Maintenance Integration in Manufacturing Systems: From the Modeling Tool to Evaluation

In manufacturing systems, wear-out and eventual failure are unavoidable. However, to reduce the rate of their occurrence and to prolong the life of equipment or the capacity for extended productive use of the equipment under the necessary technological functioning and servicing, maintenance can be performed. For large manufacturing systems, maintenance integration involves a particular development concerned with both complexity models and computing time. This paper presents an effective way of modeling complex manufacturing systems through hierarchical and modular analysis by using stochastic Petri nets and Markov chains. In the proposed approach, the integration of maintenance policies in a manufacturing system is facilitated by the development of a generic model. With this generic modeling, the user doesn't need to code the strategies but only to instantiate the generic model with the structure of the manufacturing system. This method allows various maintenance strategies to be coded in the generic model with the aim of studying their influence on system dependability and performance.     

Integrated Modeling Framework for Manufacturing Systems: A Unified Representation of the Physical Process and Information System

The task of process modeling in a manufacturing environment centers around controlling and improving the flow of materials. This flow comprises a complicated web of control and physical systems. Despite a variety of manufacturing system modeling approaches, more rigorous process modeling is required. This paper presents an integrated modeling framework for manufacturing systems (IMF-M). Conceptual modeling of physical materials flow supported by a graphical representation facilitates improvement of operations in manufacturing environments. A declarative and executable representation of control information systems helps to improve information management by managing a variety of information models with improved readability and reusability. A unified representation of the physical process and information system provides a common modeling milieu in which efforts can be coordinated among several groups working in the different domains of scheduling, shop floor and logistics control, and information system. Since the framework helps adapt to the changes of the physical process and information system affecting each other in a consistent manner, the modeling output enhances integration of the manufacturing system.     

Insights into pneumococcal pathogenesis from the crystal structure of the modular teichoic acid phosphorylcholine esterase Pce

Phosphorylcholine, a specific component of the pneumococcal cell wall, is crucial in pathogenesis. It directly binds to the human platelet-activating factor (PAF) receptor and acts as a docking station for the family of surface-located choline-binding proteins (CBP). The first structure of a complete pneumococcal CBP, Pce (or CbpE), has been solved in complex with the reaction product and choline analogs. Pce has a novel modular structure, with a globular N-terminal module containing a binuclear Zn(2+) catalytic center, and an elongated choline-binding module. Residues involved in substrate binding and catalysis are described and modular configuration of the active center accounts for in vivo features of teichoic acid hydrolysis. The hydrolysis of PAF by Pce and its regulatory role in phosphorylcholine decoration of the bacterial surface provide new insights into the critical function of Pce in pneumococcal adherence and invasiveness.     

Modeling and simulation of molecular biology systems using petri nets: modeling goals of various approaches

Petri nets are a discrete event simulation approach developed for system representation, in particular for their concurrency and synchronization properties. Various extensions to the original theory of Petri nets have been used for modeling molecular biology systems and metabolic networks. These extensions are stochastic, colored, hybrid and functional. This paper carries out an initial review of the various modeling approaches based on Petri net found in the literature, and of the biological systems that have been successfully modeled with these approaches. Moreover, the modeling goals and possibilities of qualitative analysis and system simulation of each approach are discussed.     

An algebraic-combinatorial model for the identification and mapping of biochemical pathways

We develop the mathematical machinery for the construction of an algebraic-combinatorial model using Petri nets to construct an oriented matroid representation of biochemical pathways. For demonstration purposes, we use a model metabolic pathway example from the literature to derive a general biochemical reaction network model. The biomolecular networks define a connectivity matrix that identifies a linear representation of a Petri net. The sub-circuits that span a reaction network are subject to flux conservation laws. The conservation laws correspond to algebraic-combinatorial dual invariants, that are called S-(state) and T-(transition) invariants. Each invariant has an associated minimum support. We show that every minimum support of a Petri net invariant defines a unique signed sub-circuit representation. We prove that the family of signed sub-circuits has an implicit order that defines an oriented matroid. The oriented matroid is then used to identify the feasible sub-circuit pathways that span the biochemical network as the positive cycles in a hyper-digraph.     

