Optimisation and Process Economy Karel Bouzek Department of Inorganic Technology, Institute of Chemical Technology Prague H. Wendt, G. Kreysa: Electrochemical Engineering, Science and Technology in Chemical and Other Industries, Springer, Berlin 1999

Process economy and research work Shall the process economy be considered in the research work? basic research oriented on the understanding of the substance of the process has not direct relation to possible application costs don’t represent an issue great situation for the researcher applied research the aim is typically to assess potential of the system for application typically substantial research work need to adopt basic research results provides input information for the economical analysis of the process continuous evaluation of the process costs substantial more difficult multidisciplinary point of view formally turns important part of the attention away from “science” irreplaceable for the process commercialisation offers exciting challenges from the engineering point of view

Process economy and research work Economical analysis more levels needed raw analysis on the process viability resulting from the basic research results detail analysis based on the applied research work real reliable data available first after pilot-plant experiments no one step can be avoided, typically more steps added parameters followed typically at the prepilot level electrical energy consumption reaction efficiency reaction selectivity cell effluent composition parameters followed at the pilot and postpilot level optimisation of the process flow sheet → cost analysis unit longevity

Process costs optimisation by the experiment Fundamental assumptions underlying process optimisation more solution muss exists in optimal cases the solutions are known often alternative solutions have to be found and evaluated quantitative parameters allowing comparison muss exist based on the optimisation target selection of the most suitable criteria represents important issue requires precise definition of the target to be reached investment costs operational costs product purity high conversion etc.

Process costs optimisation by the experiment Fundamental assumptions underlying process optimisation general individual steps towards optimised process definition of the target quantity (quantities) establishing suitable type of mathematical model (physico-chemical, statistical, …) definition of the target quantity (quantities) dependence on the process variables determining extreme on the dependence (optimisation) formulation of the quantity optimum dependence on the remaining process parameters dependence of the reaction engineering quantities on the adjustable parameters generally highly complex dependence influenced by several hardly quantified parameters physico-chemical laws seldom applicable experimental data needed need to minimise number of experiments in order to save costs electrode material current density distribution impurities in the system factorial experiments design helps to reduce it

Process costs optimisation by the experiment Experiments planning factorial experiments design influencing variables referred to as factors values of factors called levels levels chosen on the base of previous knowledge number of experiment to be completed is equal to m n m - indicates number of levels n - number of factors evaluation of the factor effect example of 2 2 situation effect of the factor evaluated from the difference between mean values of the results for the high and low factor levels current density (A) concentration (B) a b c d

Process costs optimisation by the experiment Experiments planning weak point of 2 2 approach – considering linearity of the dependence verification – introducing central element the results should coincide with the central experiment if the condition is not satisfied, alternative solution has to be searched solution of the nonlinearity problem transformation of the experiment results typical transformations used in chemical engineering ln x 1/x x2x2 modification of the equations to account for the nonlinearity

Process costs analysis Costs composition fixed costs (FC) capital investment fixed amount per year for amortisation variable costs (VC) often also called operational costs expenditures for the raw materials, energy, labour etc. maintenance costs (MC) not necessarily much dependent on the operational variables character similar to the fixed costs total costs (TC) correspondingly Relevant parameter – TC per unit of product (specific costs)

Process costs analysis Investment costs consist of two main parts – electrochemical and chemical ones electrochemical part rectifier, busbars, cell, electrodes, … in classical inorganic process represents the major part of the FC chemical part preparation of the electrolyte mixture separation and purification of the product typical examples – brine electrolysis and adiponitrile process storage of the products recycling of the electrolyte treatment of the effluents increasing role of the separation and purification processes

Process costs analysis Remaining types of costs situation almost identical with the FC variable costs maintenance costs total costs specific costs interrelation of electrochemical and chemical part of the costs

Process costs optimisation Current density as the main factor important factor influencing costs significantly increased current density increases VC increased current density reduces FC R * effective cell resistance U 0 ’ reversible cel voltage j current density A total electrode area a c surface specific costs D yearly capital depreciation M molecular weight F Faraday charge z number of electrons exchanged

Process costs optimisation Current density as the main factor optimum determination TC specific electrochemical costs VC FC

Process costs analysis Non-selective electrochemical process typical reasons current density vs. current efficiency efficiency decreases with increased current density ratio U/  e increases more progressively than in previous case temperature vs. current efficiency increasing temperature accompanies electrochemical processes reduces VC due to the increased electrolyte conductivity and reduced competing electrode reaction product degradation at the counter electrode product diffusion across the separator back dissolution of the solid product FC costs decrease less progressive according to 1/j  e electrode processes activation energy reduces process selectivity due to the reduction of the high activation energies of the competitive reactions more progressively

Economical analysis input parameters Performance criteria of the electrochemical reactors fractional conversion conversion related yield quantifies degree of the substrate used for the desired product estimates degree of the substrate utilisation in some cases important impact on the product separation

Economical analysis input parameters Performance criteria of the electrochemical reactors current efficiency process selectivity closely related to the substrate utilisation and process efficiency electrical charge yield overall and point (integral and differential) values are distinguished

Economical analysis input parameters Performance criteria of the electrochemical reactors energy yield specific energy consumption independent of the unit size quantifies the degree of the kinetics hindrances (irreversibility)

Economical analysis input parameters Performance criteria of the electrochemical reactors space time space time yield using Faraday law time necessary to reach required degree of conversion amount of product per reactor volume and time unit

Conclusion Process economy important aspect of the applied research unintentionally followed by the majority of us may significantly complicate or prevent realisation of many nice ideas it deserves larger attention to avoid inefficient spending of the resources