Recently, much focus has been given to a new type of chemical production plant, with the aim of a much faster time-to-market (“50% idea”) and better cash-flow revenue. The main enabling technology is to have the plants pre-manufactured and assembled by a modular construction and to use innovative, smart-scale processing and apparatus technology, in order to achieve a compact overall plant footprint. Focal points in such technology are on the one hand, flow processing, with micro process technology as a cutting-edge cornerstone, and on the other hand, the container framework. Yet, other process-intensified technologies are suitable as well such as milli-flow or upgraded batch technologies. Finally, process robustness and short-time applicability make the decision. In this paper, for the first time, a CAPEX and OPEX analysis of the new plant technology is done, at the example of the Evotrainer production platform. This platform is pre-manufactured in serial and provides all the utilities needed around the reactor and e.g., separator to be tailored and inserted. The unit-operational modularization, with respective definition of interfaces, was developed further to a so-called functional modularization, where different cabinets with pre-defined functions and equipment are proposed. Three virtual microreactor applications were used and stand as model-based scenarios for market applications in bulk chemistry, fine chemistry and pharmacy. It is shown, in many facets, that the Evotrainer infrastructure based plants indeed have a faster payback and higher earnings as compared to conventional technology, particularly when serving high-priced markets such as pharmaceutical applications. Further, the combination with novel chemical routes or novel processing (Novel Process Windows) is advantageous. Micro process technology is one of the key enablers and was taken here, since the dataset of such technology was readily available to the authors due to past research efforts and there is some general belief in the combination to the so-called “Future Factories”. Yet, it stands also for any other process intensification technology which can achieve the same performance level and which is able to satisfy the needs of a producing industry.
Europe's chemical industry is under pressure in view of new emerging markets and production capabilities in Asia and the Near East . Lower costs of production, lower taxes, different approval, environmental and safety procedures, and increasingly skilled personnel in Asia allow the chemical industry to grow at a high rate and to increase the global high market share . To improve competitiveness of the chemical industry in Europe and worldwide, new innovative production and plant technologies are needed. Besides, markets are continuously diversifying, as products are increasingly designed for special customer needs . New products have to be developed in even shorter time periods and thus the time to market has to be shortened correspondingly . The current plant concepts used in the chemical industry cannot necessarily satisfy all of these market conditions to the full extent anymore.
To reduce risk over the whole time line from the product idea to the product launch requires a reduction in the capital investment . A critical issue is the numerical ramp up scenario of the product quantity sold. Firstly, intelligent handmade experiments in the lab help to reduce the technical risk of product development and an early-bird provision of test samples helps to make a timely contract with the future customer. Especially in volatile markets, it is highly important to enter at the right time in the “window of opportunity” which is facilitated when engineering is done at an early stage. A window of opportunity denotes a short period of time during which an opportunity must be acted on or missed. This established term in medicine (‘neuronal window’) and social sciences, is increasingly used also in the economy for volatile markets, to describe the right time to approach a customer. It may be too early, e.g., if the manufacturing of the product with the targeted high quality and functionality cannot be proven (documented probes on a pilot/production level) or if adherence to a production schedule is not secured. It may be too late when the competitor is already on the market, the client is in contracts with other parties, and product prices decline [6, 7].
Bulk chemical industry builds high capacity plants as a consequence of economies of scale. They are optimized for the efficient production of a single product . The plant is built from individually designed equipment in a customized way. Because of their size and the degree of optimization required, design and engineering takes a long time and costs are higher . Also, procurement of the equipment and construction of the plant is lengthy and expensive . These all lead to a long time-to-market. Fine chemical production is carried out batch-wise in multi-purpose plants and is flexible regarding production rate and different products produced . Yet, it is nonetheless inefficient in terms of energy and raw material consumption, as the equipment is not optimized for the requirements of the products and recycling and heat recovery is hard to implement .
When the demand for customized, high-value products in low annual capacities increases and a much shorter market entry is required, these existing plant concepts are not necessarily optimal anymore.
Modular compact plants, being partly or fully preconfigured in their modules, parts and interfaces, constitute an innovative approach to address this situation . ACHEMA puts modular plants 1st in the list of top five trends in the process industry this year . With having entirely new concepts and apparatus at hand (process intensification), investigations of the advantages of modular design and its economic potential, have gained new momentum and intensified recently. Bramsiepe and Schembecker pointed out the advantage of modular process design in terms of planning process that enables laboratory to production with small effort . Hady and Wozny presented a modular concept with the aim of showing engineering and equipment reuse, creating saving in terms of know-how and cost . Brodhagen et al. showed that with a shorter time-to-market achieved, modularization is more economical than conventional batch technology . Rottke et al. described an approach to configure plant design using modules, making it easier to determine the cost of different layouts .
Standardization through pre-manufactured modules assembled into highly functional plant environment facilitates a desired lead time reduction to respond to market changes in an efficient manner. It was pointed out by Bramsiepe et al. that with a modular plant concept, elimination of specialized field installation and customized design is possible by standardization, leading to savings in construction and design time and expenditure . Through the reduction of the planning and construction period, the Net Present Value (NPV) of a modular plant was 30% higher compared to multiproduct batch plant . For the calculation of the capital investment for a modular plant, Shah suggested that the factors which are used to estimate based on total equipment cost should be reduced, but the degree of reduction was not specified .
Modularization is already established in equipment and instrument manufacturing industries such as electronics (TV, computer), automotive and the airline industry [18, 19]. However, modularization is, so far, rarely applied to the production of bulk and fine chemicals . Standardized enframing, utility and process control supports the standardization of modules . The compatibility of the modules offers the opportunity to rearrange the same design to meet the needs of different processes. Design and engineering time is reduced significantly through pre-manufactured modules. Standardization reduces the need for customized equipment, piping and structural design . Thus, efforts for detailed equipment design will be reduced, as well as detailed piping and instrumentation design. The engineering job can be focused to find the optimal configuration of modules for the specific process . Since the engineering task is significantly easier, there is faster transfer from lab to production.
Modular plants are efficient in terms of construction and mounting. Construction time can be significantly reduced by the opportunity of preassembling modules in a workshop where tools and machinery to build will be already available . With the use of modular components it is possible to minimize additional field installation. The different modules will only be plugged together on the production site . Accordingly, the costs for scaffolding, construction tools and rentals and personnel located at the construction site can be minimized. A further advantage of the concept is that construction will not be affected by the weather conditions. Expensive site inspections can be omitted, as testing can be partly done on the preassembled plant in the workshop . The sum of these benefits helps to reduce the investment cost and time-to-market.
