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Siting Optimization of Facility and Unit Relocation with the Simultaneous Consideration of Economic and Safety Issues
Abstract
A general optimization model is proposed to determine the optimal plant layout with the simultaneous consideration of economic and safety aspects. An important characteristic of the proposed optimization model is that it allows the relocation of some of the existing units to reduce the risks associated with current locations. The formulation also allows the addition of new units. A multiobjective mixed-integer linear programming model (MO-MILP) is developed to determine the optimal location of new and existing units while accounting for cost and risk. The proposed model is analyzed through a case study for a hexane distillation process showing the advantages of considering the possibility of relocating units originally installed following exclusively heuristic approaches and economic criteria.
... Another study proposed a multi-objective mixed-integer linear programming model to optimize the plant layout by considering both economic or cost factors and safety considerations. 12 Additionally, a different study presented a mixed-integer nonlinear programming (MINLP) model for optimizing plant layout while prioritizing safety concerns. 13 Use of the idea of inherent process safety is particularly relevant at the early design stages, including that of the plant layout. ...
... This is evident from the value of the DHS (Table 13) plant boundaries. DHI for units A and F is calculated using Equation (12) and displayed in Table 15 for all three cases. The table clearly shows that the DHI values are minimum for case 3. ...
... Consequently, no protection devices are installed at unit H. The DHI for units A and F is determined using Equation(12) and detailed inTable 20. The overall DHI for this layout is 40.2. ...
An optimal process plant layout needs to ensure that the associated piping and land costs are minimized, while the overall safety is maximized. Although various approaches to optimizing plant layout exists in the literature, none considers the essential need for simultaneous compliance with local risk regulations. Employing mixed‐integer nonlinear programming, this article presents a methodology to enable design of layout of a major hazard plant, while simultaneously achieving conformity with both applicable individual and societal risk acceptance criteria. The algorithm is applied to a model plant which poses hazards of toxic gas releases, fires, and explosions. Additional risks of domino effects due to fires and explosions are also incorporated. The results of the article suggest that the approach can be employed to automate any plant layout optimization exercise while ensuring regulatory compliance concurrently. The proposed approach can help substitute the iterative, manual process that is presently applied in practice.
... Xu and Li (2012) tackle the complexities of dynamic construction site layout, striving to minimize costs while maximizing the distance between high-risk and high-protection facilities to enhance safety. Martinez-Gomez et al. (2014) address a multi-objective Facility Layout Problem for relocating existing facilities, focusing on risk reduction. They employ the ε-constraint method to balance cost and risk objectives, ingeniously transforming the multi-objective problem into a single objective for optimal solutions. ...
Facility layout problem is crucial in the design of manufacturing systems across industries due to their significant economic implications and considerable impact on various decision criteria, such as safety considerations in the casting industry. The presence of hazardous equipment like furnaces and melt casting units underscores the necessity of layouts that mitigate safety risks. This study introduces a multi-objective programming model tailored for addressing unequal area layouts, simultaneously optimizing transportation costs and safety risks. The proposed nonlinear model is transformed into a linear equivalent to facilitate solution. To generate the non-dominated Pareto solutions, the NSGA-II algorithm is employed, further fine-tuned by the Taguchi method for parameter optimization. Additionally, Goal Programming is applied to derive a singular solution from the Pareto set. Empirical validation is conducted using real-world data from a casting workshop. The results underscore the model's practicality and effectiveness in a real-world context.
... Therefore, researchers have approached the use of multiobjective optimization to incorporate inherent safety design into established processes; ideally, these concepts should be taken into account in the design stage [112], resulting in scenarios that aid in the decision-making process in order to find the optimal design. Some authors have used multi-objective optimization combined with quantitative risk analysis tools to re-evaluate plant layouts, evaluating the trade-offs in safety and economic objectives [113][114][115], while others have used risk assessment to redesign process equipment and networks considering thermodynamic parameters [116][117][118][119]. Another approach was made to reduce risk values across all potential hazards in an industry, taking into consideration the constraint of a given safety investment budget, minimizing company costs by reducing the risk of accidents [120]. An algorithm can also be used to select the optimal safety measures [121], considering costs and their contribution to the system risk reduction; the approach yielded results that minimized hazard risks and total cost. ...
