Matthias Schmidt

21 papers Journal 6Unranked 15
YearRankTypeTitle / Venue / Authors
2026 J jnl
The Role of Reinforcement Learning in Production Control: A Systematic Literature Review.
IEEE Access
Jonas Schneider, Carl Pfannschmidt, Peter Nyhuis, Matthias Schmidt
2026 J jnl
Toward a System-of-Systems Approach for Product, Factory, and Spatial Planning: A Methodological Convergence Framework Based on a Systematic Literature Review.
IEEE Access
Mehmet Demir, Matthias Schmidt
2025 — conf
Capacity-Driven Decision Model for Impact Assessment of Product Variants in Factory Systems.
APMS (4)
Mehmet Demir, Tobias Kleinewächter, Matthias Schmidt
2025 — conf
Field-Based Assessment of Key Influence Factors for Throughput Time Prediction in Job Shop Manufacturing.
APMS (6)
Jonas Reinhold, Alexander Rokoss, Matthias Schmidt
2025 — conf
Machine Learning-Based Methodology for Root Cause Analysis of Extended Throughput Time in Production.
APMS (3)
Kira Welzel, Lucas Wieggrebe, Matthias Schmidt
2025 — conf
Reinforcement Learning in Production Control: A Deep Dive into Order Release.
APMS (1)
Jonas Schneider, Peter Nyhuis, Matthias Schmidt
2025 J jnl
Reinforcement Learning in Production Control: An Agent-Based Approach to Sequencing.
IEEE Access
Jonas Schneider, Tamara Hamfeld, Peter Nyhuis, Matthias Schmidt
2025 — conf
Scientific Concept for Analyzing the Potential of Energy-Oriented Production Planning and Control in SMEs.
APMS (5)
Manuel Rischmann, Markus Weber, Tobias Hiller, Stefan Roth, Tabea Marie Demke, Peter Nyhuis, Matthias Schmidt
2025 — conf
The Influence of the VUCA World on Production Systems: A Scenario-Based Analysis.
APMS (4)
Tanya Jahangirkhani, Eddie Sigrist, Serjosha Wulf, Matthias Schmidt
2025 — conf
Use Phase-Oriented Innovation Assessment in Early Development Stages: A Value-In-Use Approach for Thermal Interface Materials.
APMS (2)
Friederike Stefanowski, Timon Steinhoff, Luca Köhnen, Christian Klose, Matthias Schmidt, Hans Jürgen Maier, Peter Nyhuis
2024 J jnl
Case study on delivery time determination using a machine learning approach in small batch production companies.
J. Intell. Manuf.
Alexander Rokoss, Marius Syberg, Laura Tomidei, Christian Hülsing, Jochen Deuse, Matthias Schmidt
2022 — conf
Modelling Interdependencies Within Production Planning and Control: An Application-Motivated Approach.
APMS (1)
Alexander Mütze, Simon Hillnhagen, Matthias Schmidt, Peter Nyhuis
2021 — conf
Logistical Potentials of Load Balancing via the Build-up and Reduction of Stock.
IEEM
Tammo Heuer, Janine Tatjana Maier, Tim D. Busse, Matthias Schmidt, Peter Nyhuis
2020 — conf
Machine Learning-Supported Planning of Lead Times in Job Shop Manufacturing.
APMS (1)
Kathrin Julia Kramer, Carsten Wagner, Matthias Schmidt
2020 — conf
Supporting the Decision of the Order Processing Strategy by Using Logistic Models: A Case Study.
APMS (1)
Janine Tatjana Maier, Tammo Heuer, Peter Nyhuis, Matthias Schmidt
2020 — conf
Why a Systematic Investigation of Production Planning and Control Procedures is Needed for the Target-oriented Configuration of PPC.
IEEM
Alexander Mütze, Simon Hillnhagen, Philipp Schäfers, Matthias Schmidt, Peter Nyhuis
2019 — conf
Simulation Based Optimization of Lot Sizes for Opposing Logistic Objectives.
APMS (2)
Janine Tatjana Maier, Thomas Voß, Jens Heger, Matthias Schmidt
2017 J jnl
The Hanoverian Supply Chain Model: modelling the impact of production planning and control on a supply chain's logistic objectives.
Prod. Eng.
Matthias Schmidt, Philipp Schäfers
2012 J jnl
Model based logistic monitoring for supply and assembly processes.
Prod. Eng.
Ben Münzberg, Matthias Schmidt, Sebastian Beck, Peter Nyhuis
2007 — conf
Gentelligent® Parts: A Decentralized Information System for Enterprises.
CONFENIS (1)
Matthias Schmidt, Felix S. Wriggers, Frank Fisser, Peter Nyhuis
2007 — conf
Service Level Driven Stock Allocation: A Model Based Enterprise Information System.
CONFENIS (1)
Felix S. Wriggers, Matthias Schmidt, Rouven Nickel, Peter Nyhuis