Additional benefits can be gained in terms of operating costs as well. Due to modularity, only the interaction between the modules needs to be managed, which lowers the labor requirement . Accordingly, the cost of operating labor and its supervision will be reduced. Also, owing to standardization, the maintenance of modules will be easier and no requirement for special parts makes it less costly .
To be able to bring a new product to market faster than other products produces an opportunity to seize high margins in the early phase of a product launch. Because of the capacity of money to earn further money, the financial gain earned earlier is worth more than the same amount earned later .
In Figure 1 the difference between classical project workflow is shown in comparison to the proposed workflow based on modular plants. In a classical project work flow after initial selection of the process to be used, the process flow diagram is prepared . The flowsheet shows the arrangement of the equipment selected, operating conditions and stream flow rates and compositions . The flowsheet is formed by the material and energy balance calculations which are carried out using process simulation. It is used as a basis for the design of instrumentation and control, equipment and piping and structure . Piping and instrument diagrams are made and equipment specification sheets are prepared via detailed design . Using these sheets, the procurement of equipment and materials is done.
The field construction and equipment installation is done and after field inspection and testing, the plant is started up. The workflow based on modular components deviates considerably from classical project workflow. Some major steps are eliminated or extremely simplified. From the process selection, different configurations of the modules are considered and a modular assembly plan is made . With the use of process simulation software, different modular processes are compared and optimal configuration is identified . Then, the step from process flow diagram to final piping and instrument diagram is prepared with minimum effort, due to standard information regarding each module. The modules are constructed in workshops and field installation includes only plugging the modules together . Since the checks of the plant are made before delivery, after installation on site it can be started up. These differences in workflows indicate the saving in engineering and construction time and corresponding cost reduction.
Figure 1 naturally presents a generic, yet ideal picture. Real-case engineering can be more complex and need to take into account additional time-consuming engineering activities to comply with company or governmental specific regulations. It has to be further considered that the modular project is re-using equipment from earlier projects, for which equipment and process and instrumentation diagram (P&ID) design is required, as well as procurement. Thus, an ultimate comparison needs to mirror a first-time built classical project with a modular project where a large part of initial engineering has already been done.
Microstructured reactors increase transport – mixing, mass and heat transfer – in chemical reactions by orders of magnitude and also allow a much easier handling of hazardous reactions and process conditions [22–25]. Moreover, flow processing in microstructured reactors gives the possibility of changing the chemical protocol towards process conditions not accessible or forbidden so far, i.e., processing at high temperature, high pressure, high concentration up to solvent-free (with use of alternative solvents), ex-regime, via new chemical transformations, and by process integration/simplification. All of these routes are coined “Novel Process Windows” [26, 27].
For all these reasons, micro process technology provides a potential for improvements to chemical processes regarding economic sustainability. An economic advantage principally can occur from a reduction in capital expenditure (CAPEX) through lower investment and from a reduction in operating costs (OPEX) by introducing this technology. Merck Company together with the Technical University Clausthal presented a four staged potential analysis for the microreaction technology as theoretical, technical, material and economical potential . Cost saving from using a microreactor was discussed for the example reaction of nitration to 3-methyl-4-amido-5-nitro benzoic acid. Roberge et al. presented a cost analysis of continuous vs. batch production for large scale pharmaceutical production . For a large-scale unit, the CAPEX for a microreactor system can be as high as, or even higher than that of the batch process. Regarding OPEX, the raw material costs account for 30–80%. Higher product yield and quality attained represents the main cost saving potential for microreactors . This also has a direct influence on labor and waste treatment costs. Krtschil et al. and Azurchem Company made an economic evaluation of the 4-cyanophenylboronic acid formation process . Besides the assessment of the existing microchemical process, capacity increase case scenarios were described. Five- and 10-fold increases in capacity were considered. The plant size per given production rate can be decreased with the order-of-magnitude change in productivity, enabling a reduction of the overall costs to 25% of the investigated microchemical process with the 10-fold capacity increase . It was also noted that the equipment cost having a low share should have a minor impact on the decision to go for the novel technology. Hessel et al. performed a cost analysis for the Kolbe-Schmitt synthesis of 2,4-dihydroxy benzoic acid . The base case considered is microreactor production at 4.4 tons/year, and the final product cost is calculated as approximately 91€/kg (based on a reaction time of about 4 s). A microreactor production under the same conditions and with the same productivity, but being operated at a reaction time of 2 h under reflux conditions, would run into a final product cost of approximately 17,350€/kg, which is fully out of economic range. For a similar throughput, the operating cost for a 20 l batch-reactor is approximately 107€/kg. This economy of scale can be seen in relation: a 1 l batch, which matches roughly the space requirements of the microreactor, including tubings (same scale of equipment), accounts to a product cost of approximately 985€/kg. This one-order of magnitude increase in product costs also reflects the economy of scale of chemical industry – in negative manner. For the microstructured reactor with a 10-fold throughput, the operating cost is reduced to approximately 57€/kg which reflects the economy of numbering-up of flow chemistry [31, 32].
It is an aim of this paper to analyze for the first time the combined benefits of process intensification enabled by smart-scaled process-intensified reaction equipment and of modular compact plants. The first can be upgraded and integrated batch technology or, following a prime industrial trend , continuous processing, favorably with small-scale flow equipment, which may be milli-reactors or, when needed, microstructured reactors. Since the authors have much experience with the latter, and therefore have data sets and experience to hand, this paper focuses in a methodological way on (virtual) microreactor applications; yet they stand for the use of any similar high-performing reactor technology, and finally, the most robust will be chosen if the performance is similar. The innovative microstructured reactors have so far been implemented in a more conventional plant environment and tailored to the needs of these reactors and process intensification. Thus, so far, it remains unclear which potential dedicated process control, utility, and safety systems may add. Here, it is aimed at a financial answer; the processing advantages need to be determined experimentally through demonstration projects. They are just underway in EU's FP7 Call for Process Intensification . Such theoretical and experimental first steps are in line with the holistic ambition and vision of the European Union on the “Factory of the Future” and “Flexible Future Production Strategies”, i.e., to combine micro process technology with process integration . This full-chain ambition of European funding policy is expressed as the realization of “new, intensified process and plant concepts for speeding up market penetration, for enhancing the product life-cycle and improving sustainable production” . Five large-scale projects on Future Factories with many of the major industrial players are underway: F3 FACTORY, COPIRIDE, POLYCAT, PILLS, and SYNCLEAN [36–40]. These projects target basically all the different chemical industries, including bulk-chemical, fine-chemical and pharmaceutical manufacturing, as well as applications in polymerization, cosmetics, and renewable resources. The five Future Factory EU projects supplement each other in focusing on different aspects of the whole value added chain – starting from new tailored catalyst development over new reactors towards new types of processing and finally approaching the plant and systemic process evaluation level. This is esteemed to give the first building blocks for the sustainable chemical production platforms of the future.