Industrial processes provide several of the products and services required for society. However, each industry faces different challenges from different perspectives, all of which must be reconciled to obtain profitable, productive, controllable, safe and sustainable processes. In this context, multi-objective optimization has become a powerful tool to aid the decision-making mechanism in the synthesis, design, operation and control of such processes. The solution to the mathematical models provides the necessary tools to asses the system performance in terms of different metrics and evaluate the trade-offs between the objectives in conflict. The number of applications of multi- objective optimization in industrial processes is ample and each application has its own challenges. In the present literature review, a broad panorama of the applications in multi-objective optimization is presented, including future perspectives and open questions that still need to be addressed.
... However, very few works about industrial FLPs have applied multi-objective optimization. As far as we know, only Martinez-Gomez et al. 7,28 proposed a multi-objective mixed integer linear programming (MO-MILP) model for industrial FLPs. The total annualized cost and the number of expected fatalities were chosen to be the two objectives. ...
The general layout design significantly impacts the economy and safety performance of an industrial park. In most of the previous works, safety issues are converted to economic numbers in objective functions. However, this conversion is not appropriate. In this work, a multi-objective optimization method is proposed to obtain a set of solutions that achieves different trade-offs between economy and safety. An improved FLUTE algorithm is employed to obtain the most economical pipe networks. An extended risk map method is proposed to describe the distribution of risk considering the uncertainty of weather conditions. The proposed model is compared with a single-objective method in one case study to show the superiority of the proposed method. In addition, three different evolutionary algorithms are employed to solve a second case for comparison. The results show that the non-dominated sorting genetic algorithm - II (NSGA-II) is more effective for industrial FLPs with multi-objective.
... Using a grid-based model, Wang et al. (2017) optimized the layout of an industrial area to improve economic performance and safety simultaneously. Martinez-Gomez et al. (2014) proposed a grid-based layout model in which the units can occupy one or more grids, and the relocation of some units is allowed. As for the continuous model, the coordinates of units can vary continuously. ...
The general layout design of an industrial park has a significant impact on safety, transportation, piping, and land occupation. Currently, the relevant studies are not mature, and most of the practical designs heavily rely on expertise. In this work, an optimization methodology is proposed to consider safety, piping connection, and occupied land simultaneously for the layout problem. A method based on an improved FLUTE algorithm is developed to optimize the pipe network arrangement. Quantitative risk analysis is employed to describe the safety aspect and the interaction among multiple hazard resources. A continuous model is used rather than a grid model to describe occupied land. The first case study illustrates that the improved FLUTE algorithm can find a better pipe network connection compared to previous algorithms with up to 38% reduction of cost. In the second case study, the layout-relevant cost from the proposed model is 6.3% lower than from a previous model, and the effectiveness of the model for multiple hazard sources is also illustrated. A Monte Carlo simulation is employed to test the optimal layout obtained from the proposed model. The results indicate the feasibility and the acceptability of accident consequences of the obtained layout. Consequently, the proposed model can significantly enhance safety and reduce capital cost for an industrial park.
... Halwagi et al. (2013) proposed a mathematical model for multi-objective economic-safety optimization of bio-refineries. Gomez et al. (2014), similarly, proposed an economic-safety optimization framework for unit relocations in petrochemical plants. Although recently many research studies have been devoted to the issue of multi-objective safety-economic concurrent optimizations in different studies (see e.g., Riauke and Bartlett, 2009; Torres-Echeverría et al., 2012; Hoffenson et al., 2014) yet, to the best of the authors' knowledge, no similar model has been proposed yet for the specific case of surface mining operations, and in particular, the off-road-related-accidents in the US surface mine industry. ...
Off-road-truck-related accidents are a major cause of considerable losses in the US surface mining industry. Though the rates of fatalities, permanent disabilities and other injuries have shown decreasing trends in the past decade, the associated lost lives and working days are far from a “zero work place accident policy” in this industry. After identification of the root cause(s) of off-road truck related accidents, the major task is to decide on the implementation of appropriate safety measures. In cases that there are several alternatives, an optimal decision should be taken in order to choose the most effective alternative(s) which incur minimum costs while achieving maximum improvements. The three major objectives are defined, in this study, as (i) maximization of loss prevention, (ii) minimization of costs, and (iii) maximization of reliability of safety measures. A multi-objective three-function-two-variable mathematical framework for optimization of the decision is proposed. The framework is examined in a generic mining situation to demonstrate its applicability. The genetic algorithm method was used to solve the multi-objective decision problem. The results identified the most effective safety measures and the optimal time interval that each one should be employed to achieve the best results.
