Ferenc Friedler

University of Pannonia, Veszprém, Gyulafirátót, Veszprém, Hungary

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Publications (100)92.37 Total impact

  • Ferenc Friedler, Ka Ming Ng
    Current Opinion in Chemical Engineering. 01/2013;
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    ABSTRACT: The present work proposes a computer-aided methodology for designing sustainable supply chains in terms of sustainability metrics by utilizing the P-graph framework. The methodology is an outcome of the collaboration between the Office of Research and Development (ORD) of the U.S. EPA and the research group led by the creators of the P-graph framework at the University of Pannonia. The integration of supply chain design and sustainability is the main focus of this collaboration. The P-graph framework provides a mathematically rigorous procedure for synthesizing optimal and alternative suboptimal networks subject to multiple objectives and constraints, which include profitability and sustainability in the proposed methodology. Specifically, to evaluate the sustainability of a given process under construction including its supply chain, sustainability metrics are incorporated into the design procedure. The proposed methodology is demonstrated with the optimal design of a supply chain for providing heat and electric power to an agricultural region with relatively limited land area where agricultural wastes can potentially be recovered as renewable resources. The objective functions for optimization comprise the profit and the ecological footprint. The results of the study indicate that, compared to using electricity from the grid and/or natural gas, using renewable energy resources can yield substantial cost reductions of up to 5%, as well as significant ecological footprint reductions of up to 77%. It may, therefore, be possible to design more sustainable supply chains that are both cost-effective and less environmentally damaging.
    Industrial & Engineering Chemistry Research. 11/2012; 52(1):266–274.
  • Mate Barany, Botond Bertok, L T Fan, Ferenc Friedler
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    ABSTRACT: The determination of reaction pathways is one of the most important functions that should be performed in exploring the kinetics of catalyzed chemical reactions or biochemical reactions, the latter being generally catalyzed by enzymes. It is proven that the terms, "type-I extreme pathway" and "structurally minimal pathway", both introduced to characterize the kinetics of a catalyzed reaction are equivalent. These two terms are based on two distinct methodologies, one mainly rooted in convex analysis and the other in graph theory. The equivalence promises further even more effective methods for reaction-pathway identification by synergistic integration of existing ones.
    Bioprocess and Biosystems Engineering 11/2012; · 1.87 Impact Factor
  • Ferenc Friedler, Ka Ming Ng
    Current Opinion in Chemical Engineering. 11/2012; 1(4):418–420.
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    ABSTRACT: The current work reveals a methodology that provides an adequate basis to portray and model supply chains mathematically and formally as well as to synthesize optimal and alternative supply scenarios algorithmically while taking into account structural redundancy. The proposed methodology is based on the combinatorial foundations of algorithmic process synthesis or more specifically on the P-graph framework. A biodiesel supply network involving blending and transportation serves as an illustrative example. A novel algorithm generates the mathematical model and alternative solutions to increase reliability of supply scenarios. Major steps of the generation are the structure generation and estimation of reliability of a supply scenario.
    Industrial & Engineering Chemistry Research. 10/2012; 52(1):181–186.
  • Botond Bertok, Mate Barany, Ferenc Friedler
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    ABSTRACT: The primary aim of process-network synthesis, or PNS in short, is to determine the best process network achieving a desired goal, e.g., producing a set of desired products or satisfy demands. PNS has a long history, and numerous methods for executing it are available. Its acceleratedly increasing importance can be attributed to the need to respond to the rapid emergence of new technologies and fast changes in the economic environment. It is highly desirable that any corporation be able to ascertain if a new technology is viable for its business as well as to assess if its current technology remains sustainable in the changing environment. Herein, a novel method and software for PNS are proposed for generating, optimizing, and analyzing alternative process designs at the conceptual level. The method is illustrated by synthesizing alternative process designs with different network structures for the production of butanol, ethanol, and acetone from grains. Furthermore, the sustainability of the resultant process designs is analyzed. This is executed by varying the payout period and the production rate, i.e., load.
    Industrial & Engineering Chemistry Research. 10/2012; 52(1):166–171.
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    ABSTRACT: An effective strategy comprising two phases is proposed to determine the thermodynamically dominant pathways in a metabolic network of a given phenotype, involving several metabolic reactions. In the first phase, stoichiometrically feasible metabolic pathways are exhaustively identified through the flux balance analysis and the graph-theoretic method based on P-graphs. In the second phase, thermodynamically dominant pathways are selected from these stoichiometrically feasible metabolic pathways on the basis of the Gibbs free energy change of reaction. The proposed strategy’s efficacy is demonstrated by applying it to two E. coli models: one is for maximal acetate and ethanol production, and the other is for maximalpoly(3-hydroxybutyrate) production.