In the case of micro process technology, the scale-up risks can be substantially reduced because the process development accomplished in a small-scale apparatus is representative of the full-scale production unit . Accordingly, by omitting some scale-up stages process development time can be shortened. The time saving potential of micro process technology for the complete process development was discussed for the first time by Hessel et al. . Since no industrial data are available and laboratory experiences cannot be used for such time predictions, rather an impact analysis was made assuming factorial contributions (increases/reductions) towards the whole process development time. The factorial assignment was based on expert opinion and was largely based on the technical maturity (practical “commercial” potential) of the respective part of micro process technology and not on the theoretical potential. Two major cases, fine-chemical and bulk-chemical applications, were considered and each split into five to six further sub-cases, comprising the separate use of transport, chemical and process-design intensification routes and more. Especially, the use of a compact plant infrastructure was demonstrated and shortenings of the process development time were predicted.
The NPV is a central tool in discounted cash flow analysis and is a standard method for using the time value of money to appraise long-term projects . It is used to find the sum of future cash flows discounted back to its present value. Thus, the NPV is sensitive to the discount rate used. The discount rate is the minimum acceptable return that must be achieved by an investment . It is adjusted to compensate for the degree of risk in an investment with the rate increasing with the risk level. Since the modular plant concept lowers the risk in process development, this allows lower discount rates, which depends on risk. This in turn enables a higher NPV to be achieved.
Modular compact plants can be quickly built and applied at any location with approval for chemical manufacture and needed installations, facilities, and piping to take advantage of economical potentials. Producing directly at a customer's site can be attractive regarding adapting the product to varying requirements quickly; also if the product is hazardous to transport . Depending on the process, if raw material consumption is high, production close to the source can be advantageous in terms of transportation costs and availability of resources. Another argument for distributive manufacturing is if the process has high energy demands and is moved to a site where energy is reliably available at a low price. Production in close proximity to an existing plant might also determine the plant location decision. In such Verbund fashion, compact plants can be used to produce derivatives from the product or upgrade a small volume of products . They can also be used for new product production whose market chances are unknown.
A detailed calculation of capital investment and operating cost for a modular plant, to our best knowledge, has not been made so far in open literature quantifying the benefits of modular design. In particular, this has not been done considering the step-change character of process intensification and smart-scale technologies such as microstructured reactors, with the aim of checking if they add to the advantage of modular compact plants.
We would like to express clearly at this point that naturally for a very new technology such as the Evotrainer plant infrastructure, a number of assumptions had to be made. These are listed clearly throughout the text. Wherever possible, in the context of an industrial development, a rationalization of the assumption is made. Clearly those parameters, such as the cost reduction by pre-manufacture or the risk-related lowering of the rent, have a decisive impact on the outcome of the study. These are to be proven by industrial demonstration activities. For all these reasons, we have assigned this study as an investigation towards model-based scenarios (including virtual microreactor applications) making clear that the generic outcome is the main ambition in the sense of a parametric sensitivity and a proof of principle for a new economic model in chemical manufacturing.
The chemical manufacturing in the compact and pre-manufactured plant infrastructure was analyzed for three application fields – bulk chemistry, fine chemistry, and pharmacy. These markets have very different production volumes, product prices, added value, plant technologies and more, as summarized in Table 1 . It was clear and expected that the bulk chemical manufacturing in the novel plant infrastructure is economically not efficient. Yet, this case serves as a comparison to complete the picture given here.
|Characteristics||Bulk chemical||Fine chemical||Pharmaceutical|
|Added value||Low||High||Very high|
|Safety and Environmental efforts||Relatively low||High||Relatively higher|
The fine chemical considered here is 2,4-dihydroxybenzoic acid, which was chosen due to extensive past experience with experimental microreactor work and cost analysis for the respective synthesis, i.e., all relevant cost data (materials, equipment, performance, etc.) were at hand. In the following, the published background is given; cost information is part of the introduction given above. As bulk-chemical, adipic acid manufacturing was considered, for which first cost analyses were published and more extended results are at hand . Also, non-published experimental research on the adipic acid synthesis in flow is currently being performed. The pharmaceutical product considered is naproxen, a commercial drug. Reasons for this selection were the general relevance of this product on the pharma market, the fact that patent protection is not given anymore (market prices orient more on function/production rather than on development costs) and, last but not least, that a derivative of this product (naproxcinod) has been made at large scale in flow with microreactors . More details concerning adipic acid and naproxen are given below.
2,4-Dihydroxybenzoic acid is used as an intermediate in the manufacture of dyes, pharmaceuticals and of additives in photography, and cosmetics . It is produced via conversion of resorcinol with aqueous potassium carbonate solution at 100°C and applying a carbon dioxide pressure of 4.5 bar. A by-product of 2,6-dihydroxybenzoic acid (γ-resorcylic acid) is formed and can be separated by recrystallization .
The reaction of resorcinol to 2,4-dihydroxybenzoic acid in aqueous potassium bicarbonate solution at high temperatures and high pressure using a microreactor rig was studied previously . The achieved yield was up to 45%, which compares closely to the batch operation carried out for at least 2 h (only reaction time considered here); much higher yields are difficult to reach due to the reversible nature of the reaction. Microreactor superheated processing at 200°C and 40 bar in comparison to the batch operation carried out at 100°C and 1 bar, enabled a reduction of reaction time by a factor of 450 at comparable yields . Cost analysis of the microreactor and batch reactor operation of the realized process was done previously at a production rate of 0.55 kg/h with a five-tube reactor [31, 32]. This corresponds to a production rate of 4.4 tons/year assuming an 8000 h/year operation. Also, the production rate with a 10-fold higher throughput (44 tons/year) equivalent to microstructured reactors operating in parallel was considered. It was found in other studies that new approaches such as microwave heating (MW) and using ionic liquids (IL) can increase the yields compared to the conventionally heated process from about 40% up to 60% and allow operation at a lower reaction temperature . This improvement in yield can have a profound effect in terms of cost, since synthesis of high-value product is made from expensive raw materials. However, the investment for microwave heating and the high cost of ionic liquid material (due to missing recycling at this point of time) presents economic burden for these processes.
In this study, a capacity of 200 tons/year is selected according to the production capacity of the compact and pre-manufactured plant infrastructure. The process data of raw material and utility requirements are based on the previous experimental data of the microreactor and batch reactor operation at a yield of 45% for both. Besides these two cases, a virtual case of 60% yield with the same microreactor operation was considered to take into account the potential of achieving high yields with the use of microreactors, which has been demonstrated for so many reactions  (yet the Kolbe-Schmitt reaction here is rather an exception, if not considering the IL- and MW-processing).
