Capacity management under uncertainty with inter-process, intra-process and demand interdependencies in high-flexibility environments

In this paper, we develop models for capacity planning within the framework of stochastic processing times and stochastic demand for different process outcomes in high-flexibility environments. We particularly address stochastic interdependencies between processing times for different processes (inter-process correlation), interdependencies between the capacity consumption (task times) of different executions of the same task in a given production stage (intra-process correlation) as well as interdependencies between the demand for different process outcomes. After presenting the base model, we conduct extensive sensitivity analyses and analyze the main relationships between different model variables. We use process and demand data from the financial industry to demonstrate the applicability and relevance of our findings.