Amazing great post on cross-cultural negotiation

In this article, the author (Erin Meyer) draws on her work on cross-cultural management to identify five rules of thumb for negotiating with someone whose cultural style of communication differs from yours. The trick, as we will see, is to be aware of key negotiation signals and to adjust both your perceptions and your actions in order to get the best results.

For full post, check this out. HBR

TSK (Tsukishima KIKAI) - Ion Exchange / Chromatography Separator

http://www.tsk-g.co.jp/en/tech/equip/ion.html

ISEP/CSEP is an innovative machine developed by Advanced Separation Technologies Inc. in the US (now owned by Calgon Carbon Corporation). ISEP collects usable components and removes unnecessary components from the liquid. CSEP is applicable for Chromatographic separation.
[Major applicable process]
Purification of amino acids, desalting and decoloring of glucose and sugar
Collection of valuables from wastewater
Collection and purification of vitamins
Chromatographic separation etc.
[Features]
In comparison with the fixed bed type, Running cost is reduced
Reduced amount of water and chemical usage (approx. 1/4)
Reduced resin fill-up amount for Ion exchange (approx. 1/2)
Easy operation
Reduced installation space
Easy maintenance due to valve usage
High separation capacity
High reliability
Due to its simple structure, little time is required to maintain the equipment, and proves high reliability

Nippon Rensui / Ameridia - Chromatography Process

http://www.rensui.co.jp/en/products/separation/chromato.html
http://www.ameridia.com/html/ic.html

Nippon Rensui Co. has been developing a new separation and purification process using chromatographic separation technology originally developed by Mitsubishi Chemical Co. group, combined with experienced distinguished application technology for ion exchange resins.
In 1977 our technology was originally established as the continuous separation process between fructose and glucose in the high fructose corn syrup(HFCS) production process, then became an essential process in this industry, and more than 100 plants have been built and operated in the world.
Furthermore, we have been seeking to improve and spread this technology for new field such as separation and purification of sugar, oligosaccharide and other foodstuffs or pharmaceuticals.

Industrial Chromatography Example - Dow Water & Process Solutions

http://www.dowwaterandprocess.com/en/industries-and-applications/food_and_beverage/sweeteners/corn_and_starch_sweeteners/chromatographic_enrichment

Chromatographic Enrichment

Industrial scale chromatography used in the sweetener industry is dependent on highly engineered chromatography media based on ion exchange (IX) technology. Depending on the polymer density, or microporosity, and ionic form, sweeteners can be separated from salts, and sweetener-related products can be separated from each other through both ligand exchange and size exclusion chromatography. Dow Water & Process Solutions is the premier supplier of engineered, industrial scale chromatography media, offering a full range of DOWEX™ MONOSPHERE™ products for a wide range of applications. This table shows examples of commercial applications of industrial scale chromatography employed in the sweetener industry. For more information on this subject, please read the technical manual, "Chromatographic Separation of Fructose and Glucose with DOWEX MONOSPHERE Ion Exchange Resins."

Applications of Chromatography in Sweeteners

• Sugar recovery from Molasses
• Fructose – Glucose Separation
• Fructose Enrichment – Crystalline Fructose
• Glucose Enrichment – Crystalline Glucose
• Hydrogenated sugars purification

Are you also too busy to improve?

How to call .Net library from Excel

This method has been verified using Visual Studio 2010 and MS Office 2010. It works!!

(Reference: http://richnewman.wordpress.com/2007/04/15/a-beginner%E2%80%99s-guide-to-calling-a-net-library-from-excel/ )

(1) Create a public .Net class and have a public method therein. ClassInterface will allow ‘intelligence’ feature on VBA, so it is useful to have. For example:

    Imports System
    Imports System.Collections.Generic
    Imports System.Text
    Imports System.Runtime.InteropServices

    ClassInterface(ClassInterfaceType.AutoDual)_
    Public Class DotNetClass
      Public Sub DotNetMethod(ByRef input As String, ByRef output As String)
        output = "Hello" + input
      End Sub
    End Class

    Let’s assume the filename is Test.dll

(2) On the project Assembly Information, give a check to “Make assembly COM-Visible”

(3) Build library

(4) On Excel , create VBA code for testing. For example,           

   Sub Button1_Click()
   Dim testClass As New DotNetClass
   Dim inp As String
   Dim out As String
   inp = "World"
   Call testClass.DotNetMethod(inp, out)
   MsgBox (out)
   End Sub

(5) For deployment to others who doesn’t have a programming environment, the deliverables are Test.dll only.