Evonik Industries have developed a modular, mobile, compact platform that supports an individual chemical process with a highly functionalized infrastructure – the Evotrainer (see Figure 2) [49, 50]. The Evotrainer infrastructure concept links research with process development and integrates production as well as plant engineering. The concept orients particularly on the manufacture of specialty products with tonnage, which are at present typically made as campaign products in conventional multi-product plants. It can be upgraded to a production plant of a capacity of some 100 tons per year .
Every Evotrainer is tailored to the reaction that will take place with the processing equipment being adapted to the specific chemical process. It can house a complete chemical plant or just a single module, such as a reactor or a processing step . The platform shall have high flexibility concerning diverse chemical syntheses and correspondingly diverse products. This concept is made with a target on the apparatus for process intensification – in particular milli and micro process technological apparatus.
The Evotrainer infrastructure is divided into several cabinets for logistics, reaction/purification and instrumentation and control . Its infrastructure supplies the raw materials, product and by-product logistics, the utility requirements of, e.g., electricity, cooling water for the process, compressed air, inert gas required for the process. A process control room, emergency exits and a containment basin (disaster pan) are provided; the latter in compliance with water management regulations. The design of the compact and pre-manufactured plant infrastructure meets further fire prevention standards . These features allow the realization of highly efficient solutions for warranty on-the-job and environmental safety standards and maintenance .
The cabinet-subdivision, the omittance of the reactor/separator part in the pre-configuration, and the focus on the utility/process control (“plant electrification”)/safety environment render the Evotrainer infrastructure to represent functional modularization rather than the unit operation based modularization. Following the latter idea, Schembecker proposed a hierarchical module structure, which allows for each single element of a process flowsheet the design of the respective P&ID module . Based on decision trees and simple design rules, a knowledge-based P&ID is assembled. In this way, a difference is given between the functional Evotrainer infrastructure concept and many modular plant approaches of the “50% idea” and of the F3 FACTORY container, so that complementary and in future potentially synergistic approaches were developed in the EU's Future Factory Large-Scale projects .
Thus, Evonik's Evotrainer platform triggers a far-fetching modular plant approach, with a holistic view comprising far beyond the reaction parts. It takes into account the whole process development to make easier the conversion from lab to production by including raw material and product logistics, separation parts, utilities, process control and environmental and safety measures.
The capital needed to supply the required manufacturing and plant facilities is called the fixed capital investment (FCI), while that necessary to start the plant up and operate to the point when income is earned is termed the working capital (WC) with the sum making the total capital investment (TCI) . WC is recovered at the end of the plant life. FCI is subdivided into manufacturing FCI, also known as direct cost, and non-manufacturing FCI, also known as indirect cost. Direct costs include purchased equipment, purchased equipment installation, instrumentation and controls, piping, electrical systems, buildings and service facilities . Indirect costs include engineering and supervision costs covering the design of the plant and purchasing, procurement and construction supervision as well as contingency allowance to cover for unforeseen circumstances .
Capital cost estimation is done based on an estimate of the total purchase cost of the major equipment items required for the process and the other costs being estimated as factors of the equipment cost. This method is called the factorial estimate method . After the preparation of the material and energy balances for the process and preparation of the flowsheets, sizing of major equipment items is done. Then an estimation of the purchased cost of equipment is made. In literature log-log plots or correlations for the main types of process equipment based on cost data obtained from vendors are provided [43, 55] that are used here for estimation.
For the detailed factorial estimate method used here, the factors allow the total capital investment to be calculated based on information of the purchased equipment cost. These factors are given in literature and are determined for typical chemical plants of three general process types – solid, solid-liquid and liquid processing. Table 2 gives the ratio factors that are used here for estimating FCI based on delivered equipment cost. These factors are based on work by Peters et al., where yard improvements, legal expenses and contractor's fee are neglected in this context . The delivered equipment cost is calculated with a delivery allowance of 10% of purchased equipment cost .
|Fraction of E|
|Solid processing plant||Solid-fluid processing plant||Fluid processing plant|
|Delivered equipment cost (E)||1.00||1.00||1.00|
|Purchased equipment installation||0.45||0.39||0.47|
|Instrumentation and controls||0.18||0.26||0.36|
|Total direct plant cost||2.54||2.90||3.50|
|Engineering and supervision||0.33||0.32||0.33|
|Total indirect plant cost||0.68||0.69||0.77|
|Fixed capital investment||3.22||3.59||4.27|
The compact and pre-manufactured plant infrastructure of the Evotrainer, as can be seen in Figure 2, includes instrumentation and controls, electrical systems, building and service facilities in its structure. The associated costs of these in calculating the direct costs with the detailed factorial estimate method are already incurred in the Evotrainer infrastructure. Therefore, the factors used to calculate these in this scenario are eliminated and the corresponding total cost is replaced by the efforts about the Evotrainer infrastructure. Due to the compact structure of the plant and the standardization of units as discussed previously in Section 13, the associated costs for the purchased equipment installation and piping are adjusted to lower than for a conventional plant, as an estimate by 35%. Engineering and supervision costs included in the indirect costs are also expected to be significantly lower than for a conventional plant, due to the elimination of customized equipment, piping and structural design as discussed previously in Section 1.3. Also, the contingency allowance can be reduced significantly due to the lower risk of design errors. The factors in their estimation are decreased accordingly as an estimate by 50%. The corresponding fixed capital investment calculation for the Evotrainer based scenario can be done according to Table 3. This table is based on factors used for a solid-fluid processing plant by Peters et al. given above . Since the Evotrainer is a pre-manufactured plant infrastructure, part of the costs for instrumentation and controls, electric systems, buildings, and service facilities are constant and here a fixed value was assumed which shall not be disclosed here due to confidentiality.
|Fraction of E|
|Solid-fluid processing plant|
|Delivered equipment cost (E)||1.00|
|Purchased equipment installation||0.25|
|Instrumentation and controls|
|Total direct plant cost|
|Engineering and supervision||0.16|
|Total indirect plant cost|
|Fixed capital investment|
The working capital is then estimated as 15% of the TCI . With the knowledge of the fixed capital investment as calculated above the TCI is found.
The fixed cost, mentioned in Table 3 and considered for further calculations, stands for the current Evotrainer infrastructure (third generation) with given demands and flexibility on scale and possibly on application and fits to the production targets considered in this paper (200 t/a). Yet, future generations of such a modular plant with a much different scale and project task, may have other fixed costs. That would naturally change the outcome of the calculations; yet also the cost data for the conventional plant would then be different.
