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The main benefits expected from module-based plant design are shortened planning periods and increased planning as well as cost estimation accuracy during early engineering phases. Most of the existing approaches require equipment module databases. However, overall equipment module databases do still not yet exist. Even though these databases will be available, they will most likely not contain operable equipment modules for any process task. Thus, the objective of this work is to increase the accuracy of investment cost estimation without the need of equipment module databases, which is exemplified for plate as well as shell and tube heat exchangers. Instead of selecting one equipment module from an existing module database for a certain process task, all operable equipment modules are generated by determining design parameter combinations, which are located inside the design space and thus fulfill all operating constraints. Tailor-made equipment design is not needed in any step. The detailed investment cost estimates of all operable equipment modules are used to determine the range of possible investment cost. The variance of the investment cost estimates determined is equal or less than half of the error of conventional preliminary investment cost estimation in case of 54% of the industrial process tasks.

Current challenges for (bio-)chemical industry require shorter project lead times. To reduce the lead time, the concept of module-based plant design was developed. Suitable equipment modules are selected from an equipment module database instead of time-consuming tailor-made equipment design. The quality of module-based plant design strongly depends on the quality of the equipment module database. An equipment module database should contain the least number of equipment modules covering as many industrial applications as possible. Hence, the generation of an equipment module database is a maximum coverage problem known from other disciplines, such as facility location. Within this work, the corresponding maximum coverage problem is formulated and solved by a randomized greedy algorithm. The approach for the generation of an equipment module database presented is exemplarily applied for liquid/liquid heat transfer applications provided by Evonik . It is shown, that less equipment modules are required for the same coverage of applications if the equipment module database is generated based on the maximum coverage problem than based on the existing methodology presented by Eilermann et al. (2017). Additionally, less computational effort is required.

In this work an approach to select equipment modules for a flexible modular production plant at low investment costs using a multi-objective evolutionary algorithm is introduced. Thereby, a good determination of the plant`s overall operating window is of utmost importance. A styrene production plant serves as case study to evaluate the equipment module selection approach, to analyze the resulting compromise solutions as well as the flexible modular equipment sets with low investment costs. It is for example possible to achieve an 11-fold enlarged operating window for 50% higher investment costs compared to the conventional design. Thus, this work presents an important step towards the realization of modular production plants.

Module-based plant design opens up the opportunity for the (bio-)chemical industry to reduce lead times, which is crucial for future competitiveness. Equipment modules are designed once such that they can cover a wide range of process tasks and conditions. The time-consuming equipment design step is replaced by selecting the most suitable equipment module from an equipment module database so that engineering work is reused. It is the aim of this work to develop a structured approach for the determination of features to characterize industrial process tasks. On the one hand, these characteristic features determined are required for the generation of an equipment module database based on cluster analysis of industrial process tasks (Eilermann et al., 2017). On the other hand, the characteristic features are a measure for similarity of process tasks and support the selection of the same equipment module for similar tasks. Thereby, reuse of engineering is enabled. The approach for the determination of characteristic features presented is based on those used in data mining, whereas the quality of the characteristic features is traded off against the computational effort required. The approach developed is exemplarily applied to industrial liquid/liquid heat exchanger and condenser tasks kindly provided by Evonik.

Increasing economic challenges lead to the need for faster plant design in process industry. In this context, a promising approach is module-based plant design. Thereby, for the accomplishment of the required design tasks modules are selected from databases and configured instead of time-consuming and tailor-made plant design. Within this work, a general approach to module-based plant design is introduced and illustrated based on an example. To structure the design procedure different types of modules are defined for different design tasks: PFD, P&ID, Equipment and 3D Layout. Additionally, module selection can be performed at different Levels of Aggregation to cope with the high variance of applications. This enables module selection and configuration avoiding time-consuming, tailored modifications. Since modules are unmodifiable and project-independent, the module-based plant design approach presented is based on a consistent module definition. This work provides a framework to integrate some of the existing modularization approaches into a general module-based plant design approach. However, most often new approaches are necessary to accomplish the design tasks within the presented module-based plant design approach. Thus, this work also identifies open research gaps that need to be filled by future research.

