Dynamic scheduling is very important in constructing CIM and improving productivity of chemical processing systems. Computation at the scheduling level requires mostly a long time to generate an optimal schedule, so it is difficult to immediately respond to actual process events in real-time. To solve these problems, we developed dynamic scheduling algorithms such as DSMM(Dynamic Shift Modification Method) and PUOM(Parallel Unit Operation Method). Their main functions are to minimize the effects of unexpected disturbances, to predict a makespan of the updated dynamic schedule and to modify schedule desirably in real-time responding to process time variations. As a result, the algorithms generate a new pertinent schedule in real-time which is close to the original schedule but provides an efficient way of responding to the variation of process environment. Examples in a shampoo production batch process illustrate the efficiency of the algorithms.