(6) To register all public classes contained in Test.dll, and generates and registers the type library Test.tlb, which contains definitions of all the public types defined in Test.dll. Open Command Window, Use following command for registration:

  C:\windows\microsoft.net\Framework\v4.0.30319\regasm.exe /codebase Test.dll /tlb: Test.tlb

An important advice is that you must use 32bit version of regasm.exe in .Net 4.0 even if your computer is 64 bit. It is because .NET library is compiled for 32 bit (in VS2010).

Things to know when you choose Aspen reactor model

I think this is useful, concise information to know about the reactor model in Aspen Plus (and Dynamics as well). Thanks to original commenter - David Tremblay. His original comment is found in LinkedIn comment ID 78253172 .

Aspen Plus includes three types of reactor models. The type you choose depends on the level of rigor you want to use and the amount of information you have available:

(1) Balance/conversion reactors - RSTOIC, RYIELD - These reactors are for mass and energy balance purposes. You specify the conversion or yield and the reaction stoichiometry. In essence, you tell Aspen the expected result and it handles the details of the mass, energy, and species balances.

(2) Equilibrium reactors - REQUIL, RGIBBS - These reactor models are appropriate for fast reactions that reach equilibrium quickly (although there are ways to specify approach to equilibrium for non-ideal cases). RGIBBS is the most flexible model. It allows multiple phases (including multiple solid phases) and multiple species. This model uses Gibbs free energy minimization to predict results. It requires accurate thermodynamics since Gibbs energy is calculated from enthalpy and entropy.

(3) Rate-based kinetic reactors - RBATCH, RCSTR, RPLUG These models are appropriate when you know the reaction kinetics. You describe kinetics using one of the built-in reaction models (power law, LHHW, etc.) or your own user-defined kinetic subroutine. RBATCH and RCSTR are able to represent reactors with solid-phase catalysts. RPLUG can represent tubular or multi-tube plug flow reactors. RCSTR represents any well mixed stirred tank (or fluid bed) reactors. RBATCH is for batch reactors. These reactor models are more predictive, but they require more information to describe reaction rates.

Some compiler options to improve computing performance in VB.NET

I often see that some people claims that VB is slower than C#. I have talked with different people and searched information to confirm whether it is true. This could be untrue but my conclusion so far is that there's no fundamental difference in between two language types within .NET Framework. Then why the programmers complains that VB is slower. It seems that the default compiler options set by the IDE (Visual Studio) is more conservative for VB than C#. As I can easily forget such valauable information, I decide to write the information in the blog.

In VS2010,

1. Compiler Options under Compiler Page

Set "Option Strict" = On

2. Advanced Compiler Settings within the Compiler Options under Compiler Page

Give a check for "Remove integer overflow checks"
Give a check for "Enable optimizations"
Set On for "Generate serialization assembles" --> I was told this is good for WPF XAML performance

If anyone has an ojection or has an opinion, please leave your note, so that I can learn from it.

Boehringer to create biosimilars division (original post in www.inpharm.com)

Another post on biosimilar business initative... by Boehringer Ingelheim.
The original post can be found at http://www.inpharm.com/news/168064/boehringer-biosimilars-division
----
Boehringer Ingelheim is to tap into the growing interest in biosimilars with the creation of a division dedicated to that market. The new venture, which the manufacturer says will be a separate business, is tasked with developing and commercialising Boehringer’s own biosimilars.