Operating costs include direct costs and general expenses. Direct costs, also called as manufacturing costs, refer to the costs of producing the product at the production site. In addition to these costs are general expenses for contributing to corporate functions of research and development and selling of the product . The direct costs are divided into variable and fixed operating costs. Variable costs include raw material, utilities and catalysts and solvents . Fixed costs include operating labor, supervision, maintenance, plant overheads, laboratory charges, depreciation, taxes and insurance . General expenses include administrative, distribution and marketing and research and development costs .
The variable cost items are determined based on mass and energy balances and operating labor is determined based on the production rate and the type of processing plant. The other items are estimated based on the known operating cost items and fixed capital investment. This factorial method of estimation of operating cost can be seen in Table 4. These factors used for estimation are based on average values given by Peters et al. and Sinnott et al. [43, 55].
|Operating cost items||Factor||Basis|
|Raw materials||–||Required input|
|Catalysts and solvents||–||Required input|
|Operating labor||–||Required input|
|Operating supervision||0.15||Of operating labor|
|Maintenance and repairs||0.05||Of FCI|
|Plant overheads||0.50||Of operating labor|
|Laboratory charges||0.15||Of operating labor|
|Local taxes||0.02||Of FCI|
|Depreciation/Capital charges||Calculated separately|
|Direct production cost||Variable+fixed costs|
|General expenses||0.20||Direct production cost|
|Total product cost|
The Evotrainer infrastructure enables the reduction of operating costs due to its modularity and compact structure in terms of cost of operating labor and due to standardization of units in terms of cost of maintenance, as discussed previously in Section 1.3. The factors in their estimation are decreased accordingly as an estimate by 20%, which is a rough-cut assumption taken from the very first experience. Since some other cost items, including operating supervision, plant overheads and laboratory charges, are related to operating labor as explained above, their corresponding costs are reduced accordingly as well.
Depreciation is calculated separately because it is not the same each year. A depreciation method termed modified accelerated cost recovery system (MACRS) with a 5-year recovery period and half-yearly convention is selected, which is typically preferred for chemical plants . Table 5 shows the annual depreciation rates for this method .
A cumulative cash flow diagram allows visualization of the forecasted cumulative new cash flow over the life of a project . It gives an idea of the resources required and timing of the earnings. The cash flow is found by adding depreciation to net profit after taxes and subtracting the TCI:
Net profit=(sales-total operating costs (without depreciation) (1-ϕ) (1)
Cash flow=net profit+depreciation-total capital investment (2)
where ϕ is income tax rate 
For doing cash flow analysis, the schedule of the project is decided. Generally, for a chemical plant, the construction takes place heavily in the 1st year and in the 2nd year the remaining construction is completed . Accordingly, it is taken here that 30% of the FCI is spent in the 1st year and 70% of the FCI is spent in the 2nd year. Then, in the 3rd year, working capital is allocated and the plant starts production. Production at full design capacity does not usually occur in the 1st year, so that production at 50% capacity is taken for this year . This gives 50% of revenue in this year. In terms of the operating cost, 50% of the variable cost but 100% of fixed costs occur in this year. From the 4th year, production at full capacity takes place until the end of project, with 100% of annual revenue and 100% of operating costs. For this evaluation 8 years of operation is considered with the end of the project at the 10th year, due to 2 years of construction. At the end of the project working capital is recovered by the sale of materials and supplies.
Due to the reduction of the planning and construction period, it was assumed that the construction of the Evotrainer plant can be achieved in 1 year. So, 100% of FCI is spent in 1st year and in the 2nd year, working capital is allocated and the plant starts production. The end of the project is at the 9th year, with 8 years of operation selected here.
The cash flows show the value in the year in which they occur, so they stand for the future worth of the projected industrial manufacture. Since cash flows occur in different years throughout the project, it is necessary to convert them to equivalent values. This is done by discounting future cash flows to a particular point in time . In this way, the time value of money is taken into consideration. The time value of money is related to the capacity of money to earn money. The money earned in any year can be reinvested as soon as it is available and can start to earn a return. NPV calculation is made here to assess the profitability of a projected industrial manufacture. The net cash flow in each year of the project is brought to its present value at the start of the projected industrial manufacture by discounting it at a chosen interest rate. The NPV is then found as the sum of the present values of the future cash flows :
CFn= Cash flow in year n
t = Project life in years
i= interest rate
In practice there may be factors which decrease the theoretical potential in time saving for the container, as given below in Figure 5 and the following Figures. For instance, special alloys for the reactors, piping etc., have an extended delivery time. In addition, time-frames go hand-in-hand with the internal decision making steps (financial and business stage-gates). This is not taken into the equation in the article, but this time-consuming phase is often combined in practice with the engineering phases, and thus in some cases can lead to off-setting the advantage of a faster design phase for the Evotrainer plant infrastructure.
The value of NPV is strongly dependent on the interest rate chosen. It will have a lower value if a higher interest rate is selected. The appropriate interest rate to use is determined from the minimum acceptable rate of return. It is the rate of earning that must be achieved in order for it to be acceptable to the investor, given its risk and opportunity cost of forgoing other projects . The interest rate is determined based on the rate from safe investment such as on government bonds (8%) and adjusted to account for uncertainties associated with a new project. With the increase in risk for the project, the risk premium added on top of the risk-free rate increases.
Since the fine-chemical application comprises the envisaged target market of the Evotrainer infrastructure and also since for this application all relevant data were at hand, the cost analysis investigations started with and were centered around this chemical process. From the earnings made and common data on the compact and pre-manufactured plant Evotrainer infrastructure gathered, the same procedure was applied to the bulk-chemical (adipic acid) and pharmacy (naproxen) applications.
The process equipment for the 2,4-dihydroxybenzoic acid manufacture used included pumps for feeding the reactor at the required pressure, a mixer for mixing the reactants, heat exchangers for heating the reactor feed and cooling the reactor effluent and a reactor unit supplied with heating . The choice of apparatus refers to flow equipment in the case of microreactor operation and to batch equipment in the case of batch operation. For the microreactor operation, the reaction conditions are 200°C and 40 bar, whereas for the batch operation, 100°C and 1 bar were used. Besides the reaction part downstream processes are considered as well. After cooling to about 60°C, water is added to the suspension until complete dissolution of the solid is achieved. Then, the resulting mixture is acidified with hydrochloric acid at room temperature. Then, by cooling to about 15°C, crystals are formed which are then filtered and dried. The product is attained with about 99% purity. For the downstream processes, the same batch equipment was used for both operation types (batch/flow) consisting of a dissolving tank, crystallizer, filter and dryer. In addition to the normal flow process with the standard yield, a virtual flow process with a higher (60%) yield, termed “micro 60%”, was investigated as well. This refers to the proven capability of microreactors to increase selectivity, which actually was also found for the Kolbe-Schmitt synthesis, yet with use of microwaves (which was not considered as equipment here) .