... In this figure is possible to appreciate the geographic location of the configuration (Process Design, A, B, C and D) as well as other facilities involved in the process: control room (CR), administrative building (AB) and warehouse (WH). The number of persons residing in these facilities is 10, 15 and 7, respectively (based on the typical number of people needed in these facilities, Martinez-Gomez et al., 2013b). The assessment of the consequences consists in finding the probability of damage that these accidents cause to other facilities or personnel. ...
Traditionally, the design of a separation sequence for the biobutanol production has been based primarily on economic criteria with little or no consideration to the environmental and safety issues. Since biobutanol is produced from acetone-butanol-ethanol (ABE) fermentation, the process involves several substances that may cause fire and explosion and can lead to negative environmental and health impact. Hence, it is desirable to incorporate safety and environmental issues in the design objectives to determine the optimal separation route. This work presents an optimization approach for the biobutanol separation process from the ABE fermentation while accounting simultaneously for economic, environmental and safety objectives. The optimization is carried out through a differential evolution with a Tabu search algorithm, where several Pareto solutions are identified and some routes are highlighted to determine the best compensated solutions. In this case, the best economic solution involves elevated values of the Eco-Indicator 99, the best environmental solution incurs high costs, and the safest solution features less separation columns. The most compensated solutions include configurations that represent a balance among the economic, environmental and safety objectives.
... It has been claimed in that work that heat integration might be avoided between units in geographical distance to generate realistic networks. The non-linear problem has been simplified to produce a bi-objective mixed integer linear programming and to determine optimal allocations of new process units while considering contradicting cost and risk functions (Martinez-Gomez et al., 2014). ...
A new approach is presented to determine optimal layout of facilities where toxic releases may occur in an existing or new facility. The land area is divided in equally sized rectangular grids, where each grid contains up to one facility surrounded by streets. Some facilities may produce hot and/or cold streams and the associated heat exchangers network (HEN) is simultaneously optimized with the layout problem. The three dimensions of geographical allocation points for each generated stream are included in the model. No additional cost for geographical allocation of heating and cooling services is considered since every facility is expected to contain these services regardless of their use in the HEN. The toxic effect is estimated via probit functions and its associated risk reduction results in providing safety to the combined HEN-facility layout problem. The grid-based allocation eliminates numerical difficulties appearing with conventional non-overlapping and Euclidian distance equations.
... Lira-Flores et al. (2013) implemented a mixed-integer nonlinear programming model for layout designs based on the domino hazard index. Martinez-Gomez et al. (2014) presented a multi objective optimization approach for the optimal sitting in industrial facilities. Medina-Herrera et al. (2014) reported a mathematical programming model for the optimal layout considering quantitative risk. ...
The risks in natural gas industries are perceived to be lower than in many upstream and downstream oil and gas operations, yet process safety incidents keep happening. Synergistic deployment of advanced process safety methods, technologies, strong safety management systems, and best‐in‐class safety culture can prevent future incidents. This chapter presents current status and advances in process safety related to hazard analysis, plant and equipment reliability, facility siting and layout optimization, relief systems design, toxic and heavy gas dispersions, fire and explosion, effective mitigation systems, and regulatory programs and management systems focusing on natural gas processing and liquefied natural gas (LNG) operations. Several outstanding process safety challenges are presented for further advancement in this area.
The facility layout problem is fundamental during the plant design. The solution of this problem has required strategies that become in numerical challenges. One of them is the exact method, which finds optimal distributions for facility layout, as demonstrated the linear and disjunctive models. Both models are distinguished by a high quantity of non-overlapping constraints. In contrast, a nonlinear model was formulated with low number of constraints, but it has been solved by genetic algorithms. Herein, that model is reformulated to a MINLP (mixed integer nonlinear programming) problem. The solution was possible by using a visual interface linked to GAMS (General Algebraic Modeling System). Three case studies were solved to compare them. The reformulated model reached feasible solutions, and its computational time and binary variables were lower than those of the others. This suggests that the reformulated model can be extended to solve topics about process safety.