Object-Oriented Modeling for Flexible Manufacturing Systems

Object-oriented modeling provides a new way of thinking about flexible manufacturing systems, using models organized around real-world concepts. This paper describes how the object modeling technique can be used to develop integrated factory models that embrace factory process modeling as well as policy modeling. Such models can be used to assess how quickly a manufacturing organization can adjust its operations to meet changes in demands for products, consumer preferences, supplier quality, and lead times. These models also can be used as vehicles for studying the impact of introducing new product lines or new process technology without the disruption or expense of pilot projects or test setups.     

Engineering modular ester fermentative pathways in Escherichia coli

Sensation profiles are observed all around us and are made up of many different molecules, such as esters. These profiles can be mimicked in everyday items for their uses in foods, beverages, cosmetics, perfumes, solvents, and biofuels. Here, we developed a systematic ‘natural’ way to derive these products via fermentative biosynthesis. Each ester fermentative pathway was designed as an exchangeable ester production module for generating two precursors− alcohols and acyl-CoAs that were condensed by an alcohol acyltransferase to produce a combinatorial library of unique esters. As a proof-of-principle, we coupled these ester modules with an engineered, modular, Escherichia coli chassis in a plug-and-play fashion to create microbial cell factories for enhanced anaerobic production of a butyrate ester library. We demonstrated tight coupling between the modular chassis and ester modules for enhanced product biosynthesis, an engineered phenotype useful for directed metabolic pathway evolution. Compared to the wildtype, the engineered cell factories yielded up to 48 fold increase in butyrate ester production from glucose.     

Food purchases: Impacts from the consumers’ point of view investigated with a modular LCA

The goal of this research work was to assist consumers in considering environmental aspects of food consumption. A simplified, modular LCA approach has been used to evaluate the impacts from the consumers’ point of view. Comparative LCA’s have been calculated for five single aspects of decisions: type of agricultural practice, origin, packaging material, type of preservation, and consumption. The inventory for one module includes the environmental impacts related to one particular product characteristic. The modular LCA allows one to investigate the trade-offs among different decision parameters. It could be shown that most of the decision parameters might have an influence on the overall impact of a vegetable product. Greenhouse production and vegetables transported by air cause the highest surplus environmental impact. For meat products, the agricultural production determines the overall environmental impact. The total impact for vegetable or meat purchases may vary by a factor of eight or two-and-a-half. Different suggestions for consumers have been ranked according to the variation of average impacts, due to a marginal change of behaviour. Avoiding air-transported food products leads to the highest decrease of environmental impacts.     

A case study in FMS production planning and dispatching

The speedy development and extensive application of computers have helped play a significant role in a new technological revolution. The importance of FMS flexibility in producing a variety of products and adapting rapidly to customer requirements makes FMSs attractive. Further, FMSs are most appropriate for largevariety and medium- to high-volume production environments. However, the module of the FMS production planning system is not perfect. This paper focuses on a new scheme for FMS production planning and dispatching under the realistic assumptions promoted by a particular flexible manufacturing factory. Some practical constraints such as fixture uniqueness, limited tool magazine capacity, and a given number of pallets are considered. The simulation results indicate that the scheme provides a good production plan, according to the short-term plans from the MIS Department. Some conclusions are drawn and a discussion is presented.     

