• Korean Journal of Computational Design and Engineering
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• v.21 no.4
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• pp.389-396
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• 2016

The necessity for environment-friendly material development has emerged in the recent automotive field due to stricter regulations on fuel economy and environmental concerns. Accordingly, the automotive industry is paying attention to carbon fiber reinforced plastic (CFRP) material with high strength and stiffness properties while the lightweight. In this study, we determine a shape of lower control arm (LCA) for maximizing the strength and stiffness by optimizing the thickness of each layer when the stacking angle is fixed due to the CFRP manufacturing problems. Composite materials are laminated in the order of $0^{\circ}$, $90^{\circ}$, $45^{\circ}$, and $-45^{\circ}$ with a symmetrical structure. For the approximate optimal design, we apply a sequential two-point diagonal quadratic approximate optimization (STDQAO) and use a process integrated design optimization (PIDO) code for this purpose. Based on the physical properties calculated within a predetermined range of laminate thickness, we perform the FEM analysis and verify whether it satisfies the load and stiffness conditions or not. These processes are repeated for successive improved objective function. Optimized CFRP LCA has the equivalent stiffness and strength with light weight structure when compared to conventional aluminum design.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.1
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• pp.113-124
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• 2008

Distributed operation of overall structural design process, by which product optimization and process parallelization are simultaneously implemented, is presented in this paper. The database-interacted hybrid method, which selectively takes the accustomed procedure of the conventional method in the framework of the optimal design, is utilized here. The staged application of design constraints reduces the computational burden for large complex optimization problems. Two kinds of numeric and graphic processes are simultaneously implemented by concurrent engineering approach in the distributed environment of PC networks. The former is based on finite element optimization method and the latter is represented by AutoCAD using AutoLISP programming language. Numerical computation and database interaction on servers and graphic works on independent clients are communicated through message passing. The numerical experiments for some steel truss models show the validity and usability of the method. This study has sufficient adaptability and expandability, in that it is based on general methodologies and industry standard platforms.

• Composites Research
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• v.21 no.1
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• pp.30-39
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• 2008

In this paper, a parallel micro genetic algorithm was utilized in the optimal design of composite structures instead of a conventional genetic algorithm(SGA). Micro genetic algorithm searches the optimal design variables with only 5 individuals. The diversities from the nominal convergence and the re-initialization processes make micro genetic algorithm to find out the optimums with such a small population size. Two different composite structure optimization problems were proposed to confirm the efficiency of micro genetic algorithm compared with SGA. The results showed that micro genetic algorithm can get the solutions of the same level of SGA while reducing the calculation costs up to 70% of SGA. The composite laminated structure optimization under the load uncertainty was conducted using micro genetic algorithm. The result revealed that the design variables regarding the load uncertainty are less sensitive to load variation than that of fixed applied load. From the above-mentioned results, we confirmed micro genetic algorithm as a optimization method of composite structures is efficient.

• Korean Chemical Engineering Research
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• v.46 no.3
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• pp.610-618
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• 2008

It is not easy to compare the treatment processes and find an optimum operating condition by the experiments due to influent conditions, treatment processes, various operational conditions and complex factors in real wastewater treatment system and also need a lot of time and costs. In this paper, the activated sludge models are applied to four principal biological wastewater treatment processes, $A_2O$(anaerobic/anoxic/oxic process), Bardenpho(4 steps), VIP(Virginia Initiative Plant) and UCT(University of Cape Town), and are used to compare their environmental and economic assessment for four key processes. In order to evaluate each processes, a new assessment index which can compare the efficiency of treatment performances in various processes is proposed, which considers both environmental and economic cost. It shows that the proposed index can be used to select the optimum processes among the candidate treatment processes as well as to find the optimum condition in each process. And it can find the change of economic and environmental index under the changes of influent flowrate and aerobic reaction size and predict the optimum index under various operation conditions.