In this manuscript a new phenomenon of adjacency and closeness rating is proposed for constructing the optimal facility layout design. In the proposed approach, the closeness rating is applied to every pair of neighboring departments in a range of their attached point up to a predefined distance between them. Also, while in the traditional approach the closeness rating is applied for determining either the proximity or farness of two departments, the proposed approach considers both the degree of closeness as the economical purposes, and farness as the safety purposes concurrently. A mathematical model is proposed for constructing the optimal layout design. For evaluating the efficiency and flexibility of the proposed model, a computational experiment is conducted. Through the results of this experiment, three major novelties of the proposed model such as its flexibility for concurrent consideration of the economic and the safety aspects of the layout design, its ability for constructing varieties of the layout designs, and a better implementation of adjacency among the neighboring department’s pairs during the designing processes are demonstrated.
In industrializing countries, the rapid population growth frequently tends to reach the vicinity of the industrial parks, yielding an imminent hazard to the residents in the case of the occurrence of an accident. In the case of Mexico, particularly in the city of Morelia, the industries associated to the vegetable oil and margarine, originally located far from the city, have been absorbed by the city due to the high population growth. It should be noticed that this industry represents a high hazard because it uses huge amounts of hydrogen and LP gas. Therefore, to determine the potential impact of an accident for the people within and around these industries, this paper presents a quantitative risk analysis applied to the vegetable oil refining industry in Morelia. The main objective is the identification of the facilities with the highest hazard, as well as the risk analysis to the personnel inside and the people leaving around the plant. According to the quantitative risk analysis, the hydrogen processing and storage units are the most dangerous facilities inside the plant. Moreover, the identified potential accidents were boiling liquid expanding vapor explosion, flash fire, jet fire, and vapor cloud explosion, which were evaluated through the software SCRI. Furthermore, an inherent approach was applied to propose alternatives for risk reduction.
A comprehensive overview of methods to quantify and limit risks arising from different sources is still missing in literature. Therefore, a study of risk literature was carried out by the authors. This article summarises about 25 quantitative risk measures. A risk measure is defined as a mathematical function of the probability of an event and the consequences of that event. The article focuses mainly on risk measures for loss of life (individual and societal risk) and economic risk, concentrating on risk measurement experiences in The Netherlands. Other types of consequences and some international practices are also considered. For every risk measure the most important characteristics are given: the mathematical formulation, the field of application and the standard set in this field. Some of the measures have been used in a case study to calculate the flood risks for an area in The Netherlands.
Over the last three decades the process industries have grown very rapidly, with corresponding increases in the quantities of hazardous materials in process, storage or transport. Plants have become larger and are often situated in or close to densely populated areas. Increased hazard of loss of life or property is continually highlighted with incidents such as Flixborough, Bhopal, Chernobyl, Three Mile Island, the Phillips 66 incident, and Piper Alpha to name but a few.The field of Loss Prevention is, and continues to, be of supreme importance to countless companies, municipalities and governments around the world, because of the trend for processing plants to become larger and often be situated in or close to densely populated areas, thus increasing the hazard of loss of life or property. This book is a detailed guidebook to defending against these, and many other, hazards. It could without exaggeration be referred to as the "bible" for the process industries. This is THE standard reference work for chemical and process engineering safety professionals. For years, it has been the most complete collection of information on the theory, practice, design elements, equipment, regulations and laws covering the field of process safety. An entire library of alternative books (and cross-referencing systems) would be needed to replace or improve upon it, but everything of importance to safety professionals, engineers and managers can be found in this all-encompassing reference instead. Frank Lees' world renowned work has been fully revised and expanded by a team of leading chemical and process engineers working under the guidance of one of the worldâ??s chief experts in this field. Sam Mannan is professor of chemical engineering at Texas A and M University, and heads the Mary Kay Oâ??Connor Process Safety Center at Texas A and M. He received his MS and Ph.D. in chemical engineering from the University of Oklahoma, and joined the chemical engineering department at Texas A and M University as a professor in 1997. He has over 20 years of experience as an engineer, working both in industry and academiaNew detail is added to chapters on fire safety, engineering, explosion hazards, analysis and suppression, and new appendices feature more recent disasters. The many thousands of references have been updated along with standards and codes of practice issued by authorities in the US, UK/Europe and internationally. In addition to all this, more regulatory relevance and case studies have been included in this edition. Written in a clear and concise style, Loss Prevention in the Process Industries covers traditional areas of personal safety as well as the more technological aspects and thus provides balanced and in-depth coverage of the whole field of safety and loss prevention.