“We believe that biosimilars will become a major part of the biopharmaceutical market and will enable many more patients access to important medicines,” explained Wolfram Carius, member of Boehringer’s board of managing directors.

“We feel confident that we are able to leverage our capabilities in product development, supply and clinical expertise at Boehringer Ingelheim to offer high quality biosimilars understanding patients’ needs,” he added.

Biosimilars differ from generics in that they are close copies of, rather than identical to, off-patent biologic brands.

Growing interest in biosimilars

+ Boehringer’s move mirrors that of Merck & Co, which entered the sector in earnest in 2009 after creating a dedicated division, Merck BioVentures, and has shown serious intent this year in particular.

+ In June Merck announced it was to develop its own version of Pfizer’s ageing arthritis drug Enbrel with South Korean manufacturer Hanwha Chemical Corporation.
Hanwha has been working on HD203, a candidate biosimilar form of TNF inhibitor Enbrel (etanercept).

+ And in January Merck entered an agreement with contract research organisation Parexel to help boost biosimilar development: the company has said it planned to have five biosimilars in late-stage clinical trials by 2012.

+ Those in the pipeline include a biosimilar of Amgen’s Neupogen (filgrastim), an investigational recombinant granulocyte-colony stimulating factor (G-CSF) drug to prevent infections in cancer patients receiving chemotherapy.

Pharma manufacturers are not the only ones showing an interest in biosimilars: earlier this year South Korean electronics giant Samsung formed a joint venture with Quintiles to break into the market. At the heart of the tie-up is the construction of a biopharmaceutical production facility in Songdo, South Korea, with the intention of getting its first biosimilars to market in 2016.

Adam Hill

Tech opportunity in biologics - biosimilar drug market

Biosimilar is a hot issue these days among bio-pharmaceutical businesses. Well, today no one could predict the future and tell a definite answer whether the biz idea could indeed be realized (as those investors has wanted). However, I could see there are number of opportunities for chemical engineers if the biosimilar business is indeed accepted by common and politicians. The opportunities would present in bio-pharmaceuticals, including (1) downstream process modeling (2) continuous processes, especially in reaction and purification (3) biosimilar properties, and may be more. Since the bio-species are large molecules and its physical properties are mostly not known, therefore it is likely that a computer simulation approach upon molecular modeling and statistical physics could get attention from publics and eventually any predictive methods should be incorporated with first principle mathematical models in chemical engineering. Such demand may be challenging for those who has fixed idea in traditional chemical engineering approach, but it would create big opportunities for those who has young and new mind with ability to integrate IT and chemical engineering….

Here is a news about Samsung’s involvement in biosimilar business. Such movement indicate it is not a joke.. Samsung won’t do this if it is not feasible idea. They are good and smart. (Original article posted at http://www.firstwordplus.com/Fws.do?articleid=1003E8EAB47E4ECDA43229969E719985)

Samsung announced plans to establish a joint manufacturing venture with Quintiles to produce biologic drugs, as part of a series of moves by the South Korean company to diversify its businesses in order to drive growth. Samsung executive vice president Kim Tae Han noted that the unit is expected to start supplying biologic drugs in the first half of 2013, adding that the company is also looking to enter the biosimilar market.

The joint venture, which will initially have 300-billion won ($266 million) of capital, will begin construction of a plant near Seoul in the first half of the year. Once operational, the facility will produce biologic drugs under contract, with the majority being sold overseas. Kim remarked that due to demand for biopharmaceuticals, Samsung may exceed its target to generate 1.8 trillion won ($1.6 billion) a year by 2020 from these products.

Kim added that the company may also establish another joint venture to make biosimilars this year. In May, Samsung said it had 23.3 trillion won ($20.7 billion) to invest in five new business areas by 2020, with 2.1 trillion won ($1.9 billion) set aside for biopharmaceuticals. Half of the budget for biologic drugs will be spent on developing the products and the other half will be used to construct factories.