Modular plant design is an approach for making chemical production more flexible and more efficient. Different approaches for modular plant design have been developed, for example in the CoPIRIDE or F3 factory project. They have in common, that lead time reductions for modular equipment are expected e.g. by utilizing design repetition or parallelization of preassembly of modules. To support the decision for or against a modular concept, besides cost effects possible lead time changes compared to conventional concepts should be anticipated in early economic evaluations already. In this article, a lead time estimation method will be presented that correlates project costs and project durations and can be applied to modular and non-modular plants enabling comparative studies. An example from a previous paper was used to investigate the impact of modularization on lead time. It includes modular production lines and a non-modular backbone facility that provides energy and utility supply. A range of investment sizes (FCI of 3–95 mio. €) was investigated and compared with a conventional reference plant. Total lead time reduction was in the range from 2.6 to 5.5 month depending on investment size. For a more significant impact on the lead time the modularization approach needs to be modified by also applying modular design to the backbone facility. In this case depending on investment size total lead time reduction would be between 3.9 and 18.7 months representing a very significant reduction of 23%–60% compared to the lead time of the conventionally designed reference plant. This is considered as the maximum expectable lead time reduction that can be achieved through modular plant design. This reduction would represent a major potential for speeding up construction of chemical plants.

Process Equipment Assemblies (PEA) are pre-designed equipment sets which are selected instead of time-consuming tailor-made design. This paper introduces a new method for the selection and configuration of PEAs exemplified on the unit operation distillation. First step of the new methodology is the selection of the most suitable technology applying matching matrices. The matching matrix required for selecting a suitable distillation technology is introduced. Next a process function-based planning approach is executed using so called master block flowcharts (MBF). These technology specific flowcharts contain all possible process functions required for any potential separation task and contain the technology specific main function and technology independent process functions. Considering process boundary conditions and functions already available in the infrastructure, the MBF is reduced to the functions required for the process. Next, concrete PEAs are selected starting with the main function where the separation of the fluids takes place using the PEA operating range as the main selection criterion. A tool required to determine the operating range of a distillation column is demonstrated. Finally, the PEAs for auxiliary functions are selected from a databank.

Module-based plant design opens up the opportunity for the (bio-)chemical industry to reduce lead times, which is crucial for future competitiveness. Equipment modules are designed once such that they can cover a wide range of process applications and conditions. The time-consuming equipment design step is replaced by selecting the most suitable equipment module from an equipment module database so that engineering work is reused. Although of central importance in module-based plant design, an applicable equipment module database has not been developed, yet. Therefore, it is the aim of this work to develop a methodology for the generation of shell and tube heat exchanger modules for an equipment module database. Existing industrial heat transfer applications are grouped by a hierarchical clustering algorithm. For each cluster of applications a representative heat exchanger is selected. A set of possible representatives is generated in a Sobol sequence from which a heat exchanger is selected to be the representative that covers most of the applications inside the cluster considered. The representative heat exchangers are stored in the equipment module database. The resulting 17 heat exchanger modules can cover 59% of the considered industrial applications despite their considerable diversity regarding conservative operating constraints.

A modular production plant consists of predefined apparatuses with a fixed design, called equipment modules. Selecting the equipment module with the appropriate suitable capacity to compensate fluctuations in production rate is one of the key challenges in module-based plant design. The equipment module’s operating window needs to fit and determines the point in time when a capacity expansion is required so that the operating window of the equipment module also affects a capacity expansion strategy. In order to avoid an unnecessary use of multiple apparatuses in parallel, equipment modules should be developed specifically for a large operating window in contrast to conventionally designed equipment. Therefore, an approach is required to design equipment modules for flexibility in production rate. In this work a method to design equipment modules for flexibility based on a global sensitivity analysis and the deduction of design rules of thumb is introduced. This method is applied to the design of a liquid/liquid heat exchanger without phase change. The resulting design for flexibility is compared to the conventional design with regard to the operating window and investment as well as operating costs. It is shown that for 14% higher annual costs a four-fold operating window can be obtained. This presents an important step towards increasing the competitiveness of modular production plants.

Continuously operated multi-product plants enable an efficient and flexible production of new products. As a future plant concept, a modular design allows the possibility of a stepwise capacity expansion when market demand is increasing. Choosing the right plant capacity combined with a suitable expansion strategy is a key challenge in this context. Therefore, additional costs for expansion have to be balanced against an achievable economic performance and a reduction of investment risk. In this work a framework to evaluate the production capacity of a continuously operated modular multi-product production line for a production line wise capacity expansion will be presented. As a result, a decision tree analysis integrating production planning by a capacitated lot sizing method is introduced to evaluate the economic performance of plants with different capacities in an uncertain market. The framework is applied for a case study considering a continuous production of a set of three different products. As a key result it can be said that the investment risk can be reduced by applying smaller scale modular production lines. However, the low scalability of investment costs of a small scale production line negatively affects an economic expansion strategy.

