Variation is the archenemy of quality. To reduce or control the variation in a complex production unit, firstly we need to identify the location of the root cause of the variation. This paper discusses the detection of variability and the techniques used for reduction of variation for a production unit consisting of many processes. In the first part of this paper, the background of variability detection in production systems is introduced which is then followed by a weighted network corresponding to correlation matrix of all processes. Based on the network and clustering criterion of maximum spanning tree, a classification of all processes is derived. Furthermore, the variation of each process in a class is determined by residual analysis. In the last part, the use of methods of robust design for the processes with a larger variability is discussed.