Thus, equipment cost estimates are made for three processes (batch, micro, micro 60%). The equipment for the reaction part is based on the costs of lab set-ups determined previously for 4.4 tons/year production . For the batch operation, scaling up of the batch reactor and apparatus is done and for the flow operation, the microreactors are numbered up. The downstream equipment is simulated with Aspen and their respective costs are determined using the literature . The microreactor operation has a higher cost than the batch operation, due to the higher cost of flow equipment in comparison to batch equipment. However, the difference is not so high (about 25%), mainly because the downstream equipment used is the same. The equipment cost for the microreactor operation with 60% yield is estimated to be 10% lower than the microreactor operation with 45% yield, since a lower amount of raw material goes through to achieve the same amount of product, making it possible to use smaller equipment.
Applying the methodology described in Section 2.3, the detailed factorial estimate method based on the total purchased equipment cost, the FCI for the three processes (batch, micro, micro 60%) is determined for the conventional plant and the Evotrainer plant. With the three process types taking place in two plant types, a corresponding six cases are considered in this evaluation.
The cost of the Evotrainer infrastructure, comprising the costs of instrumentation and controls, electrical systems, building and service facilities, were estimated. The sum of these costs calculated separately with factorial estimates for the conventional plant is slightly higher than that of the cost of the Evotrainer infrastructure. The other direct costs of installation and piping are considerably lower for the Evotrainer plant regarding the factors used, as explained in Section 2.3 and its 20% cost-decrease assumption (in line with the first experience in practice). Also, the indirect costs of engineering and supervision and contingency allowance are lower due to lower factors used. This makes the capital investment for the Evotrainer plant around 15% lower than that for the conventional plant. Figure 3 shows the FCI estimated for the six cases showing the direct and indirect plant costs separately. It should be noted here that batch operation in the conventional plant has a very close capital investment with the microreactor operation in the Evotrainer plant. This shows the opportunity of using Evotrainer infrastructure for applying micro process technology to be competitive, with conventional operation in terms of capital investment which cannot be achieved normally due to the higher cost of more advanced flow reactors.
The operating cost estimation is started with estimation of raw material, utility and operating labor costs. The raw material requirement is derived from the experimental data for the 45% yield for the micro and batch operations and for the 60% yield it is estimated by stoichiometry. A five– to six-fold excess of potassium bicarbonate to resorcinol is used conventionally (textbook recommendation). However, for the microreactor operation, this could be reduced to three-fold excess, enabling saving in terms of raw material cost. The microreactor operation with 60% yield has a considerably lower raw material cost, due to lower raw material requirement. Further the mass and energy balance is made for the whole process. The raw material costs are based on wholesale price information . The operating labor is estimated based on rule of thumb of solid-fluid plants as 10 employee-hours per ton of product . For the microreactor operation 1.5 times lower labor of 6.6 employee-hours per ton of product is taken, partly accounting for a faster product manufacture by estimation. An average common labor rate of 34_/employee-hour is taken based on the Engineering News Record . This corresponds to one to two operators, which is a reasonable estimate for such a small plant of 200 tons/year production.
The other operating costs are determined by factors of the known values as described in Section 2.4. Figure 4 shows the operating costs estimated for the six cases split into the variable costs, fixed costs and general expenses.
Since the Kolbe-Schmitt synthesis presents the case of a synthesis of high-value product from relatively expensive raw materials, the raw material cost dominates the operating costs. The raw material costs constitute around 66% of the operating costs and the total variable costs sum up to around 80%. Accordingly, the share of other operating cost items is low. The use of an Evotrainer infrastructure affects the operating labor and maintenance. However, since these cost categories have a low share in the overall operating cost, the effect of the Evotrainer infrastructure is seen as very small for this process example. For process examples with cheaper raw material (yet high product cost) the effect of the Evotrainer plant will be larger.
It is seen that compared to batch, lower operating cost values can be achieved with the microreactor. Also, the increase in yield in the microreactor operation with 60% yield case enables a profound reduction of the operating costs, due to the raw material cost reduction, which has a big effect on the overall operating cost.
In Table 6, a sample cash flow analysis is given for the batch process in a conventional plant. The schedule of the project is as described in Section 2.5. For the conventional plant, 30% of the FCI is paid in the 1st year and 70% is paid in the 2nd year. In the 3rd year, the working capital is allocated and the plant starts production at 50% capacity. Accordingly, plant generates 50% of design basis and 50% of variable operating cost, but 100% of the fixed operating cost is incurred this year. After the 3rd year, 100% of revenue is earned and 100% of operating cost is spent. Eight years of operation is selected and for the conventional plant, the end of the project is assigned at the 10th year. At the end of the project, the working capital is released and taken as a positive increment to the cash flow. The annual depreciation charge is calculated with rates of MACRS depreciation method given in Table 5 for the recovery period. The revenue, that is the income earned from the sales of the product, is found by sales price 58€/kg multiplied by the amount of 200,000 kg of product produced . Gross profit is calculated as the difference between the revenue and the operating cost, including depreciation. The net profit is calculated as gross profit after taxes, as shown in Eq. (1). Then, the annual cash flow is found. The cumulative cash is calculated to see the cash position over the life cycle of the project.
|End of year||1||2||3||4||5||6||7||8||9||10|
|Fraction of capacity||–||–||0.5||1||1||1||1||1||1||1|
|Annual revenue, 103€||–||–||5800||11600||11600||11600||11600||11600||11600||11600|
|Annual operating cost w/o depr., 103€||–||–||3892||6482||6482||6482||6482||6482||6482||6482|
|Annual depreciation, 103€||–||–||251||402||241||145||145||72||–||–|
|Annual gross profit, 103€||–||–||1657||4716||4877||4973||4973||5046||5118||5118|
|Annual net profit, 103€||–||–||1077||3065||3170||3233||3233||3280||3327||3327|
|Annual cash flow, 103€||-377||-880||1106||3467||3411||3377||3377||3352||3327||3548|
|Cumulative cash flow, 103€||-377||-1257||–150||3317||6728||10106||13483||16835||20162||23710|
|Present value factor (15%)||0.87||0.76||0.66||0.57||0.50||0.43||0.38||0.33||0.28||0.25|
|Present value of annual cash flows, 103€||-328||-668||730||1976||1706||1452||1283||1106||931||887|
|Present value cumulative cash flow, 103€||-328||-996||–266||1710||3416||4868||6151||7258||8189||9076|
The present value of the cash flow in each year (n) is then determined by multiplying by (1+i)-n as given in Eq. (2). The NPV up to year n is the cumulative sum of all the present values of cash flow up to that year. The important consideration here is the selection of the discount rate as explained previously, which is the minimum acceptable rate of return suitable for each case. For a low level of risk in investment, a lower rate can be selected. Since with the Evotrainer plants there is a lower risk in bringing the product from idea to production, a lower discount rate can be used. That is evident from Figure 1, with its fewer respective steps in development and the combined development from laboratory to production in this pre-manufactured facility and the early provision of master samples to the customer to facilitate development decisions, mentioned in the corresponding text. As micro process technology is fairly new technology, it can be considered to have a higher risk than the established process technology of batch production. Accordingly, a higher rate is selected for micro processes. The values selected for the different cases based on the level of risk estimation are given in Table 7. The known conventional batch rate of return was taken and by estimation, reduced by 3%; the risk increase by use of micro process technology was considered by 5% higher risk and reduced again by 3% when being operated in a container.
