstätter, R |
| 2016-01-01 | Excellent, lean production: Framework on the base of systematic variability and lead time reduction and continuous improvement cycles. | Roth, N; Deuse, J |
| 2022-01-01 | Explainable Predictive Quality Inspection using Deep Learning in Electronics Manufacturing | Saadallah, A; Büscher, J; Abdulaaty, O; Panusch, T; Deuse, J; Morik, K |
| 2024-05-14 | Extracting Key Value Streams Using Process Mining and Machine Learning | Tomidei, L; Sick, N; Deuse, J; Guertler, M |
| 2023-01-01 | Flexible job shop scheduling with preventive maintenance consideration | Wocker, MM; Ostermeier, FF; Wanninger, T; Zwinkau, R; Deuse, J |
| 2023-01-01 | Forecasting Algae Growth in Photo-Bioreactors Using Attention LSTMs | Boiar, D; Killich, N; Schulte, L; Hernandez Moreno, V; Deuse, J; Liebig, T |
| 2023 | Framework for predictive sales and demand planning in customer-oriented manufacturing systems using data enrichment and machine learning | Syberg, M; West, N; Lenze, D; Deuse, J |
| 2018-01-01 | From production planning flows to manufacturing operation management KPIs: linking ISO18828 & ISO22400 standards | Varisco, M; Deuse, J; Johnsson, C; Nöhring, F; Schiraldi, MM; Wöstmann, R |
| 2023-02-08 | Guided Learning from Demonstration for Robust Transferability | Sukkar, F; Moreno, VH; Vidal-Calleja, T; Deuse, J |
| 2023-07-04 | Guided Learning from Demonstration for Robust Transferability | Sukkar, F; Moreno, VH; Vidal-Calleja, T; Deuse, J |
| 2023-01-01 | How Moderator Variables Affect Scheduling Objectives in Unpaced Mixed-Model Assembly Lines | Ostermeier, F; West, N; Deuse, J |
| 2022-05-01 | Identification and Prediction of Dynamic Bottlenecks - Conception and User Requirements for a Practical Process Selection and Further Development | Schwenken, J; Schallow, J; Sollik, D; Richter, R; Deuse, J |
| 2020-10-01 | Implementing industrial data science | Nolte, V; Sindram, T; Mazarov, J; Deuse, J |
| 2020-01-01 | Implementing Industrial Data Science - Interview based study on success factors and obstacles | Nolte, V; Sindram, T; Mazarov, J; Deuse, J |
| 2019-01-01 | Increasing flexibility of employees in production processes using the differential learning approach – adaptation and validation of motor learning theories | Weisner, K; Knittel, M; Jaitner, T; Deuse, J |
| 2019-12-01 | Industrial data science in value creation networks | Mazarov, J; Wolf, P; Schallow, J; Nöhring, F; Deuse, J; Richter, R |
| 2019-01-01 | Influence and causes of variability in customer order-specific production | Wolf, P; Deuse, J; Richter, R |