Modular plant design is an approach for making chemical production more flexible and more efficient. Different approaches for modular plant design have been developed, for example in the CoPIRIDE or F³ factory project. They have in common that reductions in design and construction expenses for modular equipment and its assembly are expected e.g. by preassembly of modules in a workshop under controlled conditions resulting in less field work on the construction site for erection. However, the main disadvantage of the modular approach is the loss of economy of scale. Thus, the effective impact of the modular concept concerning the fixed capital investment has to be investigated. In this article, a new approach for estimating fixed capital investment of modular production plants will be presented and applied using a generic example. Based on the results we expect that positive effects through modularization on engineering and construction costs can nearly compensate the loss of economy of scale. In the investigated example investment costs of the modular plant are 12% higher than for the comparable conventionally built plant. Such increase could allow other effects that are attributed to the modular concept to be employed to advantage. That would be an economic improvement and a reduction of investment risk in view of the modular plant’s life cycle.

The chemical and biochemical industry has to face the challenges of globalization, short product cycle times and volatile markets. Therefore, the lead time of development projects has to be shortened. Modules and module-based plant design are widely discussed to enable shorter time-to-market by reuse of engineering effort and standardization. In this paper general requirements on modules in process engineering and modules for particular applications in the chemical and biochemical industry are reviewed. This includes the impact of modules on the planning process and examples of realized modular equipment concepts. Based on this, a general terminology definition of ‘modules’ and of specific module types for the process industry is presented, whereas modules on various ‘aggregation levels’ are accounted. A ‘block representation frame’ stores information and tracks information fluxes along the whole process and plant life cycle and on different ‘realization levels’ from laboratory studies over miniplant validation to production plant design and operation.

A more flexible and efficient production of chemicals is a requirement for further strengthening the competitiveness in the chemical industry. An approach proposed to achieve this is modular plant design. It offers new opportunities for the supply chain and combines production flexibility and efficiency. However, modular facilities are expected to be built at comparably small scales and loss of economy of scale is a major concern. There is a need to know under which conditions a modular plant design is a beneficial option. Addressing this it would be helpful to have a methodology that includes modeling of production scenarios in a holistic way including supply chain and process simulation and thus allowing a meaningful evaluation. For that reason we developed such a methodology, using the F3 factory concept as an example for modular plant design. Demonstrating the methodology's feasibility an exemplary implementation in a software tool was established enabling comparative simulation and evaluation of batch, continuous and the modular F3 factory production. As unique feature supply chain and process simulation is combined in a single software implementation allowing for statistical analysis to automatically evaluate the economic performance of production concepts under different boundary conditions of the process and the supply chain. The incorporation of those boundary conditions is usually not part of process simulation and goes beyond state of the art approaches. In this paper, the methodology implemented will be presented and the application will be demonstrated using two production scenarios as examples. For the examples investigated, it was found that compared to the conventional production concept the modular F3 factory concept is economically robust concerning the choice of design capacity with regard to diverse market conditions.

Direct heat exchanger network synthesis for continuous processes based on pinch methodologies benefits from its intuitiveness and simplicity. The challenge in synthesizing direct heat exchanger networks in batch processes is to handle many small heat streams to form an economic heat exchanger network. In this publication, a new approach for synthesis of direct heat exchanger networks is presented and compared to existing approaches described in literature. Within the new approach a match ranking matrix is utilized to prioritize stream combinations which exhibit the largest potential for cost effective installation instead of matching the streams by their temperature. Thereby, possible loss of heat integration potential is accepted. As a result, the following optimization of the heat exchanger network takes less iteration steps compared to stream matching by temperatures. The approach is applied to an example process to show its applicability.

Reduction of investment risk is a major challenge in chemical process design. To minimize financial risks a paradigm shift is necessary. Therefore, risk analysis will have to gain importance already during process development. Only in this way can plant designs be identified that cover the expected demand uncertainty at optimal costs. Stepwise expansion is one option to reduce risks as investments can be spread over a certain time period. This allows waiting for more precise market information and adapting production output to changing market development. The drawback of this approach is the loss in economy of scale. Potentially higher investment costs have to be balanced against an achievable risk reduction which makes the integration of risk assessment in process design indispensable. Furthermore, equipment allowing for an efficient numbering up in plant expansion is needed. Here one of the most promising options is the application of intensified equipment. This work shows how process intensified equipment can be used to reduce the investment risk of a large scale hydroformylation plant. Two methods for risk quantification are applied. Both show that investment risk is reduced by numbering up unit operations and adapting their size. Influencing parameters are the cost structure and process boundaries.