Process flexibility and inventory flexibility via product substitution

This paper studies the optimal control of and interaction between two types of flexibility under Markov models of demand and production: process flexibility and inventory flexibility. In our model, process flexibility is generated by a multi-functional production facility that can produce two types of products, and inventory flexibility is manifested in firm-driven one-way product substitution. Both process flexibility and inventory flexibility are important drivers of supply chain performance and are strategic design considerations. To analyze the interaction between these two types of flexibility, we model a dynamically controlled two-product, make-to-stock system with stochastic processing times and stochastic demand. We characterize the complex joint optimal production and post-production policy for a special case and numerically show that a simply structured multi-threshold policy is a near-optimal heuristic policy for the general case. We gain further insight into the impact of system parameters on the value of process flexibility and inventory flexibility via a comprehensive numerical study. We find that for a wide range of capacity and cost parameters, process flexibility and inventory flexibility complement each other, so pursuing both forms of flexibility is effective.     

Process performance models in the optimization of multiproduct protein production plants

In this work we propose a model that simultaneously optimizes the process variables and the structure of a multiproduct batch plant for the production of recombinant proteins. The complete model includes process performance models for the unit stages and a posynomial representation for the multiproduct batch plant. Although the constant time and size factor models are the most commonly used to model multiproduct batch processes, process performance models describe these time and size factors as functions of the process variables selected for optimization. These process performance models are expressed as algebraic equations obtained from the analytical integration of simplified mass balances and kinetic expressions that describe each unit operation. They are kept as simple as possible while retaining the influence of the process variables selected to optimize the plant. The resulting mixed-integer nonlinear program simultaneously calculates the plant structure (parallel units in or out of phase, and allocation of intermediate storage tanks), the batch plant decision variables (equipment sizes, batch sizes, and operating times of semicontinuous items), and the process decision variables (e.g., final concentration at selected stages, volumetric ratio of phases in the liquid-liquid extraction). A noteworthy feature of the proposed approach is that the mathematical model for the plant is the same as that used in the constant factor model. The process performance models are handled as extra constraints. A plant consisting of eight stages operating in the single product campaign mode (one fermentation, two microfiltrations, two ultrafiltrations, one homogenization, one liquid-liquid extraction, and one chromatography) for producing four different recombinant proteins by the genetically engineered yeast Saccharomyces cerevisiae was modeled and optimized. Using this example, it is shown that the presence of additional degrees of freedom introduced by the process performance models, with respect to a fixed size and time factor model, represents an important development in improving plant design.     

An object-oriented, individual-based approach for simulating the dynamics of genes in subdivided populations

An object-oriented, individual-based simulation framework was developed for modeling the diffusion of genetic material in subdivided populations. Objects representing individual organisms were defined, each with a unique genotype composed of gene objects. The organisms mate and reproduce, and progeny disperse or recruit back to their native population through the use of a Movement interface. The object-oriented approach is also linked to analytical theory through the development of matrix-based equations. An implementation of the model demonstrates how changes to basic population parameters affect spatial and temporal genetic structure. Scalar changes to the system affect the duration over which processes occur as well as the degree of variance, but appear to leave overall structural patterns unchanged. Object-oriented programming provides some unique advantages for modeling population genetic processes, including the use of abstraction and implementation, as well as the ability to accommodate complex, heterogeneous behavior.     

Economic evaluation of the development of a phage therapy product for the control of Salmonella in poultry

Poultry products are one of the major transmission media of Salmonella enteritidis to humans. A promising alternative to reduce the load of Salmonella in poultry are bacteriophages. Elsewhere, a mixture of six bacteriophages has been used successfully, but large-scale production would be necessary to supply potential poultry market and costs analyses have not been calculated yet. For this, a powerful tool to predict production costs is bioprocess modeling coupled with economic analyses. This work aims to model the scaled-up production of a six bacteriophages mixture based on a laboratory/pilot-scale production using Biosolve Process. For the model construction, a combination of experimental and reported data was applied, in which different production alternatives and the range of 1–100% of the Colombian poultry market (at broiler's farm and slaughterhouse) were analyzed. Results indicate that the best cost-effective process configuration/scale is to use one bioreactor (156 L) for the six bacteriophages, then a 0.45 μm filtration for removal of biomass, and a 0.22 μm filtration for sterility; this to supply the 35% of the market size for broiler farms (equivalent to 210 million chickens). This configuration gives a production cost per chicken of US$ 0.02. Additionally, a sensitivity analysis and a theoretical contrast for understanding the impact that titer and recovery have on production scale determined that titer affects the most the cost and requires optimization. The present works serves as a first, and required, approach for the development of phage therapy products that are alternatives to present-day pathogens control strategies.     