Plant layout is concerned with the spatial arrangement of processing equipment, storage vessels and their interconnecting pipework. This is an important aspect in the design of chemical and process plants since a good layout will ensure that the plant functions correctly and will provide an economically acceptable balance between the many, often conflicting, design constraints. These constraints are derived from safety, environmental, construction, maintenance and operational considerations. Process relationships, for example the use of gravity flow, and issues such as the provision of space for future expansion must also be taken into account. Traditional methods for locating equipment within chemical plants are based on mixtures of process heuristic rules and exact-to-the-inch distance information. Such techniques are unsystematic and they do not make use of all the relevant and appropriate data. In this paper an optimization based approach is used to determine a good preliminary plant layout, subject to all of the above constraints. A novel mathematical formulation is presented which addresses the problem of locating items of equipment within a given two or three dimensional space. The objective function to be minimised is the sum of the relevant operation, connection and floor construction costs. Detailed cost factors ate used to account for the flow direction between two connected units. The problem is formulated as a mixed integer linear programming problem. Specific attention is paid to constructing a formulation which is suitable for the solution of large scale problems. The method presents the rigorous solution of problems with around 30 process equipment and of essentially unlimited size problems when combined with single heuristic rules. The approach is demonstrated with several practical scale problems, including an industrial multi-purpose plant.
Chemical processes are constructed within very compact areas in the consideration of limited resources, including land, although many of their units are dangerous and vulnerable to accidents. Even the safety among units is secured by modifying the layout of process to ensure the safety distance, this situation can get worse if the process site is near residential areas or the workspace of employees because of the risk to humans from the process. In this study, such risk to humans as well as the risk to the equipment itself are quantitatively considered to give more reliable layout of chemical processes. Modified individual risk index has been adopted, counting for the direct risk that a person near the dangerous equipment can take. With this index, optimal process layout is designed by minimization of cost and land area to consider the limitation of resources. The proposed methodology can provide a guideline to designing safe layout of a chemical process concerning the various safety distance measures including equipment–equipment distance, equipment–workspace distance, and equipment–public area distance.
A new approach for the incorporation of safety criteria into the selection, location, and sizing of a biorefinery is introduced. In addition to the techno-economic factors, risk metrics are used in the decision-making process by considering the cumulative risk associated with key stages of the life cycle of a biorefinery that includes biomass storage and transportation, process conversion into biofuels or bioproducts, and product storage. The fixed cost of the process along with the operating costs for transportation and processing as well as the value of the product are included. An optimization formulation is developed based on a superstructure that embeds potential supply chains of interest. The optimization program establishes the tradeoffs between cost and safety issues in the form of Pareto curves. A case study on bio-hydrogen production is solved to illustrate the merits of the proposed approach. © 2013 American Institute of Chemical Engineers AIChE J, 59: 2427–2434, 2013
Plant layout is concerned with the spatial arrangement of processing equipment, storage vessels and their interconnecting pipework. This is an important aspect in the design of chemical and process plants since a good layout will ensure that the plant functions correctly and will provide an economically acceptable balance between the many, often conflicting, design constraints. These constraints are derived from safety, environmental, construction, maintenance and operational considerations. Process relationships, for example the use of gravity flow, and issues such as the provision of space for future expansion must also be taken into account. Traditional methods for locating equipment within chemical plants are based on mixtures of process heuristic rules and exact-to-the-inch distance information. Such techniques are unsystematic and they do not make use of all the relevant and appropriate data. In this paper an optimization based approach is used to determine a good preliminary plant layout, subject to all of the above constraints. A novel mathematical formulation is presented which addresses the problem of locating items of equipment within a given two or three dimensional space. The objective function to be minimized is the sum of the relevant operation, connection and floor construction costs. Detailed cost factors are used to account for the flow direction between two connected units. The problem is formulated as a mixed integer linear programming problem. Specific attention is paid to constructing a formulation which is suitable for the solution of large scale problems. The method presents the rigorous solution of problems with around 30 process equipment and of essentially unlimited size problems when combined with single heuristic rules. The approach is demonstrated with several practical scale problems, including an industrial multi-purpose plant.
