The complexity of a manufacturing system is determined by the uncertainty in achieving the system’s functional requirements and is caused by two factors: by a time-independent poor design that causes a system-inherent low efficiency (system design), and by a time-dependent reduction of system performance due to system deterioration or to market or technology changes (system dynamics). To maximize the productivity of a manufacturing system, its entire complexity must be reduced. Many valid methods have been developed so far addressing different single manufacturing and quality issues. But to continuously increase the productivity of a manufacturing system within a turbulent environment its entire complexity must be reduced. This requires a holistic understanding and knowledge about the system. To reduce a system’s complexity, its subsystems should not overlap in their contribution to the overall system’s functionality, they must be mutually exclusive. On the other hand, the interplay of system’s components must be collectively exhaustive in order to include every issue relevant to the entire system’s functionality. This paper introduces a concept for complexity reduction in manufacturing systems with the help of Nam P. Suh’s Axiomatic Design principles. In a first step, time-dependent elements are separated from time-independent elements. To eliminate the real complexity of the time-independent elements (so called manufacturing modules), a set of alternative design parameters are defined that fit the system range of the manufacturing module’s set of functional requirements. To reduce the time-dependent combinatorial complexity, a methodology is proposed to systematically define an entire manufacturing system’s functional requirements within very short times in order to guarantee a fast reconfiguration of the system considering internal and external system dynamics. With the help of practical examples and the obtained results, the validity of the approach is illustrated.