(218f) Reactor Network Development for Multiple Rigid Polyol Productions

In many polymer processes semi-batch reactors are used, and only a few examples of continuous reactors appear in the patent literature. As the product demand of a polymer increases, larger or more semi-batch reactors are built to meet the demand, and the capital cost per production capacity is predictably lowered. However, this capital cost is still too high for re-investment, and alternative lower capital cost solutions, such as switching the production from semi-batch to continuous processes, could help sustain growth. Hence, continuous processes can reduce the capital cost and the cost required for heat transfer equipment, since the heat load is more evenly distributed over time. In addition, continuous reactors are easier to optimize at a steady state to maximize the overall production rate. However, continuous reactors are not as flexible regarding multiple products, product transition can be difficult, and scale-up of the products requires extra investment. The motivation of this project is to switch the current production from the existing semi-batch reactors to continuous reactors, such as plug flow and continuous stir tank reactors, to lower the capital cost. Furthermore, it is not efficient to use the reactor network to produce a single rigid polyol. Therefore, we aim to construct a reactor configuration that is able to produce multiple rigid polyols. In addition, we are interested in output a pareto chart of capital cost vs. (Net sales – Operation cost).

In this talk, we first focus on developing continuous reactor network models able to produce multiple rigid polyols under strict product and safety specifications. At the same time, we determine the optimal decision profiles that lead to minimum capital cost. Decision variables include the feed rates of initiator, monomers and catalyst, reactor temperature, residence time, number and location of monomer injection points. Moreover, we narrow down the types of continuous reactors that can be part of the network to two: plug flow reactor (PFR) with multiple feed injection points and continuous stirred tank reactor (CSTR). The PFR model is a differential algebraic equation (DAE) optimization problem. The simultaneous collocation method is applied to transform the DAE into a mixed integer nonlinear programming (MINLP) problem. An iterative algorithm is proposed to solve the MINLP, where binary variables are manually fixed. After obtaining the optimal capital cost, we move on to the second stage, which can be defined as a multi-scenario design problem with multiple products, to generate the pareto chart of capital cost vs. profit.