• Journal of the Korean Society of Safety
• /
• v.35 no.1
• /
• pp.25-33
• /
• 2020

In most plant layout optimization researches, MILP(Mixed Integer Linear Programming) problems, in which the objective function includes the costs of pipelines connecting process equipment and cost associated with safety issues, have been employed. Based on these MILP problems, various optimization solvers have been applied to investigate the optimal solutions. To consider safety issues on the objective function of MILP problems together, the accurate information about the impact and the frequency of potential accidents in a plant should be required to evaluate the safety issues. However, it is really impossible to obtain accurate information about potential accidents and this limitation may reduce the reliability of a plant layout problem. Moreover, in real industries such as plant engineering companies, the plant layout is previously fixed and the considerations of various safety instruments and systems have been performed to guarantee the plant safety. To reflect these situations, the two step optimization problems have been designed in this study. The first MILP model aims to minimize the costs of pipelines and the land size as complying sufficient spaces for the maintenance and safety. After the plant layout is determined by the first MILP model, the optimal locations of blast walls have been investigated to maximize the mitigation impacts of blast walls. The particle swarm optimization technique, which is one of the representative sampling approaches, is employed throughout the consideration of the characteristics of MILP models in this study. The ethylene oxide plant is tested to verify the efficacy of the proposed model.

• Journal of the Society of Naval Architects of Korea
• /
• v.52 no.1
• /
• pp.77-87
• /
• 2015

For a floating offshore plant such as FPSO(Floating, Production, Storage, and Off-loading unit), various equipment should be installed in the restricted space, as compared with an onshore plant. The requirement for an optimal layout method of the plant has been increased in these days. Thus, a layout method of the floating offshore plant was proposed in this study. For this, an optimization problem for layout design was mathematically formulated, and then an optimization algorithm based on the genetic algorithm was implemented with C++ language in order to solve it. Finally, the proposed method was applied to an example of FPSO topsides. As a result, it was shown that the proposed method can be applied to layout design of the floating offshore plant such as FPSO.

• Journal of the Korean Society of Safety
• /
• v.30 no.3
• /
• pp.32-37
• /
• 2015

In the fields of plant layout optimization, the main goal is to minimize the construction cost including pipelines as satisfying all constraints such as safety and operating issues. However, what is the lacking of considerations in previous researches is to consider proper safety and maintenance spaces for a complex plant. Based on the mathematical programming, MILP(Mixed Integer Linear Programming) problems including various constraints can be formulated to find the optimal solution which is to achieve the best economic benefits. The objective function of this problem is the sum of piping cost, pumping cost and area cost. In general, many conventional optimization solvers are used to find a MILP problem. However, it is really hard to solve this problem due to complex inequality and equality constraints, since it is impossible to use the derivatives of objective functions and constraints. To resolve this problem, the PSO (Particle Swarm Optimization), which is one of the representative sampling approaches and does not need to use derivatives of equations, is employed to find the optimal solution considering various complex constraints in this study. The EO (Ethylene Oxide) plant is tested to verify the efficacy of the proposed method.

• Korean Chemical Engineering Research
• /
• v.57 no.1
• /
• pp.51-57
• /
• 2019

A plant layout problem has a large impact on the overall construction cost of a plant. When determining a plant layout, various constraints associating with safety, environment, sufficient maintenance area, passages for workers, etc have to be considered together. In general plant layout problems, the main goal is to minimize the length of piping connecting equipments as satisfying various constraints. Since the process may suffer from the heat and friction loss, the piping length between equipments should be shorter. This problem can be represented by the mathematical formulation and the optimal solutions can be investigated by an optimization solver. General researches have overlooked many constraints such as maintenance spaces and safety distances between equipments. And, previous researches have tested benchmark processes. What the lack of general researches is that there is no realistic comparison. In this study, the plant layout of a real industrial C3MR (Propane precooling Mixed Refrigerant) process is studied. A MILP (Mixed Integer Linear Programming) including various constraints is developed. To avoid the violation of constraints, penalty functions are introduced. However, conventional optimization solvers handling the derivatives of an objective functions can not solve this problem due to the complexities of equations. Therefore, the PSO (Particle Swarm Optimization), which investigate an optimal solutions without differential equations, is selected to solve this problem. The results show that a proposed method contributes to saving the capital expenditures.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.17 no.12
• /
• pp.3063-3072
• /
• 1993

The layout is an important and difficult problem in industrial applications like sheet metal manufacturing, garment making, circuit layout, plant layout, and land development. The module layout problem is known to be non-deterministic polynomial time complete(NP-complete). To efficiently find an optimal layout from a large number of candidate layout configuration a heuristic algorithm could be used. In recent years, a number of researchers have investigated the combinatorial optimization problems by using neural network principles such as traveling salesman problem, placement and routing in circuit design. This paper describes the application of Self-organizing Feature Maps(SOM) of the Kohonen network and Simulated Annealing Algorithm(SAA) to the layout problem of the two-dimensional rectangular shapes.

