In this cumulative habilitation thesis for the subject business administration a set of contributions on operations management for manufacturing companies are presented when internal and external processes are stochastic. The research carried out has been divided into two major fields. In Research Field 1 the specific managerial decisions to be taken within the hierarchical production planning process and the interaction between the hierarchical planning levels is investigated. The main contributions show how information on internal and external randomness - e.g., customer demand distribution - can improve planning decisions on different hierarchical levels and hence company profit. In Research Field 2 the economic influence of different order fulfillment policies is evaluated when manufacturing processes and customer demand are stochastic. The main contributions pertaining to this field provide decision support for anonymous pre-production and critically review the effect of information sharing on needed production capacity. These results can also be applied to improve sales policies. To derive these findings, stochastic modeling of manufacturing systems is used to provide rigid proofs of system behavior, while simulation is applied to study more complex production system structures. For the cumulative habilitation thesis, 7 peer-reviewed journal papers (rated A or B according to VHB) and 5 contributions in peer-reviewed journal proceedings are com-bined. In the field of other research with a broader scope, 4 peer-reviewed journal pa-pers (rated A or B according to VHB) and 8 contributions in peer-reviewed journal proceedings are appended.
|Translated title of the contribution||Contributions on Operations Management in Stochastic Manufacturing Environments|
|Publication status||Accepted/In press - 2016|