• Korean Chemical Engineering Research
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• v.46 no.3
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• pp.585-597
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• 2008

The aim of this study was to find an analytic solution to the problem of determining the optimal capacity (lot-size) of a batch-storage network to meet demand for a finished product in a system undergoing random failures of operating time and/or batch material. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to short-term random variations in the cycle time and batch size as well as long-term variations in the average trend. Some of the production processes have random variations in product quantity. The spoiled materials are treated through regeneration or waste disposal processes. All other processes have random variations only in the cycle time. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis, the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.1-12
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• 2016

The current economic crisis is making new demands on manufacturing industry, in particular, in terms of the flexibility and efficiency of production processes. This requires production and administrative processes to be meshed with each other by means of IT systems to optimise the use and capacity utilisation of machines and lines but also to be able to respond rapidly to wrong developments in production and thus to minimise adverse impacts on the business. The future scenario of the "smart factory" represents the zenith of this development. The factory can be modified and expanded at will, combines all components from different manufacturers and enables them to take on context-related tasks autonomously. Integrated user interfaces will still be required at most for basic functionalities. The complex control operations will run wirelessly and ad hoc via mobile terminals such as PDAs or smartphones. The comnination of IoT, and Big Data optimisation is bringing about huge opportunities. these processes are not just limited to manufacturing, anywhere a supply chain environment exists can benefit from information provided by linked devices and access to big data to inform their decision support. Building a smart factory with smart assets at its core means reaching those desired new levels of productivity and efficiency. It means smart products that leverage advanced traceability, connectivity and intelligence. For businesses, it means being able to address the talent crunch through more autonomous. In a Smart Factory, machinery and equipment will have the ability to improve processes through self-optimization and autonomous decision-making.

• Clean Technology
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• v.11 no.4
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• pp.165-170
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• 2005

The aim of this study is to provide vapor-liquid equilibrium (VLE) information for the study of process which directly synthesize dimethyl carbonate (DMC) from $CO_2$. For this study we collected some necessary VLE systems data of Methanol-Water, Methanol-DMC, $CO_2$-DMC, $CO_2$-Methanol, $CO_2$-Methanol, and performed VLE calculation with Peng-Robinson equation of state, Wong-Sandler mixing rules that widely used in chemical industry. These calculation results relatively agreed with VLE data well. Optimized Parameters of EoS given through this calculation will be used as some valuable information for fundamental study, process development and process optimization of DMC direct synthesis.

• Korean Chemical Engineering Research
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• v.45 no.3
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• pp.234-241
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• 2007

To achieve safe operation and to improve economics it is imperative to monitor and analyse demand and supply of utilities and to meet utility needs in time. The main objective of motor/turbine processes is to manipulate steam and electricity balances in utility plants. The optimal operation of motor/turbine processes is by far the most important to improve economics in the utility plant. In order to analyse motor/turbine processes, we need steady state models for steam generation equipments and steam distribution devices as well as turbine generators. In addition heuristics concerning various operational situations are required. The motor/turbine optimal operation system is based on utility models and operational knowledgebase and provides optimal operating conditions when the amount of steam demand from various steam headers is changed frequently. The optimal operation system also produces optimal selection of driving devices for utility pumps to reduce operating cost.

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

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.326-354
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• 2014

In this paper, a new green clustering algorithm is proposed to be as a first approach in the framework of an energy efficient strategy for centralized enterprise high-density WLANs. Traditionally, in order to maintain the network coverage, all the APs within the WLAN have to be powered-on. Nevertheless, the new algorithm can power-off a large proportion of APs while the coverage is maintained as its always-on counterpart. The two main components of the new approach are the faster procedure based on K-means and the more accurate procedure based on Evolutionary Algorithm (EA), respectively. The two procedures are processes in parallel for different designed requirements and there is information interaction in between. In order to implement the new algorithm, EA is applied to handle the optimization of multiple objectives. Moreover, we adapt the method for selection and recombination, and then introduce a new operator for mutation. This paper also presents simulations in scenarios modeled with ray-tracing method and FDTD technique, and the results show that about 67% to 90% of energy consumption can be saved while it is able to maintain the original network coverage during periods when few users are online or the traffic load is low.