With growing evidence of deep learning-assisted smart process planning, there is an
essential demand for comprehending whether cyber-physical production systems (CPPSs) …

The recent manufacturing trend toward mass customization and further personalization of
products requires factories to be smarter than ever before in order to:(1) quickly respond to …

Smart manufacturing systems have to meet high performance expectations in form of
customer individual products, short lead times, high due date reliability and resilience by the …

Computing solutions to job shop problems is a particularly challenging task due to the
computational hardness of the underlying optimization problem as well as the often dynamic …

Companies compete in a fierce market, in which the main focus is consumer satisfaction,
forcing them to respond dynamically to market changes and instabilities. Due to these …

An increasing product individualization has led to workshop (-like) production in many
companies. Mastering the resulting planning complexity has proven to be a challenging …

Decision-making in complex systems becomes even more challenging when the
environment creates volatile, uncertain, complex, and ambiguous conditions that disrupt …

The reliability of production plans drops drastically within several days after plan creation.
The reasons for the deviation between planning and execution are manifold. Causes can be …

Timely delivery is the major issue in Fast Moving Consumer Good (FMCG) since it depends
on the lead time which is stochastic and long due to several reasons; eg, delay in …

The unawareness of production planners about the interaction of key performance indicators
(KPIs) in manufacturing systems and misinterpretations of system states often leads to …