|Batch, conventional||Batch, Evotrainer||Micro, conventional||Micro, Evotrainer|
|Minimum acceptable rate of return||15%||12%||20%||17%|
For the batch process in a conventional plant with the interest rate of 15% present, value factors are calculated from (1+i)-n for each year (n). The present value of cash flow in each year is then calculated by multiplying annual cash flow with the factor for that year. The cumulative value at the end of the project gives the NPV.
By carrying out this calculation for the six cases, the resulting cumulative cash flow diagram is given in Figure 5.
It is seen that in comparison to the conventional plant, the Evotrainer plant enables a higher cumulative cash flow for each process case. Also, the capital investment is repaid quicker with the reduction of the construction period. The microreactor operation with 60% yield has the lowest operating cost and highest cash flows are attained accordingly. Due to synthesis of the high value product, the reduction in operating costs has a significant effect. This makes the investment cost difference a minor influence. Accordingly, the batch operation has the lowest cash flow, because of its higher operating cost and cannot profit from its lowest capital investment.
Cumulative cash flow diagrams do not take into account the time value of money. Accordingly, an NPV calculation is made to take this into consideration. As explained before, with a higher discount rate, lower NPV values can be achieved for the same investment consideration. The resulting calculation of NPV for the six cases is given in Figure 6.
The reduction of risk achieved with the compact and pre-manufactured Evotrainer plant enables higher NPV values to be achieved for each process considered. In comparison to the conventional plant for the reaction studied, with the use of the Evotrainer infrastructure, an increase in NPV of around 40% is obtained for each process type. Regarding the process types, although the microreactor processes have a higher interest rate, a still higher NPV than with the batch process can be achieved due to lower operating cost.
To eliminate the effect of interest rates selected, the NPV calculation is also done by using a 15% rate for all cases. The discount rate used for batch, evotrainer case is increased, batch, conventional case is kept the same and the other cases are decreased compared to Figure 6. The resulting NPV for the six cases is given in Figure 7. Due to the changed discount rates the NPV of batch, evotrainer case decreases compared to Figure 6.
In Figure 7, the same discount rate is considered and accordingly the same risk level is taken. That is why the high difference in NPV achieved with the Evotrainer infrastructure owing to lower risk in the previous Figure 6, is not seen in Figure 7. However, with the use of the same risk level, the Evotrainer plant enables higher NPV values. In comparison to the conventional plant for the reaction studied with the Evotrainer infrastructure, an increase in NPV of around 18% is obtained with the use of same risk level. This difference is due to a lower operating cost achieved with the Evotrainer infrastructure and the reduction in the construction period that enables the financial gain to be achieved, since the money earned earlier is worth more than that earned later. Considering the process type, the microreactor process is seen to have a higher NPV, due to the profound effect of the reduction in the operating cost achieved.
The authors have started to investigate the process-design intensification through the microreactors and flow processing on one reaction example: adipic acid synthesis . Current commercial production processes for adipic acid are carried out in two steps: the first step involves the production of so-called KA oil (a mixture of cyclohexanone, the ketone or K component, and cyclohexanol, the alcohol or A component). The second stage involves the oxidation of the KA oil to adipic acid, with an excess of strong nitric acid. Recently, a one-step oxidation of cyclohexene to adipic acid by 30% hydrogen peroxide (H2O2) has been reported . For this route, the use of microreactor technology is selected to overcome limits in interfacial transfer, to safely handle hydrogen peroxide, to explore new, harsher process chemistries, and to test for better selectivity at much reduced reaction times (transport and chemical intensification fields). It was seen that the direct route enables a significant reduction of the capital cost . The reader is referred to Hessel et al. for the comparison of the two-step commercial batch process and the one-step flow process .
Here, the production of adipic acid at a capacity of 200 tons/year is studied according to the production capacity of the Evotrainer infrastructure. In Table 8 investment, operating cost and revenue that are used in making cash flow analysis for this process are presented. The process data are based on the previous study of the flow and batch operations through process simulation . The investment cost calculation is done with the same factorial estimate method as used above, based on the total purchase equipment cost estimated for the two-step batch process and the one-step flow process. Due to a more compact plant design achieved with the one-step flow process, a significant reduction in capital cost occurs. A higher impact of using the Evotrainer infrastructure is seen for the two-step process, which has a higher capital cost.
|Summary of cash flow items in 103€||2-Step batch, conventional||2-Step batch, Evotrainer||1-Step micro, conventional||1-Step micro, Evotrainer|
|Fixed capital investment (FCI)||2154||1577||1407||1204|
|Working capital (WC)||380||278||248||212|
|Variable cost of production (VCOP)||246||246||415||415|
|Fixed cost of production (FCOP)||401||298||315||262|
The variable operating cost calculation is then done based on the mass and energy balance that enables determination of the raw material and utility costs. The operating labor is estimated as 10 employee-hours per ton of product for batch and 6.6 employee-hours per ton of product for the microreactor operation. The other operating costs are determined by factors of the known values, carrying out the same methodology as before.
The revenue is calculated using the wholesale price of 3000 €/ton . The cash flow and thereafter the NPV calculations are done as explained for the previous example. Again, the same interest rates given in Table 7 for the batch and micro operations are used for analysis.
The total operating cost is greater than the revenue in most cases for this process example, showing that it is not worth investing at this production rate. Accordingly, minus NPV values are attained showing that the margin is not enough to recover the investment (see Figure 8). Actually, a production capacity of 130,000–450,000 tons/year defines the commercial range seen for adipic acid synthesis . At a higher production rate, the effect of the fixed operating costs decreases, enabling higher margins to be achieved.
However, the adipic acid example is not a representative example for the whole entity of bulk chemicals, since there are numerous higher value bulk chemicals (i.e., sebacic acid) that enable at least twice the revenue to be achieved compared to adipic acid. In order to take this into account, a virtual bulk chemical process is included in the NPV calculation, by doubling the revenue and keeping other cost items the same. The resulting NPV for the six cases is given in Figure 8. Here it is seen that the virtual bulk-chemical case enables faster repayment of the investment cost with the higher revenue achieved. Also, with the Evotrainer infrastructure that enables a lower investment and operating cost, a positive NPV can be achieved in the 8th year of operation time considered.