This paper presents a general mathematical programming model for the synthesis of distributed treatment systems for industrial effluents discharged to watersheds. In addition to addressing the economic and environmental concerns of the design, the paper introduces safety as an additional objective. A multi-objective optimization formulation is developed to simultaneously address and reconcile the various objectives. Material flow analysis (MFA) is used to track the flows and concentrations throughout the watershed system while accounting for the different sources (industrial, sanitary, agricultural, precipitation, etc.), extractions (agricultural, filtration, evaporation, etc.), and physical, biological, and chemical phenomena occurring within the watershed. Additionally, the formulation allows the installation of treatment systems for the industrial effluents. The economic, environmental, and safety aspects of these treatment units are incorporated. A case study with different scenarios for the Balsas watershed in Mexico is considered to show the applicability of the proposed approach.
The bicriterion formation of the two problems and the epsilon- constraint formulation viewing the identification problem as a constraint to the optimization problem are introduced. The equivalence theorem relating these two formulations is presented and proved.
Natural gas industry is developing rapidly, and its accidents are threatening the urban safety. Risk management through quantitative assessment has become an important way to improve the safety performance of the natural gas supply system. In this paper, an integrated quantitative risk analysis method for natural gas pipeline network is proposed. This method is composed of the probability assessment of accidents, the analysis of consequences and the evaluation of risk. It is noteworthy that the consequences analyzed here include those of the outside and inside gas pipelines. The analysis of consequences of the outside pipelines focuses on the individual risk and societal risk caused by different accidents, while those of the inside pipelines concerns about the risk of the economic loss because of the pressure re-distribution. Risk of a sample urban gas pipeline network is analyzed to demonstrate the presented method. The results show that this presented integrated quantitative risk analysis method for natural gas pipeline network can be used in practical application.
A new approach to determine the optimal distribution of process facilities is presented in this paper. The formulation considers a set of facilities already installed in a given land and a new set of facilities to be accommodated within the same land. In addition, it is considered that a set of facilities either installed or to be laid out presents the possibility of toxic release. Based on previous analysis, the worst-case scenario implies calm wind and stable atmospheric condition. Since these conditions tend to exist during several days of the year, the proposed model is formulated assuming these deterministic values for wind and atmospheric conditions. The final model is formulated as a disjunctive model that is converted into a mixed-integer non-linear program (MINLP) via the convex-hull method. The model is then solved with local and global optimizers in the GAMS package. Using the current approach based on minimum distances for a particular case study results in a distribution with a very high risk whereas the optimal results using this proposed approach indicate large separations between releasing facilities and the inhabited facilities due to the high toxicity of the released material. More elaboration will be aggregated into the developed model to include prevention and mitigation systems to produce more compact but optimal and safe layouts.
The present work is focused on developing a methodology to find the optimal placement of a hazardous process unit and other facilities using optimization theory while considering a risk map in the plant area. Incidents can have possible consequences resulting from flammable gas releases, which can be evaluated by using consequence modeling programs. The probability of each incident can be derived from initial leak hole size estimation through event tree analysis. In this methodology the plant area was divided into square grids and risk scores were estimated for each grid. The overall cost is a function of the probable cost of property damage due to fires or explosions and the interconnection cost including piping, cable, and management. The proposed approach uses a mixed integer linear optimization programming (MILP) that identifies attractive locations by minimizing the overall cost. A case study is presented for a hexane–heptane separation facility that considers the meteorological data for the given area in order to show the applicability of the proposed methodology. Results from this study will be useful in assisting the selection of locations for facilities and for risk management.
This paper presents mathematical programming models for the optimal process plant layout based on a continuous dimensional space. Two alternative formulations are proposed which can accommodate rectangular equipment footprints of arbitrary size. Then, one of the formulations is extended to account for a common designer objective: to organize the layout into well-defined production sections. All models are formulated as mixed-integer linear programming (MILP) problems which can be solved to global optimality by using commercial optimization software. The applicability of the proposed mathematical models is demonstrated by a number of illustrative examples.
