Production Management

Production Management

Learning outcomes

After the successful completion of this course, the students will have learnt

  • to describe production systems as well as the objectives and tasks of production planning and control,
  • to model and evaluate production processes,
  • to explain the economic foundation and conceptual elements of hierarchical production planning,
  • to apply basic methods of procurement and production planning as well as manufacturing control,
  • to depict the architecture of information systems for integrated production planning and control, and
  • to state the principles of Lean Production and Smart Manufacturing and to follow them for the design of real production systems.


Chapter 1:  Production systems and production planning
1.1 Production processes and production systems
1.2 Target system of production management
1.3 Performance analysis of production systems
1.4 Planning, control, and organization of production systems

Chapter 2:  Foundations of production planning
2.1 Production economics
2.2 Hierarchical planning
2.3 Coping with uncertainty

Chapter 3:  Design of framework conditions
3.1 Strategic potentials
3.2 Strategic planning
3.3 Configuration planning

Chapter 4:  Aggregate production planning
4.1 Master production scheduling
4.2 Aggregate personnel capacity planning
4.3 Aggregate project scheduling

Chapter 5:  Materials requirements planning
5.1 Classification of materials
5.2 Materials requirements forecast
5.3 Materials requirements calculation

Chapter 6:  Lot-sizing
6.1 Inventory management
6.2 Deterministic static models
6.3 Deterministic dynamic models
6.4 Stochastic models

Chapter 7:  Production scheduling
7.1 Rough-cut capacity planning
7.2 Detailed scheduling
7.3 Mixed-model line balancing and sequencing
7.4 Manufacturing control methods

Chapter 8:  Business application systems for production planning and control
8.1 PPC and ERP systems
8.2 Advanced Planning systems
8.3 Manufacturing Execution systems

Chapter 9:  Lean Production and Smart Manufacturing
9.1 Value stream orientation
9.2 Quality assurance and maintenance
9.3 Staff and supplier development
9.4 Kaizen and continuous improvement
9.5 Smart Manufacturing


  • Bloech J, Bogaschewsky R, Buscher U, Daub A, Götze U, Roland F (2014) Einführung in die Produktion. Springer, Berlin
  • Corsten H, Gössinger R (2016) Produktionswirtschaft. Oldenbourg, München
  • Curry GL, Feldman RM (2011) Manufacturing Systems Modeling and Analysis. Springer, Berlin
  • Erlach K (2020) Wertstromdesign: Der Weg zur schlanken Fabrik. Springer-VDI, Berlin
  • Günther H-O, Tempelmeier H (2016) Produktion und Logistik. Books on Demand, Norderstedt
  • Nahmias S, Olsen TL (2015): Production and Operations Analysis. Waveland Press, Long Grove
  • Neumann K (1996) Produktions- und Operations-Management. Springer, Berlin
  • Schneeweiß C (2002) Einführung in die Produktionswirtschaft. Springer, Berlin
  • Schneider HM, Buzacott JA, Rücker T (2005) Operative Produktionsplanung und -steuerung. Oldenbourg, München
  • Steven M (2018) Industrie 4.0: Grundlagen, Teilbereiche, Perspektiven. Kohlhammer, Stuttgart
  • Tempelmeier H (2008) Material-Logistik. Springer, Berlin
  • Thonemann U (2015) Operations Management. Pearson Education, München

GAMS Models

The following table compiles models and sample data for different planning problems and solution methods that are dealt with during the course. The model and example files contain source code written in the algebraic modeling language GAMS, which can be executed using the GAMS system. The GAMS system includes a greater number of state-of-the-art solvers for several types of mathematical programs, providing optimal or locally optimal solutions.

By modifying the example files, new instances can easily be generated for scenario analyses or when preparing the final course exam. A free demo version of the current GAMS system can be downloaded and installed from the web pages of GAMS Development Corp. You need a demo license for the installation, which can be requested using the form provided on the download web page. By return you will receive an email with the license, which must be added to the system during the installation process following the description in the email. The GAMS models can be edited and solved using a simple text editor called GAMS IDE or the with development environment GAMS Studio. In both environments, the comprehensive documentation of the entire GAMS system is available under the "Help" tab.

Planning problemGAMS modelExample
Assembly line balancingsalbp-1_model.gmssalbp-1_data.gms
Static master production schedulingstatic-mps_model.gmsstatic-mps_data.gms
Dynamic master production schedulingdynamic-mps_model.gmsdynamic-mps_data.gms
Aggregate personnel capacity planningpers-cap-planning_model.gmspers-cap-planning_data.gms
Capacitated EOQ modelcap-eoq_model.gmscap-eoq_data.gms
Uncapacitated lot-sizing problemulsp_model.gmsulsp_data.gms
Capacitated lot-sizing problemclsp_model.gmsclsp_data.gms
Multi-level capacitated lot-sizing problemmlclsp_model.gmsmlclsp_data.gms
Stochastic EOQ modelstoch-eoq_model.gmsstoch-eoq_data.gms
Stochastic EOQ model: Iteration methodstoch-eoq-iter_model.gmsstoch-eoq_data.gms
Rough-cut capacity planningcrcpspmax_model.gmscrcpspmax_data.gms
Age-based replacementage-replacement_model.gmsage-replacement_data.gms