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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

www.vscht.cz

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

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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

unit longevity

parameters followed at the pilot and postpilot level

optimisation of the process flow sheet → cost analysis

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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

investment costs

operational costs

product purity

high conversion

etc.

selection of the most suitable criteria represents important issue

requires precise definition of the target to be reached

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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

electrode material

current density distribution

impurities in the system

physico-chemical laws seldom applicable

experimental data needed

need to minimise number of experiments in order to save costs

factorial experiments design helps to reduce it

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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 mn

m - indicates number of levels

n - number of factors

evaluation of the factor effect

example of 22 situation

c

b

effect of the factor evaluated from the difference

between mean values of the results for the high

and low factor levels

concentration (B)

d

a

current density (A)

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Process costs optimisation by the experiment

Experiments planning

weak point of 22 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

x2

modification of the equations to account for the nonlinearity

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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)

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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

storage of the products

recycling of the electrolyte

treatment of the effluents

increasing role of the separation and purification processes

typical examples – brine electrolysis and adiponitrile process

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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

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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

U0’ reversible cel voltage

j current density

A total electrode area

ac surface specific costs

D yearly capital depreciation

M molecular weight

F Faraday charge

z number of electrons exchanged

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Current density as the main factor

optimum determination

TC

VC

specific electrochemical costs

FC

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Non-selective electrochemical process

typical reasons

competing electrode reaction

product degradation at the counter electrode

product diffusion across the separator

back dissolution of the solid product

current density vs. current efficiency

efficiency decreases with increased current density

ratio U/e increases more progressively than in previous case

FC costs decrease less progressive according to 1/je

temperature vs. current efficiency

increasing temperature accompanies electrochemical processes

reduces VC due to the increased electrolyte conductivity and reduced

electrode processes activation energy

reduces process selectivity due to the reduction of the high activation energies

of the competitive reactions more progressively

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Economical analysis input parameters

Performance criteria of the electrochemical reactors

fractional conversion

estimates degree of the substrate utilisation

in some cases important impact on the product separation

conversion related yield

quantifies degree of the substrate used for the desired product

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Economical analysis input parameters

Performance criteria of the electrochemical reactors

current efficiency

electrical charge yield

overall and point (integral and differential) values are distinguished

process selectivity

closely related to the substrate utilisation and process efficiency

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Economical analysis input parameters

Performance criteria of the electrochemical reactors

energy yield

quantifies the degree of the kinetics hindrances (irreversibility)

specific energy consumption

independent of the unit size

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Economical analysis input parameters

Performance criteria of the electrochemical reactors

space time

time necessary to reach required degree of conversion

space time yield

using Faraday law

amount of product per reactor volume and time unit

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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

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