An optimal catalyst management strategy for Oxo processes

Oxo processes with rhodium-based catalysts play an important role in the ma nufacture of higher aldehydes and alcohols. Here we present a modeling meth odology for the entire process using differential reaction rate equations a nd we formulate a nonlinear programming strategy (NLP) to obtain an optimum catalyst management policy. Also, effective and robust algorithms are deve loped to converge this larger problem. The optimal results show that the op timal catalyst management policy leads to a trade-off between activities an d prices of different types of available catalyst; in addition to an optimi zed schedule. catalyst addition policy and adjusted operation conditions. T he resulting optimal management strategy leads to a robust NLP-based schedu ling strategy that shows significant savings in the current operation of th e plant. (C) 2000 Elsevier Science Ltd. All rights reserved.