A model of structure and catalysis for ketoreductase domains in modular polyketide synthases

A putative catalytic triad consisting of tyrosine, serine, and lysine residues was identified in the ketoreductase (KR) domains of modular polyketide synthases (PKSs) based on homology modeling to the short chain dehydrogenase/reductase (SDR) superfamily of enzymes. This was tested by constructing point mutations for each of these three amino acid residues in the KR domain of module 6 of the 6-deoxyerythronolide B synthase (DEBS) and determining the effect on ketoreduction. Experiments conducted in vitro with the truncated DEBS Module 6+TE (M6+TE) enzyme purified from Escherichia coli indicated that any of three mutations, Tyr --> Phe, Ser --> Ala, and Lys --> Glu, abolish KR activity in formation of the triketide lactone product from a diketide substrate. The same mutations were also introduced in module 6 of the full DEBS gene set and expressed in Streptomyces lividans for in vivo analysis. In this case, the Tyr --> Phe mutation appeared to completely eliminate KR6 activity, leading to the 3-keto derivative of 6-deoxyerythronolide B, whereas the other two mutations, Ser --> Ala and Lys --> Glu, result in a mixture of both reduced and unreduced compounds at the C-3 position. The results support a model analogous to SDRs in which the conserved tyrosine serves as a proton donating catalytic residue. In contrast to deletion of the entire KR6 domain of DEBS, which causes a loss in substrate specificity of the adjacent acyltransferase (AT) domain in module 6, these mutations do not affect the AT6 specificity and offer a potentially superior approach to KR inactivation for engineered biosynthesis of novel polyketides. The homology modeling studies also led to identification of amino acid residues predictive of the stereochemical nature of KR domains. Finally, a method is described for the rapid purification of engineered PKS modules that consists of a biotin recognition sequence C-terminal to the thioesterase domain and adsorption of the biotinylated module from crude extracts to immobilized streptavidin. Immobilized M6+TE obtained by this method was over 95% pure and as catalytically effective as M6+TE in solution.     

Prediction of the pilot-scale recovery of a recombinant yeast enzyme using integrated models

This article describes the rapid prediction of recovery process performance for a new recombinant enzyme product on the basis of a broad portfolio of computer models and highly targeted experimentation. A process model for the recombinant system was generated by linking unit operation models in an integrated fashion, with required parameter estimation and physical property determination accomplished using data from scale-down studies. This enabled the generic modeling framework established for processing of a natural enzyme from bakers' yeast to be applied. An experimental study of the same operations at the pilot scale showed that the process model gave a conservative prediction of recombinant enzyme recovery. The model successfully captured interactions leading to a low overall product yield and indicated the need for further study of precipitate breakage in the feed zone of a disc stack centrifuge in order to improve performance. The utility of scale-down units as an aid to fast model generation and the advantage of integrating computer modeling and scale-down studies to accelerate bioprocess development are highlighted.     

Advances in in-situ product recovery (ISPR) in whole cell biotechnology during the last decade

The review presents the state-of-the-art in the applications of in-situ product recovery (ISPR) in whole-cell biotechnology over the last 10 years. It summarizes various ISPR-integrated fermentation processes for the production of a wide spectrum of bio-based products. A critical assessment of the performance of various ISPR concepts with respect to the degree of product enrichment, improved productivity, reduced process flows and increased yields is provided. Requirements to allow a successful industrial implementation of ISPR are also discussed. Finally, supporting technologies such as online monitoring, mathematical modeling and use of recombinant microorganisms with ISPR are presented.     

