Synthesis of industrial systems based on value analysis (original) (raw)
Synthesis of industrial system based on value analysis
Computer Aided Chemical Engineering, 2005
In this contribution, we present a novel methodology for flexible design of industrial systems based on detailed differential value analysis (Sadhukhan, J. Ph.D. Dissertation, UMIST, Manchester, U.K., 2002). Evolving from graph theory this methodology performs better than conventional mathematical programming based optimisation approaches through systematic structural decomposition of large scale industrial systems into basic processing elements (paths and trees), which helps to reduce the size and the complexity of large combinatorial problems and comprehensively analyse the multiple objectives, set of optimal operating states and marginal contributions at elemental levels that are critical for flexible designs.
Analytical optimisation of industrial systems and applications to refineries, petrochemicals
Chemical Engineering Science, 2004
A new method for optimising process networks is presented in this paper. The method uses economic analysis of existing systems based on the value analysis method derived by Sadhukhan (2002) as the basis to derive the optimum network design. Optimising a large scale industrial system (e.g. refineries, petrochemicals) where multiple processes, many material streams and a number of supporting systems (e.g. energy) are involved, is a difficult task to achieve. For such a case, a fundamental, practical and systematic methodology for detailed differential economic analysis (Sadhukhan et al, 2003) of an industrial system at any market and environmental condition can be very useful for achieving its optimal operation.
Computers & Chemical Engineering, 2014
The developments obtained in recent years in the field of mathematical programming considerably reduced the computational time and resources needed to solve large and complex Mixed Integer Non Linear Programming (MINLP) problems. Nevertheless, the application of these methods in industrial practice is still limited by the complexity associated with the mathematical formulation of some problems. In particular, the tasks of design space definition and representation as superstructure, as well as the data collection, validation and handling may become too complex and cumbersome to execute, especially when large problems are considered. In an earlier work, we proposed a computer-aided framework for synthesis and design of process networks. In this contribution, we expand the framework by including methods and tools developed to structure, automate and simplify the mathematical formulation of the design problem. Furthermore, the models employed for the representation of the process alternatives included in the superstructure are refined, through the inclusion of the energy balance. Finally, the features of the framework are highlighted through the solution of two case studies focusing on food processing and biofuels.
Graph-theoretic approach to process synthesis: axioms and theorems
1992
The maximal structure, which can be expressed as a process graph (P-graph), is the union of all eombinatorially feasible process structures of a synthesis problem. This is analogous to the conventionalIy used term "superstructure" which has not yet been defined mathematically, and thus, cannot be analyzed mathematically. Since a mathematical programming method of process synthesis requires a mathematical model, as its input, based on the super or maximal structure, generating this structure is a problem of fundamental importance. Algorithm MSG, presented here, appears to be the first published algorithm for generation of the maximal structure. This algorithm is efficient because its complexity is polynomial. It is, therefore, advantageous for solving large industrial process synthesis problems. The mathematical basis of maximal structure, the proof of all statements and validation of algorithm MSG are also presented.
A Framework for Computer Aided Modeling, Design, and Optimization of Integrated Industrial Systems
1998
Abstract Computer aided modeling and design of industrial systems presents great potential for facilitating the construction of industrial systems which maximize utilization of materials, minimize emissions of harmful wastes, and preserve economic feasibility. A framework for modeling industrial systems that is to form the basis of a design system is described. The model takes an industrial system to be a collection of processes each characterized by their inputs and outputs of materials, energy, finances, and labor.
Combinatorial Technique for the Design and Synthesis of Large Scale Manufacturing Systems
IFAC Proceedings Volumes, 1993
Manufacturing systems synthesis (MSS) is an-W Itcp in dcaiping any lIWlUfaduring I)'Item for producing desired products from available raw materials or piecea of Itock. A lIWlUfaduring I)'Item is a networtt of nWlUfacturing or operating units where input material speciea or rnadIine pu1a are traIIIIformed into output material species or machine parts by ahering their physical, chemical, or biological properties. The importance of MSS uiaea from the fact that essentially every industrial product is manufactured through IUdt a networic. Often, a large number of different networks are available; moreover, the profitability of the same product from different networks may vary widely. Methods for general network synthesis problems are unable to IOlve MSS because of the unique combinatorial feature of manufacturing systems. The combinatorial part of MSS has been examined hen: for developing algorithmic procedures to generate the optimal manufaduring systems.