• Korean Chemical Engineering Research
• /
• v.52 no.4
• /
• pp.475-480
• /
• 2014

In the fields of researches associated with plant layout optimization, the main goal is to minimize the costs of pipelines for connecting equipment. However, what is the lacking of considerations in previous researches is to handle the multi floor processes considering the safety distances for domino impacts on a complex plant. The mathematical programming formulation can be transformed into MILP (Mixed Integer Linear Programming) problems as considering safety distances, maintenance spaces, and economic benefits for solving the multi-floor plant layout problem. The objective function of this problem is to minimize piping costs connecting facilities in the process. However, it is really hard to solve this problem due to complex unequality or equality constraints such as sufficient spaces for the maintenance and passages, meaning that there are many conditional statements in the objective function. Thus, it is impossible to solve this problem with conventional optimization solvers using the derivatives of objective function. In this study, the PSO (Particle Swarm Optimization) technique, which is one of the representative sampling approaches, is employed to find the optimal solution considering various constraints. The EO (Ethylene Oxide) plant is illustrated to verify the efficacy of the proposed method.

• Journal of the Society of Naval Architects of Korea
• /
• v.49 no.1
• /
• pp.68-78
• /
• 2012

A layout of an LNG FPSO should be elaborately determined as compared with that of an onshore plant because many topside process systems are installed on the limited area; the deck of the LNG FPSO. Especially, the layout should be made as multi-deck, not single-deck and have a minimum area. In this study, a multi-floor layout for the liquefaction process, the dual mixed refrigerant(DMR) cycle, of LNG FPSO was determined by using the optimization technique. For this, an optimization problem for the multi-floor layout was mathematically formulated. The problem consists of 589 design variables representing the positions of topside process systems, 125 equality constraints and 2,315 inequality constraints representing limitations on the layout of them, and an objective function representing the total layout cost. To solve the problem, a hybrid optimization method that consists of the genetic algorithm(GA) and sequential quadratic programming(SQP) was used in this study. As a result, we can obtain a multi-floor layout for the liquefaction process of the LNG FPSO which satisfies all constraints related to limitations on the layout.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2003.06a
• /
• pp.890-894
• /
• 2003

This paper discuss basic functional construction and plant layout of a ELV dismantling system that can maximize the reusability of tarts and the recoverability of materials by dismantling ELV rationally and efficiently. "Island" type was selected for the system configuration considering processing amount, economical efficiency, and effectiveness. The system is supported by the information system, and composed of dismantling stations and handling equipments. The layout of the stations was determined after simulation and optimization using commercial software package, Arena and OptQuest. The objective of the optimization was maximum profit while the system capacity is considered as constraint. The environmental load of ELV can be minimized when the composition and function of each station are embodied in detail and the system is interfaced with shredding operation.

• Journal of Biosystems Engineering
• /
• v.11 no.2
• /
• pp.66-75
• /
• 1986

In order to improve the traditional post harvest system in Korea, a model for mechanized grain drying and storage facilities was developed. Also, a computer program for the model system was developed. For the study, flat type steel bin and circulation type dryer were selected for the model and Fortran language was used for the computer program. This program was tested by using various practical data. The following results were obtained from the study: 1. The general model developed can be used for designing a rough rice drying and storage facility within the range from 100 ton to 1000 ton capacity. 2. Major output of the computer program for designing a model system were as follow; a. The dimension of the plant. b. The storage bin size, dryer number and dryer size. c. The dimension of individual equipment and its required HP. d. Capital requirement and operating cost of the model system.

• Journal of Welding and Joining
• /
• v.30 no.4
• /
• pp.44-48
• /
• 2012

H-beam used for stiffening the upper structure of ocean plant is cut in the various shapes. The cutting process of the H-beam is done manually and requires a long time and high cost. Therefore, automation of H-beam cutting is an important task. This research aims to develop a 3-D simulator to build the automatic H-beam cutting system and to determine the optimal cutting method. The automatic H-beam cutting system composes of 6 robots including 2 cutting robots hang to a crane and 1 conveyer. The appropriate system layout for covering the various sizes and types of H-beam was tested and determined using the simulator. The H-beam cutting system uses a hybrid type of plasma and gas cutting because of special cutting shapes of H-beam. The cutting area of each cutting method should be properly divided according to the size and shape of H-beam to shorten the total cutting time. Additionally the collision between a robot and a robot or a robot and H-beam should be avoided. The optimal cutting method for the shortest cutting time without the collision could be found for the various cutting conditions by use of the simulator. 2 simulation samples shows the availability of the simulator to find the optimal cutting method.