Naproxen is a nonsteroidal anti-inflammatory drug. It is used to relieve pain from various conditions such as headaches, muscle aches, tendonitis, dental pain, and menstrual cramps. It also reduces pain, swelling, and joint stiffness caused by arthritis, bursitis, and gout attacks .
It was introduced to the market in 1976 and the patent expired in December of 1993. The Syntex manufacturing process used today has the starting material 2-bromo-6-methoxynaphtelene (BMN), which is converted to a Grignard reagent which is then coupled with a salt of bromopropionic acid. This way, the corresponding d,l-acid is produced with a yield >90%. This is then efficiently resolved using N-alkylglucamine (>95%) .
The investment cost is determined based on the equipment required for the Grignard reaction step and the resolution step, with a racemization-recycling loop. The equipment includes a reactor and related parts, a mixer for mixing the resolving agent, a heater, a filter for separation of the insoluble salt and a separator for recovery and recycle of the resolving agent. Regarding the operating cost, again the major share refers to the raw material cost due to the production of a high value product use of relatively expensive raw materials. There are various alternatives to produce naproxen, and production with the starting material BMN enables the lowest operating cost, with BMN being the least expensive . Due to the labor intensive resolution step, the operating labor is estimated as 20 employee-hours per ton of product. The other operating costs are determined by factors of the known values carrying out the same methodology as before. The revenue is based on a wholesale price of naproxen at 25 kg of approximately $10,000 . In Table 9, investment, operating cost and revenue which are used in making cash flow analysis for this process are presented. The resulting NPV calculation is given in the following section.
|Summary of cash items in 103€||Pharma, conventional||Pharma, Evotrainer|
|Fixed capital investment (FCI)||1235||1050|
|Working capital (WC)||218||185|
|Variable cost of production (VCOP)||21920||21920|
|Fixed cost of production (FCOP)||4928||4825|
The selection of naproxen as an example is motivated by a well-published industrial application example of micro process technology. In 2009, the development was started to get a new drug, naproxcinod to treat patients with osteoarthritis, to market; it reached Phase III studies . Naproxcinod is a naproxen derivative which contains a nitrate group as a substituent. Compounds containing a nitrate group are difficult to make, as nitration reactions must be handled carefully due to producing products that can violently decompose. Highly diluted, biphasic conditions and specialized safety equipment are necessary to realize this type of processing in a classical batch manufacturing process. Beyond this safety issue, the selectivity in nitration reactions and work-up are to be considered to permit extraction and neutralization of the nitrated product. A microreactor system enabled this eco-efficient production at a few hundred tons capacity of naproxcinod per year and combined three main steps: the nitration reaction, neutralization and work-up . Thus, it would have been of interest to evaluate the use of microreactors for the synthesis of naproxcinod as a further step from the naproxen process described above. However, due to lack of data about this process, this cannot yet be done.
In Figure 9, the NPV curves are given for the bulk-chemical, fine-chemical and pharma applications. It is evident that the operation of a much more costly product, such as naproxen, has a very positive effect on the cash-flow. Using a compact and pre-manufactured plant infrastructure, already after 1 year, a substantial payback and earning is evident, while a similar trend is observed with conventional plant technology only after 2 years. The overall earnings over the years with pharma products are much higher as compared to the two other application cases. Thus, a GMP-type upgrading of the Evotrainer infrastructure technology provides a promising business case.
A detailed calculation of capital investment and operating cost for a modular plant is made for the first time, quantifying the benefits of modular design. For the evaluation, Evonik's new compact and pre-manufactured production platform, termed the Evotrainer, was considered. Standardization through pre-manufactured modules assembled into a highly functional plant environment, facilitates savings in the design and construction time and expenditure. Additional benefits can be gained in terms of the operating costs as well, regarding operating labor and maintenance. A detailed factorial estimate method, which is used in making an economic analysis for conventional plants, is employed to make an analysis for the plant based on the Evotrainer infrastructure. Regarding the advantages gained with the Evotrainer plant, these factors are either replaced with the cost of the Evotrainer infrastructure or reduced, since the latter already includes instrumentation and controls, electrical systems, and building and service facilities in its structure. The study also considers the step-change character of process intensification and smart-scale technologies, such as microstructured reactors, together with modular compact plants; the latter also stand for any other modern robust high-performance equipment to hand in the chemical industry.
The chemical manufacturing in the compact plant infrastructure (e.g., enframed in a container-like module) was analyzed for three virtual microreactor applications. These model-based scenarios for market applications in bulk chemistry, fine chemistry and pharmacy, take into consideration all possible chemistries and markets regarding production volumes, product prices etc. The fine chemical considered was 2,4-dihydroxybenzoic acid, which was chosen due to extensive past experience with experimental microreactor work. CAPEX and OPEX calculations and a following cash flow analysis were carried out. In comparison to the conventional plant, with the use of the Evotrainer infrastructure based plant, an increase in NPV of around 40% was obtained; using a lower interest rate for the Evotrainer plant, it has a lower risk in bringing the product from idea to production. However, with the use of the same risk level, the Evotrainer plant still enables higher NPV values (e.g., 18% for the fine-chemical case considered at 200 t/a and the same discount rate of 15%). This difference is due to the lower operating cost achieved with the Evotrainer plant and the reduction in the construction period. Considering the process type, microreactor (or generally intensified) processes were seen to have a higher NPV than that of the batch processes, due to the profound effect of the reduction in operating cost achieved. It was seen that the Evotrainer infrastructure and micro process technology can be synergistic in costs. The study carried out for the bulk chemical (adipic acid) did not give favorable results as expected, indicating that bulk chemical manufacturing in the Evotrainer based plant is economically generally not efficient; however, a chance for high-priced bulk chemical is indicated. In the pharma case (naproxen), a high positive effect on the cash-flow was seen due to higher value-added making it attractive to be produced in the Evotrainer based plant.
As stated in the introduction, assumptions were made; the main generic aim of this study was to provide parametric sensitivity and a proof of principle for a new economic model in chemical manufacturing using model-based scenarios (including virtual microreactor applications).
Funding by the Advanced European Research Council Grant “Novel Process Windows – Boosted Micro Process Technology” under grant agreement number 267443 and by the EU Large-Scale Projects COPIRIDE and POLYCAT of the 7th European Framework Program, under grant agreement numbers CP-IP 228853 and CP-IP 24095 of the European Community's Seventh Framework Program, respectively, is kindly acknowledged. Authors would like to thank Johan Tinge from DSM for his advice in adipic acid process.
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