The tragic accidents at Flixborough and Bhopal have led to the development of new legislation concerning the design and operation of chemical plants. In addition, the growing concern with safety and environmental issues places many new demands upon the designer. Process plant layout, as an important step in the design of chemical plants, is effected by these demands. This paper presents a new approach to process plant layout that integrates safety and economics. In this approach, the cost of a layout is a function of piping cost, land cost, financial risk, and protection devices cost. The financial risk term captures the risk of unsafe plants and can be expressed as the expected losses if major accidents happen (i.e., fires or explosions). The proposed approach is a mixed-integer nonlinear optimization problem (MINLP) that identifies attractive layouts by minimizing overall costs. This approach gives the coordinates of each unit, an estimate for the total piping length, the amount of land occupied, and the safety devices that have to be installed at each unit.
Accidents involving flammable materials often resulted in a fire or an explosion. In addition to property damages caused by fire/explosion, the concern about the potential of structural collapse on building occupants has become an increasingly emergent. The present work describes a new approach to optimizing facility siting and layout for flammable gas release scenarios, thereby minimizing the consequences of fire and explosion. This approach focuses on integrating quantitative risk analysis in the optimization formulation to obtain the optimal allocation of new facilities based on particular risk criteria derived from accident scenarios. Three different approaches to configure the optimal location of new facilities were used: fixed distance (recommended separation distance), optimized layout by considering the structural damage due to blast overpressures, and, finally, integration of the first two approaches with weighting factors to account for the risk to building occupants and the likelihood of the domino effect. The proposed approach was formulated as a mixed integer nonlinear program (MINLP) problem that determines safe locations of facilities by minimizing the overall cost. Furthermore, the proposed methodology was evaluated using a flame acceleration simulator (FLACS) to consider the congestion and confinement effects in the plant in order to provide substantial guidance for deciding the optimal layout. The outcome of this study can be used as a tool to assess a new or current layout of process plant buildings and to manage fire and explosion risks in the chemical process plant.
This paper presents a novel solution approach for addressing large-scale single-floor process plant layout problems. Based on the mixed-integer linear programming (MILP) representation proposed by Papageorgiou and Rotstein in 1998, the optimal layout (i.e., coordinates and dimensions) is determined through construction-based schemes using mixed-integer optimization. The applicability of the proposed approach is finally demonstrated through four illustrative examples by investigating flowsheets with up to 36 equipment items.
Geographic information systems (GIS) introduced here offer a source of information for problems with a geographic dimension, such as layout and environmental decision making. A mixed-integer linear-programming formulation of a chemical-plant layout problem was developed, and is presented along with an existing formulation. The effectiveness of these formulations is highly problem- and data-specific, and a combination of the two formulations can be derived that is more effective on certain problems than either formulation alone. The formulations are ineffective for some problems due to the highly redundant search space engendered by symmetries in the layout—symmetries that can be eliminated by a more careful analysis of the situation using location-specific information such as existing units and facilities, geographic constraints, wind, elevation, and soil conditions. Different classes of such information can be captured from a GIS and represented within the mixed-integer linear-programming formulation. Two cases studies presented illustrate the formulations and the use of geographic information for chemical-plant layout.
This paper presents a new methodology for determining suboptimum relative location patterns for physical facilities. It presents a computer program governed by an algorithm which determines how relative location patterns should be altered to obtain sequentially the most improved pattern with each change, commands their alteration, evaluates the results of alterations, and identifies the sub-optimum relative location patterns.3 The computer output yields a block diagramatic layout of the facility areas, and the areas need not be equal.4 A manufacturing plant layout example is used because the methodology is well illustrated by reference to some kind of example, and this one is commonly known. The methodology itself, however, is general in nature and not restricted to such applications.
Partitioning of units into multiple groups occurs naturally in multilevel plants where equipment must be distributed onto different floors, so as to minimize material flow costs. A significant complication introduced in multilevel layout is the dependence of the cost of material flows between units on the relative levels of the respective unit locations. This feature leads to three distinct costs for downward, upward and horizontal flow between any pair of units. In this paper, we formulate this problem as an Integer Non-Linear Program. A heuristic procedure proposed for the single floor graph partitioning problem in Part I of this work is extended to address this problem. Global optima were obtained for all examples for which the exact optimal solutions were obtainable by exhaustive enumeration. Solutions for problems with up to 70 units were obtained in reasonable computation times, suggesting applicability of the procedure to chemical plants of realistic scope. Additionally, a linearization scheme is used to convert the INLP to an MILP. Continuous relaxations of the MILP are solved by Lagrangean Relaxation and Subgradient Optimization to yield good lower bounds. It is demonstrated that the linearization is sufficiently tight that, for some problem instances, solutions to the continuous relaxation are optimal. In general, the combination of upper and lower bounding procedures is effective as a means of both obtaining good solutions and estimating the deviation from the optimal solution for problems of practical scope.