    Industrial & Engineering Chemistry Research. 07/2012; 52(1):222–229.
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    ABSTRACT: Hitherto, no attempt has been made to identify exhaustively feasible pathways for any mechanism of a given reaction catalyzed by a catalyst with multiactive sites. Two stoichiometically exact and definitely feasible mechanisms have been proposed to date for the hydrogenation of ethylene to ethane on biactive-site or triactive-site platinum catalysts. One comprises seven elementary reactions, and the other comprises eight elementary reactions; nevertheless, both mechanisms involve competitive as well as noncompetitive adsorption. Any of these mechanisms gives rise to a multitude of feasible catalytic pathways. The present work exhaustively identifies such feasible pathways by resorting to the inordinately efficient graph-theoretic algorithm based on P-graphs (process graphs). The efficacy of this algorithm has been amply demonstrated by successfully deploying it for several catalysts with single-active sites, but has never been deployed for catalysts with multiactive sites as in the current work. The availability of exhaustively identified feasible pathways for both mechanisms renders it possible to stipulate that the hydrogenation of chemisorbed chemisorbed C2H5 is the rate-controlling step: This step is contained in either mechanism.
    Industrial & Engineering Chemistry Research 01/2012; 51:2548-2552. · 2.24 Impact Factor
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    M At, Hegyh Ati, Ferenc Friedler
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    ABSTRACT: Methods for solving batch process scheduling problems have gone through a vast development in the last 2 decades. Most of the published approaches are based on a mixed integer programming formulation. Since the difficulty of scheduling is originated from its combinatorial nature, graphs and combinatorial algorithms are more adequate to represent and solve the problem. Although, combinatorial algorithms and data structures have an enormous literature, these algorithms can not be directly applied to scheduling and further elaboration is needed. In the present work, the combinatorial nature of batch scheduling problems is analyzed. Several combinatorial algorithms are listed that can be considered for the scheduling of batch processes. Their proper adaptation is illustrated via the S-graph framework, in which the main emphasis lies on the combinatorial tools. Furthermore, Place Petri Nets and Timed Automata are also briefly described. An S-graph algorithm has been extensively compared with well-known MILP formulations. ' COMBINATORIAL NATURE OF BATCH PROCESS SCHEDULING Scheduling is a key problem in the operation of batch plants. The industry generates a wide range of batch scheduling problems, where the goal in general is to allocate the tasks of the process to the available equipment units in the most favorable way. 1,2 An ordinary batch scheduling problem is given by the master recipe of the process, the objective, and the intermediate storage policy. The most common objectives are the minimization of the whole processing time, i.e., makespan, or the maximization of the throughput or profit over a fixed time horizon. According to different problems, the storage policy can vary between unlimited intermediate storage (UIS), finite intermediate storage (FIS), common intermediate storage (CIS), nonintermediate storage (NIS), and zero-wait (ZW). 3,4 Problem specification may include further parameters, e.g., transfer times, changeover times, or variable processing times. 5 The recipe defines the set of products to be produced, the network of tasks to produce the desired products, the available equipment units, processing times, stoi-chiometric data, etc. In the case of a complex recipe, i.e., when the process does not have sequential characteristics, the unambiguous representation of the network of the tasks is not evident. 6 In batch process scheduling, mostly directed graphs, e.g., State-Task-Net-work (STN), 7 Resource-Task-Network (RTN), 8 State-Sequence-Network (SSN), 9 S-graph, 10 Timed Place Petri Net (TPPN), 11 or Priced Timed Automata (PTA) 12 are applied for this purpose. Despite the wide range of available graph representations, most of the approaches consider them only as a graphical representation and not as the model for the optimization. The combinatorial nature of batch scheduling problems derives from the two main decisions to be made during the optimization process: (i) which processing unit is assigned to a task (if more than one is available) and (ii) what is the order of the tasks to be performed in an equipment unit. Moreover, if the objective is to maximize the throughput, the optimal number of batches has to be also identified, which is an additional computational issue. Even though the major decisions are made in discrete space, the problems may involve decisions on continuous variables, e.g., batch sizing, that can usually be handled with an LP model, which requires much less computational effort compared to the combi-natorial part of the problem.
    Eng. Chem. Res. 05/2011; 50:5169-5174.
  • Máté Hegyháti, Ferenc Friedler