The executive said the first biosimilar that Samsung would target would be Roche and Biogen Idec's Rituxan (rituximab), which has patent protection in the US until 2018 and in the rest of the world through 2013. The company expects to begin producing biosimilars in 2016, and ultimately aims to develop its own biopharmaceuticals after gaining experience in making them, Kim commented.

Column dynamics for non-Langmuirian equilibrium

We often see quite complex column dynamics when equilibrium does not follow a Langmuir type (i.e. IUPAC Type I). As a matter of fact, the effects of the equilibrium isotherm shape on breakthrough curve or chromatogram are far more significant in process design, revamp and analysis. I found this interesting video does demonstrate such interesting dynamics in liquid chromatography column.

Another one for VARICOL process

Very interesting SMB simulator in YouTube

Multicompartment process model for loose-coupling with a CFD simulation

It is probably a fact that a distributed mathematical model could represent (or model) a target system more precisely and rigorously. However, we also admit that too much detailed model could be too heavy to solve.

These days, there are many demands in CFD simulation to get a better understanding of chemical processes and the phenomenon involved. In the meantime, we also perform a traditional process simulation for design and optimization study. How come such different approaches could be integrated to make our life easy. I think we could find a solution from "hydrid modeling".

A multi-compartment modeling method (based on UNIT CELL model) could offer followings:

- Allow one to model and simulate rigorous mixing effects by complex equipment geometry
- Useful for reaction system that requiring viscous fluid dynamics simulation
- More realistic representation of industrial reactor rather than perfect mixing RBatch or RCSTR model

Using UNIT CELL, one could represent a geometry and also characterize "interractions" between CELLs.

This concept could be extended to much more complex modeling. And it could be coupled with CFD simulation. Well, the degree of the coupling is truely a demand-basis. From experiences, loose-coupling may b enough (i.e. few manual iteration should suffice the requirement). However, it should be possible to close the "Loop".

The above captured screenshots are from a consulting project that I provided in 2005. I still remember the customer really liked it. By the way, this modeling work has been done using Aspen Custom Modeler.

Is there any utility in HYSYS for PSA(Pressure Swing Adsorption) simulation

As of today, there isn't a utility in HYSYS for PSA or any other type of adsorption processes. Aspen Adsorption (formerly known as Adsim) is an independent product for gaseous adsorption processes, however currently no methods available to either interface or use Adsorption in HYSYS. In HYSYS V7.1, an ACM model export may be a useable application, thus in theory, it should be possible to export Adsorption simulation into HYSYS (Dynamics). Another possible approach could be developing a PSA simulation using CSS model approach (a steady state modeling method by discretizing time and space) available in Aspen Adsorption, and then export it to HYSYS (Steady-State). Another method I could imagine is utilizing ASW (Aspen Simulation Workbook) to interface HYSYS and Adsorption. I personally believe any above option should be possible, but none of them has been so far tested internally (in Aspen) and externally (as far as I know). The important question is whether the feature is really needed. Some industrial adsorption processes (such as Polybeds for Hydrogen separation or Parex for p-Xylene extraction) are quite rigidly pre-configured process therefore it must be beneficial to have integrated application within HYSYS framework. In the past, I met several people who has shown interests on such integration. However I never seen any people who seriously wants to have such model and willing to pay for it. I think it is a gap in between "dream" and "reality". If you are really serious on that matter, let me know, perhaps I could help.

[original post]
http://www.linkedin.com/groupAnswers?viewQuestionAndAnswers=&gid=1902045&discussionID=21678314&sik=&trk=mywl_artile&goback=%2Emwg_*2_1

What are the most useful programming languages for Chemical Engineers?

Basically, any computer language should be good. However, if you want to extend your codes (or routines) to commercial software, then the selection of "which" language may be an important factor. Typically a commercial software provides some tutorial examples (or cases), to learn how to connect or re-use a specific computing code in the commercial software. Thus it would be wiser to determine "useful" language to going forward.