This paper presents a general mathematical programming formulation for the multi-floor process plant layout problem, which considers a number of cost and management/engineering drivers within the same framework thus resolving various trade-offs at an optimal manner. The proposed model determines simultaneously the number of floors, land area, floor allocation of each equipment item and detailed layout for each floor. The overall problem is formulated as a mixed integer linear programming (MILP) model based on a continuous domain representation. The applicability of the model is demonstrated by three illustrative examples.
This paper presents a new approach for the optimal facility siting considering the uncertainty of toxic release in one of the installed facilities. The proposed formulation incorporates the effect of wind speed, wind direction and atmospheric stability to calculate the risk of death via probit functions and Monte Carlo simulation. The overall problem is initially modeled as a disjunctive program where the Cartesian coordinates of each new facility for siting and cost-related variables are the main unknowns to determine. Then, the convex hull approach is used to reformulate the problem as a mixed integer nonlinear program (MINLP). The numerical difficulties are shown in a case study where multiple optimal layouts have been found. In general, the numerical results demonstrate the potential of this approach to improve the process layout design activity.
One of the problems in the layout of a chemical plant on a single floor is to divide the given set of equipment into sections (groups) of units that reflect the partitions created by aisles or corridors. This is to be accomplished while minimizing the inter-section flow magnitude/cost. By representing the equipment and their connectivities with an edge weighted graph, an analogy to the familiar graph partitioning problem is established. In this paper, a partition of the vertices into subsets of given sizes is sought so as to minimize the total weight of the edges joining vertices from different subsets. We propose a heuristic procedure that has given globally optimal solutions in attractive computation times to all random graphs studied for which the optimal partitions were obtainable by exhaustive enumeration. This paves the way for obtaining good quality and economical layouts for chemical plants of realistic scope. Extension to the multifloor chemical plant layout problem is discussed.
This paper presents a modelling framework for discrete optimization problems that relies on a logic representation in which mixed-integer logic is represented through disjunctions, and integer logic through propositions. It is shown that transformation of the logic formulation into the equation form is not always desirable, and that therefore there is a need to address the solution of mixed-integer programming problems where some of the mixed-integer relationships are expressed in disjunctions while others are expressed as algebraic constraints. A theoretical characterization of disjunctive constraints is proposed which can serve as a criterion for deciding whether a disjunction should be transformed into equation form. A solution algorithm that generalizes the method of Raman and Grossmann (Computers & Chemical Engineering, 17, 909, 1993) for handling mixed-integer disjunctions symbolically is also proposed. Several examples are presented to illustrate the proposed modelling framework and the potential of the solution method.
Risks of personal injury from gas explosion, together with fire and smoke ingress, were among the key hazards that the Eastern Trough Area Project (ETAP) team intended to design out as far as possible. This paper describes the process ETAP followed to achieve this. The process involved the early application of the appropriate advance technology and personnel at the concept selection stage and right through different stages during design, and an integrated team including explosion specialists.All major design decisions on explosion optimisation were made at the early stage of front-end engineering design (FEED), resulting in a relatively straightforward detailed design phase. These early design decisions had the effect of not only reducing gas explosion consequences, but simplifying layout, e.g. reducing pipe run and structures. The end result is a design which gives inherently low risk to personnel and Temporary Refuge impairment without the uncertainties of high cost of late remedial work to take account of high explosion loads, and consequent project delay.
The fundamentals of Inherently Safer Design were not fully appreciated in the initial design (or re-design) in the following series of case histories. Two case histories involving the basic element of plant layout to minimize property damages and injury will be covered first. Simple physical separation could have reduced the losses. A case history that occurred in a bulk chemical terminal tank farm will highlight designs which allowed incompatible chemicals to react, create a fire and a lingering toxic gas release. The combination of these chemicals caused equipment damage in one case and a threat to the public in another case. This paper will conclude with case histories involving poor piping design or poorly identified piping systems, which needlessly resulted in expensive repairs. Exercising the principles of inherent safety would have reduced the severity and perhaps the opportunity of these events. We must employ the techniques of inherent safety to improve our performance.
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