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    ABSTRACT: Methods for solving batch process scheduling problems have gone through a vast development in the last 2 decades. Most of the published approaches are based on a mixed integer programming formulation. Since the difficulty of scheduling is originated from its combinatorial nature, graphs and combinatorial algorithms are more adequate to represent and solve the problem. Although, combinatorial algorithms and data structures have an enormous literature, these algorithms can not be directly applied to scheduling and further elaboration is needed. In the present work, the combinatorial nature of batch scheduling problems is analyzed. Several combinatorial algorithms are listed that can be considered for the scheduling of batch processes. Their proper adaptation is illustrated via the S-graph framework, in which the main emphasis lies on the combinatorial tools. Furthermore, Place Petri Nets and Timed Automata are also briefly described. An S-graph algorithm has been extensively compared with well-known MILP formulations.
    Industrial & Engineering Chemistry Research. 04/2011; 50(9):5169–5174.
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    ABSTRACT: Large amounts of thermal energy are transferred between fluids for heating or cooling in industry as well as in the residential and service sectors. Typical examples are crude oil preheating, ethylene plants, pulp and paper plants, breweries, plants with exothermic and endothermic reactions, space heating, and cooling or refrigeration of food and beverages. Heat exchangers frequently operate under varying conditions. Their appropriate use in flexible heat exchanger networks as well as maintenance/reliability related calculations requires adequate models for estimating their dynamic behaviour. Cell-based dynamic models are very often used to represent heat exchangers with varying arrangements. The current paper describes a direct method and a visualisation technique for determining the number of the modelling cells and their size.
    Computers & Chemical Engineering. 01/2011; 35:943-948.
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    Petar Sabev Varbanov, Ferenc Friedler
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    ABSTRACT: Fuel cells (FCs) are important for building combined energy systems due to their high efficiency. Molten Carbonate FCs (MCFC) and Solid Oxide FCs (SOFC) have been identified as best candidates for FC Combined Cycles (FCCC). This paper presents a procedure for evaluating the trends in emission levels and economics of FCCC based energy conversion systems, utilising biomass and/or fossil fuels. This involves significant combinatorial complexity, efficiently handled by the P-graph algorithms. A procedure for the synthesis of cost-optimal FCCC configurations is developed, accounting for the carbon footprint of the technology and fuel options. The results show that such systems employing renewables can be viable for wide range of economic conditions, due to the high energy efficiency of the FC-based systems.
    Applied Thermal Engineering 01/2011; 28(16). · 2.13 Impact Factor
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    B. Bertok, R. Adonyi, F. Friedler, L. T. Fan
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    ABSTRACT: Scheduling plays a key role in batch process operation; it has a major effect on the process' performance. Available methods for determining the optimal schedule are primarily based on either MILP/MINLP formulation in conjunction with mathematical programming (Floudas and Lin, 2004; Vaklieva-Bancheva and Kirilova, 2010) or graph representation in conjunction with combinatorial algorithms (Sanmarti et al., 2002).The current work comprises three major contributions. First, an algorithm has been crafted to generate a superstructure for a scheduling problem. The problem is defined in the form of an S-graph representing the recipe. The superstructure contains exclusively every step potentially performed by any of the functional or operating facilities or equipment units capable of completing at least one task to be scheduled. These steps involve executions of tasks and changeovers from one task to another. Second, an MILP formulation is elaborated on the basis of the superstructure, which guarantees the optimal solution of the scheduling problem. Third, a relaxation of the MILP model is incorporated into the S-graph algorithms to support the selection of subproblems and decision variables in the branch-and-bound procedure.
    01/2011;
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    ABSTRACT: Processes and markets uncertainties make batch plants a complex environment to manage production activities. Uncertainties may cause deviations and infeasibilities in predefined schedules; this may result in poor planning and inefficient utilization of materials. Consequently, the relevance of explicitly incorporating variability in the scheduling formulation in order to offer more efficient plans and robust decisions to changes has become recognized. This work addresses the batch plants scheduling under exogenous uncertainty. The most widely utilized approach to tackle this problem is stochastic programming; however its solution results in high computational expenses. From another standpoint S-graph, a graph-theoretic approach, has proved to be very efficient to deal with deterministic scheduling. In this work, the S-graph framework is enhanced so that stochastic scheduling problems can be handled. For this purpose, a LP model that is used as performance evaluator has been coupled with S-graph framework. One of the main advantages of the proposed approach is that the search space does not increase according to the number of scenarios considered in the problem. Finally, the potential of the proposed framework is highlighted through two illustrative examples. KeywordsScheduling-Uncertainty-S-graph