1) If you want to re-use your codes in some commercial software
- Aspen Plus: FORTRAN is the most popular and best language to use
- Aspen Plus Dynamics/Aspen Custom Modeler: either FORTRAN or C is good
- HYSYS and HYSYS Dynamics: Visual Basic (VB6 or VB.Net) is good. C#.Net is also good (but examples are rare)

2) If you want to run or link with commercial software
Perhaps Excel VBA provides the best exercise. VB.Net (or C#.Net) is also good.

RGibbs in Aspen Plus Dynamics

Some discussions on RGibbs model in Aspen Plus Dynamics...

1) PFR configuration for RGibbs:
PFR-RGibbs additionally calculates response-delay and equipment-volume for given geometry data. We could tell it is a minimum effort to take account the holdup contribution, but it is not done in rigorous way. Personally I don't suggest PFR configuration in RGibbs since it doesn't look theoretically sound. When a holdup is considered for RGibbs, it perhaps better to combine an Instantaneous-RGibbs and a Dynamic-Mixer (before or after the RGibbs), instead of PFR-RGibbs. Basically PFR-RGibbs is not a distributed model therefore there won't be real Plug-Flow effect at all.

2) Slow performance due to PFR configuration:
Such drawback in integration performance may be because of the complexity in delay function and volume calculation. It is not directly related to RGibbs calculation. In Aspen Plus Dynamics, RGibbs is (only one!!) the procedural model, which reuses A+ RGibbs calculation. It means its computational performance in dynamics (for RGibbs block) is identical to what A+ exhibits. Basically it carries out series of SS calculation continuously along integration time.

3) Why RGibbs?
Probably the most merit of RGibbs is that it does not require reaction stoichiometry. Without such detail reaction data, RGibbs can determine phase equilibrium by minimizing Gibbs free energy, subject to atom balance constraints at given process condition (T,P or P,H). For instance, when you model a burner, which is fundamentally a reactor but you perhaps don’t know details of what’s happening inside, RGibbs may be the one to use. There is no suggested criteria to choose RGibbs, but data-availability may be one of the major reason when choosing RGibbs.

Simulation Gets a New Dynamic

In many ways, modeling has become an established tool for process engineers. Steady-state simulations are now routine for much process design work, while the more-challenging world of dynamic simulation has virtually spawned the rapidly growing market for operator training systems (OTS’) for everything from tightly integrated petrochemical complexes to offshore platforms. However, few would question that dynamic simulation could play a greater role in process engineering. The question is whether it is now poised for wider adoption by practicing process engineers.

The ability to mathematically model a process and its unit operations from first principles arguably dates back to the advent of the first computers powerful enough to do the number crunching — but those mainframe and VAX days are long gone. “Most of us in the past in the chemical industry had our own simulators, before they became commercially available,” recalls John Pendergast, senior technical leader with Dow’s Engineering and Process Sciences Laboratory in Midland, Mich. But the processing and modeling times involved then were hardly suited to dynamic simulations. “Realistically,” he says, “the ability to solve dynamic problems is only about three to four years old.”

(click the following link to read the complete article)

Simulation Gets a New Dynamic
Mike Spear, ChemicalProcessing.com
Efforts aim to boost the use of dynamic models by process and control engineers.

Role of SMB Chromatography Process Simulator

1. Chromatography as a manufacturing process

Traditionally a chromatographic separation refers a measurement technique rather than a manufacturing process. Concerning the driving force that enables a separation, it is achieved due to the different rates of migration for pure substance in a mixture – e.g. the smaller the affinity a molecule has for the stationary phase, the shorter the time spent in a column. Such different migration rates could be explained by various mechanisms in between molecule (mobile phase)–adsorbent (stationary phase) and molecule–molecule interactions. The followings are well-known interaction mechanisms driving a chromatographic separation:

- Elution chromatography
- Displacement chromatography
- Ligand-exchange chromatography
- Size-exclusion chromatography
- Ion-exclusion chromatography
- Reverse phase chromatography

It is not a surprise that we can see various chromatography applications from industry. High purity product is crucial for certain industry, for example, Life Sciences, and chromatographic separation guarantees very high product purity. However it should be noted that much of what is written about chromatographic separation as a process operation is somewhat misguided and written from an analytical measurement perspective.