As market demand forecasts will become more uncertain in the future it is necessary to develop new methods for plant design. New technologies allow combining the flexibility of a batch plant with the efficiency of a continuous production. To gain even more economic benefit intensified equipment is often designed as a module. The usage of equipment modules allows an easily and efficient increase of capacity. In this way a plant expansion close to the market is possible. Consideration of stepwise plant expansion is often limited to the copying of complete production lines. This approach results in high additional investment costs due to the loss of economy of scale. To overcome the limitations set by economy of scale, an equipment wise expansion strategy should be applied. By debottlenecking the capacity limits of the plant it is possible to adapt plant capacity very close to the changing environment and reduce the additional costs. Therefore, design of a modular plant must be combined with suitable economic evaluation methods for uncertain demand forecasts. In this work a framework for such a design based on predefined and standardized modules will be presented. The framework consists of two stages. The first stage is the selection of possible modular setups and suitable expansion strategies. Next these setups are evaluated in a real option analysis to investigate the economic performance in an uncertain market. The approach will be used to evaluate a multiproduct continuous plant. The main finding is that the economy of the modular plant depends under the given boundary conditions on the equipment item with the highest proportion on total investment costs and a high cost degression exponent.

One of the future challenges for chemical engineering is the design of flexible plants allowing an adaptation of production output to market development. Consequently, the target for the design of new processes must be the identification of equipment allowing such an expansion close to market development. To leverage the full benefit of this approach flexibility analysis has to be integrated into process design workflow. In this article the conventional technology for hydroformylation is compared to an intensified process design. This new design consists of a jet loop reactor followed by a membrane section to separate and recycle the homogenous catalyst. In the first part of the article it will be shown that process intensification leads to a net present value improvement of 30% compared to state of the art hydroformylation at a capacity of 100 kt/a. In the second part suitability of the intensified process for a stepwise plant expansion will be demonstrated. In an expansion scenario with two steps equivalent annual annuity is increased by 5% compared to a one step investment.

Time Slice Model (TSM) is an existing model suitable to identify the potential for heat integration in batch processes. However, heat streams occurring during a heating or cooling process in a batch vessel cannot be depicted rigorously due to their time dependent temperature profile. Yet such streams can frequently be found in batch processes. Ignoring the temporal dependence of the temperature can lead to inaccurate heat integration targets. In this publication, necessity for the inclusion of time dependent heat streams is illustrated and drawbacks of existing approaches are demonstrated. A methodology for considering heat streams with temperature profiles in TSM is presented and it is demonstrated that introducing additional time slices allow prediction of integration potential without accuracy loss.

Globalization, product diversity, varying customer demands, uncertain markets and shorter product lifetime are new challenges chemical and biochemical companies are facing more and more. As they combine the flexibility of multiproduct batch plants with the efficiency of continuous world scale plants, small scale continuous plants present an alternative production mode suitable to face these challenges. Building these plants from standardized modules can additionally help to reduce time to market and costs. It is the aim of this work to prove the economical advantages of this concept. The investigations are performed on a multiproduct batch plant for the production of four different recombinant proteins. To prove the concept the production in four continuous modular mono-product plants are benchmarked against the base case. Calculating the investment and operating costs of both concepts and comparing them using discounted cash flow analysis proves, that a change from batch to continuous operation results in a more than 30% higher net present value at the end of the operating period. Designing the continuous plants modularly leads to another 35% higher net present value assuming that the construction period can be reduced from three years to one year by this concept.

A model to describe the fugitive emission of volatile organic compounds from flange joints is presented. By combination of laminar and capillary flow in a new concept of branching capillaries, this conception increases the prediction accuracy compared to the existing model of linear capillaries. Furthermore a correlation is deduced to describe the capillary diameter as a function of gasket stress using the compression curve of the gasket. A model is developed and experimentally validated, which predicts fugitive emissions from liquid charged flange joints as a function of medium properties, pipe pressure, gasket width and gasket stress. Finally the parameters influencing the emission rate of liquid charged flange joints are discussed and recommendations for fugitive emission reduction are presented.