Computational design and analysis of modular cells for large libraries of exchangeable product synthesis modules

Microbial metabolism can be harnessed to produce a large library of useful chemicals from renewable resources such as plant biomass. However, it is laborious and expensive to create microbial biocatalysts to produce each new product. To tackle this challenge, we have recently developed modular cell (ModCell) design principles that enable rapid generation of production strains by assembling a modular (chassis) cell with exchangeable production modules to achieve overproduction of target molecules. Previous computational ModCell design methods are limited to analyze small libraries of around 20 products. In this study, we developed a new computational method, named ModCell-HPC, that can design modular cells for large libraries with hundreds of products with a highly-parallel and multi-objective evolutionary algorithm and enable us to elucidate modular design properties. We demonstrated ModCell-HPC to design Escherichia coli modular cells towards a library of 161 endogenous production modules. From these simulations, we identified E. coli modular cells with few genetic manipulations that can produce dozens of molecules in a growth-coupled manner with different types of fermentable sugars. These designs revealed key genetic manipulations at the chassis and module levels to accomplish versatile modular cells, involving not only in the removal of major by-products but also modification of branch points in the central metabolism. We further found that the effect of various sugar degradation on redox metabolism results in lower compatibility between a modular cell and production modules for growth on pentoses than hexoses. To better characterize the degree of compatibility, we developed a method to calculate the minimal set cover, identifying that only three modular cells are all needed to couple with all compatible production modules. By determining the unknown compatibility contribution metric, we further elucidated the design features that allow an existing modular cell to be re-purposed towards production of new molecules. Overall, ModCell-HPC is a useful tool for understanding modularity of biological systems and guiding more efficient and generalizable design of modular cells that help reduce research and development cost in biocatalysis.     

Homology modeling using parametric alignment ensemble generation with consensus and energy-based model selection

The accuracy of a homology model based on the structure of a distant relative or other topologically equivalent protein is primarily limited by the quality of the alignment. Here we describe a systematic approach for sequence-to-structure alignment, called ‘K*Sync’, in which alignments are generated by dynamic programming using a scoring function that combines information on many protein features, including a novel measure of how obligate a sequence region is to the protein fold. By systematically varying the weights on the different features that contribute to the alignment score, we generate very large ensembles of diverse alignments, each optimal under a particular constellation of weights. We investigate a variety of approaches to select the best models from the ensemble, including consensus of the alignments, a hydrophobic burial measure, low- and high-resolution energy functions, and combinations of these evaluation methods. The effect on model quality and selection resulting from loop modeling and backbone optimization is also studied. The performance of the method on a benchmark set is reported and shows the approach to be effective at both generating and selecting accurate alignments. The method serves as the foundation of the homology modeling module in the Robetta server.     

Structural and functional analysis of C2-type ketoreductases from modular polyketide synthases

The process by which α-stereocenters of polyketide intermediates are set by modular polyketide synthases (PKSs) when condensation is not immediately followed by reduction is mysterious. However, the reductase-incompetent ketoreductase (KR) from the third module of 6-deoxyerythronolide B synthase has been proposed to operate as a racemase, aiding in the epimerization process that reverses the orientation of the α-methyl group of the polyketide intermediate generated by the ketosynthase to the configuration observed in the 6-deoxyerythronolide B final product. To learn more about the epimerization process, the structure of the C2-type KR from the third module of the pikromycin synthase, analogous to the KR from the third module of 6-deoxyerythronolide B synthase, was determined to 1.88 Å resolution. This first structural analysis of this KR-type reveals differences from reductase-competent KRs such as that the site NADPH binds to reductase-competent KRs is occluded by side chains and the putative catalytic tyrosine possesses more degrees of freedom. The active-site geometry may enable C2-type KRs to align the thioester and β-keto groups of a polyketide intermediate to reduce the pK_a of the α-proton and accelerate its abstraction. Results from in vivo assays of engineered PKSs support that C2-type KRs cooperate with epimer-specific ketosynthases to set the configurations of substituent-bearing α-carbons.