    Clean Technologies and Environmental Policy 01/2010; 12(2):105-115. · 1.83 Impact Factor
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    ABSTRACT: The paper provides an overview based on an experience and applications of process integration, modelling and optimisation software tools. The first part reviews the design practice and supporting software tools. General purpose optimisation and modelling tools overviews have been available from conferences and publication (Klemeš, 1977; Friedler, 2009 and 2010; Klemeš et al., 2010; Lam et al., 2010). Those are categorised as (i) Process integration and retrofit analysis tools (ii) Flowsheeting simulation and (iii) General mathematical modelling suites with optimisation libraries. The second part covers assessment of tools which enable the generation of sustainable alternatives. They deal with waste, environment, energy and material depletion and production cost constrains. Emphasis of the sustainable process design tools is on (a) Evaluation of process viability under sustainable economic conditions (b) Synthesis of sustainable processes and supply chains (c) Process maintenance and life cycle analysis. The concluding part provides an overview of software tools development and the potential of the research based tools in solving the problem of sustainable process design.
    Asia-Pacific Journal of Chemical Engineering 01/2010; 21:48-7. · 0.80 Impact Factor
  • Jiří Klemeš, Ferenc Friedler
    Applied Thermal Engineering - APPL THERM ENG. 01/2010; 30(1):1-5.
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    Virag Varga, Istvan Heckl, Ferenc Friedler, L T Fan
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    ABSTRACT: A novel programming framework has been developed for the P-graph-based methodology to provide a standardized software environment for different classes of process-network synthesis (PNS) problems. The P-graph framework has been proven highly successful; its applicability encompasses wide-ranging areas such as reaction-pathway identification, vehicle-routing problems and business-process modeling. A uniform programming paradigm has been proposed here to integrate various available solution engines and interfaces of different types of PNS problems into a single system. A client server architecture with a standardized communication protocol has also been developed, which renders it to be deployable by various client programs with different features, possibly implementable in different programming languages, or adoptable by varied solvers customized for specific problems. Numerous P-graph-based algorithms have been implemented to demonstrate the efficacy of the P-graph framework.
    01/2010;
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    ABSTRACT: Catalytic decomposition of methanol (MD) plays a vital role in hydrogen production, which is the desirable fuel for both proton exchange membrane and direct methanol fuel cell systems. Thus, the catalytic mechanisms, or pathways, of MD have lately been the focus of research interest. Recently, the feasible independent pathways (IPis) have been reported on the basis of a set of highly plausible elementary reactions. Nevertheless, no feasible acyclic combined pathways (APis) comprising IPis have been reported. Such APis cannot be ignored in identifying dominant pathways.
    Computers & Chemical Engineering 01/2010; · 2.09 Impact Factor
  • Clean Technologies and Environmental Policy 01/2010; 12(2):106. · 1.83 Impact Factor
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    Máté Hegyháti, Ferenc Friedler
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    ABSTRACT: The operation of a production facility has a major effect on the efficiency; therefore it is of upmost importance to find the best possible schedule. Due to the high practical expediency, the topic of batch process scheduling has gained growing interest in the last two decades and many approaches have been published to solve a wide variety of scheduling problems. In the present work first the different type of batch scheduling problems are overviewed, then the advantages and disadvantages of the available methods for batch process scheduling are summarized.
    Chemical Engineering Transactions. 01/2010; 21:895-900.

Publication Stats

714 Citations
92.37 Total Impact Points

Institutions

  • 1995–2013
    • University of Pannonia, Veszprém
      • • Department of Computer Science and Systems Technology
      • • Faculty of Information Technology
      Gyulafirátót, Veszprém, Hungary
  • 2012
    • Lands Department of The Government of the Hong Kong Special Administrative Region
      Hong Kong, Hong Kong
  • 2010
    • Yuan Ze University
      • Department of Chemical Engineering & Materials Science
      Taoyuan City, Taiwan, Taiwan
  • 1992–2010
    • Kansas State University
      • Department of Chemical Engineering
      Manhattan, KS, United States
  • 2006
    • University of Pretoria
      • Department of Chemical Engineering
      Pretoria, Gauteng, South Africa
  • 2005
    • Korea Advanced Institute of Science and Technology
      • Metabolic and Biomolecular Engineering National Research Laboratory
      Seoul, Seoul, South Korea
  • 2002–2003
    • Polytechnic University of Catalonia
      • Department of Chemical Engineering (EQ)
      Barcelona, Catalonia, Spain
  • 1993–1995
    • Hungarian Academy of Sciences
      Budapeŝto, Budapest, Hungary