Computers & Chemical Engineering, 2012
The synthesis and design of processing networks is a complex and multidisciplinary problem, which involves many strategic and tactical decisions at business (considering financial criteria, market competition, supply chain network, etc.) and engineering levels (considering synthesis, design and optimization of production technology, R&D, etc.), all of which have a deep impact on the profitability of processing industries. In this study, an integrated business and engineering framework for synthesis and design of processing networks is presented. The framework employs a systematic approach to manage the complexity while solving simultaneously both the business and the engineering aspects of problems, allowing at the same time, comparison of a large number of alternatives at their optimal points. The results identify the optimal raw material, the product portfolio and select the process technology for a given market scenario together with the optimal material flows through the network and calculate the corresponding performance and sustainability metrics. The framework includes a software infrastructure for integrating different methods and tools needed for problem definition, formulation and solution of the design problem as a MINLP, reducing thereby the time and cost needed to generate and solve the design/synthesis problems and providing efficient data transfer between the tools. A generic structural process model has been implemented within the framework to describe the multidimensional engineering issues allowing thereby fast and flexible model development for various production processes. A case study from vegetable oil industry is used successfully to demonstrate the applicability of the integrated framework for making optimal business and engineering decisions.
Ultra-flexible Factories: An Approach to Manage Complexity
Procedia CIRP, 2020
In today's business environment, the trend towards more product variety and customization is unbroken. Due to this development, the need of agile and reconfigurable production systems emerged to cope with various products and product families. To design and optimize production systems as well as to choose the optimal product matches, product analysis methods are needed. Indeed, most of the known methods aim to analyze a product or one product family on the physical level. Different product families, however, may differ largely in terms of the number and nature of components. This fact impedes an efficient comparison and choice of appropriate product family combinations for the production system. A new methodology is proposed to analyze existing products in view of their functional and physical architecture. The aim is to cluster these products in new assembly oriented product families for the optimization of existing assembly lines and the creation of future reconfigurable assembly systems. Based on Datum Flow Chain, the physical structure of the products is analyzed. Functional subassemblies are identified, and a functional analysis is performed. Moreover, a hybrid functional and physical architecture graph (HyFPAG) is the output which depicts the similarity between product families by providing design support to both, production system planners and product designers. An illustrative example of a nail-clipper is used to explain the proposed methodology. An industrial case study on two product families of steering columns of thyssenkrupp Presta France is then carried out to give a first industrial evaluation of the proposed approach.
Logic-based MINLP algorithms for the optimal synthesis of process networks
Computers & Chemical Engineering, 1996
In this paper, the MINLP problem for the optimal synthesis of process networks is modeled as a discrete optimization problem involving logic disjunctions with nonlinear equations and pure logic relations. The logic disjunctions allow the conditional modeling of equations (e.g. if a unit is selected, apply mass/heat balances; otherwise, set the flow variables to zero). It is first shown that this framework for representing discrete optimization problems greatly simplifies the step of modeling. The outer approximation algorithm is then used as a basis to derive a new logic-based OA solution method which naturally gives rise to NLP sub-problems that avoid zero flows and a disjunctive LP master problem. The initial NLP sub-problems, that provide linearizations for all the terms in the disjunctions, are selected through a set-covering problem for which we consider both the cases of disjunctive and conjunctive normal form logic. The master problem, on the other hand, is converted to mixed-integer form using a convex-hull representation. Furthermore, based on some interesting relations of outer approximation with generalized Benders decomposition, it is also shown that it is possible to derive a logic-based method for the latter algorithm. The proposed algorithm has been tested on several structural optimization problems, including a flowsheet example showing distinct advantages in robustness and computational efficiency when compared to standard MINLP models and algorithms.
Advances in mathematical programming for the synthesis of process systems
This paper presents a review of advances that have taken place in the mathematical programming approach to process design and synthesis. A review is first presented on the algorithms that are available for solving MINLP problems, and its most recent variant, Generalized Disjunctive Programming models. The formulation of superstructures, models and solution strategies is also discussed for the effective solution of the corresponding optimization problems. The rest of the paper is devoted to reviewing recent mathematical programming models for the synthesis of reactor networks, distillation sequences, heat exchanger networks, mass exchanger networks, utility plants, and total flowsheets. As will be seen from this review, the progress that has been achieved in this area over the last decade is very significant.