Perhaps the most popular chromatographic separation practise in a research laboratory is analytical chromatography such as LC (Liquid Chromatography) or GC (Gas Chromatography). The analytical chromatography system consists of three major parts, injection, column, and detector. For LC system, depending on the injection method, the operation is classified as either isocratic elution (constant mobile phase concentration) or gradient elution (continuous change in mobile phase concentration). While analytical chromatography focuses on the measurement, the main goal of industrial chromatography is achievement of high purity and recovery of target product, and high throughput. Regardless of any difference in objectives, there is actually no difference in terms of separation principle for both applications. For instance, preparative elution chromatography is one of the most popular industrial applications (see Figure 1) because of its familiarity as an analytical approach.
In the realm of preparative and industrial chromatography, Simulated Moving Bed (SMB) chromatography has received continuously increasing attention since its introduction in the early 1960s. The SMB technology involves the simulated counter-current contact between the mobile phase and the stationary phase, which is the most efficient in terms of separation performance, solvent (eluent) consumption and productivity per unity mass of stationary phase. This can be accomplished in units constituted of a set of fixed bed chromatographic columns like that illustrated in Figure 2.

The SMB technology was originally developed for very large-scale applications in the petrochemical industry, such as the separation of para-xylene from alkyl aromatic C8 fraction. After its first commercialization, SMB application has been widely expanded to food and pharmaceutical, and nowadays to nearly all Life Sciences industries, because of its high profitability as a manufacturing process.

2. Computer Modelling of Chromatographic Separation Process

Perhaps the most basic requirements to model chromatography are the ability to characterize equilibrium and mass transfer. Also solving mathematical model for chromatographic separation requires good robustness and high numerical resolution due to the complex nature of underlying hyperbolic PDE system. It has been reported that simple finite differencing schemes (e.g. backward/forward differencing schemes) are not good enough to model a chromatography column because of the sharp front in concentration profile along the column. Therefore a simulation tool to model chromatography system should offer advanced PDE discretization methods, such as Orthogonal Collocation on Finite Elements.

Chromatography applications often involve sequences of operating schemes in boundary conditions to achieve good separation. This can be seen in Figure 3, which shows a gradient elution operation with a modulator, a common chromatography application in Life Science. Thus a good modelling tool should offers capabilities to handle dynamic events and quickly defined and edit operating scenarios.

On the other hand, the SMB technology is rather complex and deep understanding is needed to use it effectively. This suggests that a general model aimed at performing a parametric analysis of SMB behaviour would be very useful. However, several attempts in academia have shown that a more synthetic approach is required to guide the choices of parameter values, or such a parametric study becomes computationally intractable. This can be achieved by assuming the system is governed by equilibrium theory where mass transfer resistances and axial dispersion are neglected. In particular, assuming a Langmuirian type adsorption isotherm yields the so-called “Triangle Theory”, which helps determination of optimal and robust separation conditions. Figure 4 shows Aspen Chromatography’s user interface for applying the Triangle Theory to determine SMB operation conditions.

The Triangle Theory serves a reliable starting position for SMB process synthesis. Unfortunately, however, industrial SMB process often shows highly non-ideal behaviour which cannot be well explained by the ideal assumptions inherent in the Triangle Theory. These non-ideal effects in industrial scale SMB system are believed to be mainly due to (1) highly non-linear equilibrium (non-Langmuirian); (2) dead volumes which affect distribution in the system; (3) complex valve control methodology. In addition, recent progress in SMB process design, such as VariCol, PowerFeed, and ModiCon, revealed a gradient SMB operation is more profitable than the classical 4-zone SMB process under isocratic conditions. Without a doubt, more sophisticated operating regimes requires more solid mathematical framework in SMB modelling. And accordingly the Triangle Theory is being challenged to improve its capability for such complicated operations. Commercial SMB modelling tool, e.g. Aspen Chromatography®, is required to meet various demands from various industries. Key requirement items, as a reliable SMB process model, may be categorized as follows:

(1) Functional

- Rigorous chromatography column dynamics

- Ease of SMB zonal configuration

- Controllable valve stepping and port switching/shifting

- Rigorous internal submodels for delivery pipes and hold-ups

- Reactive SMB operation

- Modulation of feed rate

- Modulation of feed composition

- Asynchronous port switching

(2) Numerical

- High resolution PDE method and solid integrator

- Robustness in linear and non-linear solver

- Ease of dynamic event /scenario editing and tasking

In addition, a good modeling software should be able to be utilized for not only process operation but also design parameter estimation, and Table 1 shows the application of commercial chromatography model at different user level.

A screening process in order to determine either good solvent or good packing material is quite tedious job in R&D activity. Probably so called “Trial & Error” method may be a dominant rule of thumb for a screening process, however it requires many routine works to get result and even after result acquisition it is difficult to say one completed an optimal screening. Mathematical model based on the first principle guides logically and physically valid path for such instance and moreover one can be freed from a dilemma and remove a doubt about result. Very often, mathematical model helps one to have important design parameters by means of steady-state or dynamic estimation. For instance, one can estimate equilibrium isotherm parameters or kinetic information by using limited experimental data or real plant data. Since there are no universal model in adsorption equilibria and adsorption kinetics, these two design information (equilibrium and kinetics) are normally in veil at the beginning, and therefore in general they are supposed to be collected from direct measurement, and it is truly a rate limiting step in any design or revamp work.

Nowadays the enhancement of computation performance together with reliable data handling enables commercial software to equip very attractive features, especially for dynamic estimation. Using in-built user interface that designed for dynamic estimation, one can utilize real process model to extract design data from their experimental or plant data. Figure 5 is a good example for dynamic estimation by Aspen chromatography®. Against chromatogram data that measured from pulse injection operation on a pilot scale chromatography column, the dynamic estimation extracts the best matching equilibrium parameters with respect to the chromatogram data. Since this type of estimation work can be carried out against real plant data, the estimated parameters or information can provide more realistic insight on the process. In addition, such estimation feature can be applied to expose mass transfer and heat transfer mechanisms which may be affected by equipment geometry and operating conditions.

3. Industrial SMB Processes and Simulation

Industrial SMB processes can be classified with the following categories:

(1) By Industry

- Refining / Petrochemical

.UOP Sorbex™ processes (Parex™, Molex™, Ebex™, Olex™, etc)

.IFP p-Xylene SMB

.Cresols separation

- Food

.Sugars

.Proteins

.Etc

- Pharmaceutical / Life Science

.Antibiotics

.Insulin

.Chiral compounds .Pure enantiomers

(2) By Valve Stepping Method

- Rotary Valve: Simultaneous port switching only

.Single valve operation

.Less problematic in valve maintenance

.Poor or zero flexibility in operation

.For example, UOP Sorbex™ processes

- Sequential Valve: Flexible port switching available

.Multiple valves operation

.Periodic port shifting is possible (e.g. NOVASEP VariCol™ process)

.More problematic for maintenance than rotary valve

.For example, IFP p-Xylene SMB, Nearly all Life Science application

(3) By Equipment Style (see Figure 6)

- Multiple Columns in Series

.Mostly in pharmaceutical/life science application

- Carousel type

.Some application in food industry

- Single/Twin Stacks

.Refining/Petrochemical industry

Figure 6 Classification of Industrial SMB Process by Equipment Style

In general, industrial SMB separation units are operated with 8 – 36 ports, i.e. adsorption columns. Process performance is highly dependent on the physical property of packing adsorbent (or stationary phase) and desorbent (or so-called eluent or solvent), and typically process licensor keep details about the packing adsorbent a closely guarded secret from their licensee. In addition, industrial SMB process tends to use complex control method about valve stepping and throughput handling, in order to keep the process performance at optimal. Such a complex operation method often introduces a strong perturbation in SMB system therefore the actual operation is a little far away from the ideal SMB principle. By the reason, mathematical modelling and simulation for industrial SMB must require very solid features to meet the operational principle as well as the effects from equipment surroundings including process control. That is the reason why only a general model based on the first principle can properly model industrial SMB processes.

Figure 7 shows simulation interface for a pilot scale SMB process for amino acid separation. The process operates with 12 columns connected in series, each with an approximate volume of 500cm3 and packed with Chirosolve L-Proline with an overall voidage of 0.45. Figure 7 demonstrates the full flowsheeting capability of Aspen Chromatography® by explicitly placing 12 column models with mixers, splitters, pumps and feed and products diverters, all fully interconnected. A simulation scenario editor, so-called Cycle Organizer, is used to define dynamic event schedule and execute the switching cycle.

Figure 8 shows simulation result from a production scale 24 layer SMB unit for p-xylene separation, which separates a mixture of ethylbenzene (EB), m-xylene (MX), o-xylene (OX) and p-xylene (PX) using a para-di-ethylbenzene (PDEB) as desorbent. The SMB unit includes transfer line volumes that represent 1% of the total SMB unit volume. Due to a little extraordinary operation method such as line flushing with reflux-type recycling and additional desorbent feed, this system shows extra 3 zones hen making 7 zones SMB operation. Note that this example process and its process data are collected from open publications [1,2].

4. Remarks

Chromatographic separation is being received greater attentions from various industries due to the attractive characteristics. But at the same time, the related service company and process design company are being challenged by the complexities of the principle as well as the operation. Meanwhile operation companies are also being suffered by lack of resource to understand the process nature, to improve process performance and to maximize profit. In engineering point of view, good software tool acts like a good engineer. Utilizing good software we can minimize risks at every stage in process design and the optimisation.

Reference

[1] Minceva.M. and Rodrigues.A.R., “Modeling and Simulation of a Simulated Moving Bed for the Separation of p-Xylene”, , Ind Eng Chem Res, 41, 3453-3461 (2002)
[2] Minceva.M. and Rodrigues.A.R., “Influence of the Transfer Line Dead Volume on the Performance of an Industrial Scale Simulated Moving Bed for p-Xylene Separation”, Sep Sci & Tech, 38, 7, 1463-1497 (2003)

Process simulation in chemical engineering

The process industries are faced with an increasingly competitive environment, ever-changing market conditions, and government regulations, yet they still must increase productivity and profitability. These business objectives are achieved by reducing the time required to get new products to market, increasing the quality of product produced, operating the plant more safely and efficiently, and/or designing plants for optimum performance along their life cycle. In the process industries, operational efficiencies, production economics, product quality, and, ultimately, bottom line performance can be adversely affected by a multitude of factors. Many of these factors are extremely complex and are subject to varying degrees of unpredictability. To avoid production delays, downtime, or off-spec products, process manufacturers require cost-effective tools that help to identify and correct anticipated problems before they occur. Process engineers routinely address difficult manufacturing and production issues.

Unfortunately, experience alone is not always sufficient to answer the questions that continually arise, and trial and error efforts to provide meaningful insight are usually cost-prohibitive. Process simulation is recognized as a powerful tool that helps managers and engineers link business operations to process operations. Process simulation specifically enables resolution of common issues such as ensuring safety, ensuring environmental compliance, improving operability, improving start-ups and shut-downs, achieving consistent product quality, troubleshooting operational problems, and optimizing batch process operations.

We, chemical engineers, are often faced situations that requiring conceptual or detail modeling about chemical or bio-chemical processes. We want to suggest a best solution or at least a useful workaround to get closed to the best solution, thus a smart modeling method and also having right simulation tools are very important.

I wish I could make this blog as a valuable open resource for all of us, the Chemical Engineers.