• Journal of Korean Society for Quality Management
• /
• v.34 no.2
• /
• pp.12-21
• /
• 2006

This paper considers the problem of selecting the most profitable process mean for production processes where measurement errors exist in inspection systems. For such situations, a sequential inspection procedure is proposed to reduce measurement errors. The decision to accept, reject, or take an additional inspection of an item is made at every measurement point until the number of repeated measurements reaches its upper bound. An expected profit model is constructed and the optimal process mean, the cut-off values, and the upper bound of the number of repeated measurements are obtained when accepted(rejected) items are sold at regular(reduced) price. A numerical study is performed to investigate the performance of the proposed procedure.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.19 no.5
• /
• pp.27-37
• /
• 2020

Structural optimization problems with discrete design variables require more function calculations (or finite element analyses) than those in the continuous design space. In this study, a method to find an optimal solution in the discrete design of the truss structure is presented, reducing the number of function calculations. Because a continuous optimal solution is the Karush-Kuhn-Tucker point that satisfies the optimality condition, it is assumed that the discrete optimal solution is around the continuous optimum. Then, response values such as weight, displacement, and stress are predicted using approximate models-referred to as hybrid metamodels-within specified design ranges. The discrete design method using the hybrid metamodels is used as a post-process of the continuous optimization process. Standard truss design problems of 10-bar, 25-bar, 15-bar, and 52-bar are solved to show the usefulness of this method. The results are compared with those of existing methods.

• Journal of Korean Society of Water and Wastewater
• /
• v.14 no.1
• /
• pp.76-83
• /
• 2000

This research is about wastewater containing non-biodegradable TDI(Toluene Diisocyanate) that is treated by the activated carbon adsorption method. In the case of the Fenton oxidation process being applied to the existing process, optimal pH, reaction time, chemical dosing amount, removal rate, and cost were investigated. A pilot plant test was applied after finding optimal conditions with lab experiments. The optimal conditions were pH 3~5(COD removal rate 84~88%) and reaction time 30min~1hr. In higher $H_2O_2$ dosing amount, COD removal rate was a little higher. But there was little difference in the removal rate according to $FeSO_4{\cdot}7H_2O$ dosing amount. Treatment cost was economical in the case of the Fenton oxidation process being operated earlier than activated carbon adsorption system. But chemical dosing point, chemical mixing effect, chemical dosing amount, removal rate, and the cost of facility and others must be considered in practical process.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.16 no.1
• /
• pp.76-88
• /
• 1991

Stochastic convexity (concavity) of a stochastic process is a very useful concept for various stochastic optimization problems. In this study we first establish stochastic convexity of a certain class of Markov additive processes through probabilistic construction based on the sample path approach. A Markov additive process is abtained by integrating a functional of the underlying Markov process with respect to time, and its stochastic convexity can be utilized to provide efficient methods for optimal design or optimal operation schedule wide range of stochastic systems. We also clarify the conditions for stochastic monotonicity of the Markov process. From the result it is shown that stachstic convexity can be used for the analysis of probabilitic models based on birth and death processes, which have very wide applications area. Finally we demonstrate the validity and usefulness of the theoretical results by developing efficient methods for the optimal replacement scheduling based on the stochastic convexity property.

• Journal of Korean Institute of Industrial Engineers
• /
• v.40 no.2
• /
• pp.233-239
• /
• 2014

This paper presents an extended EMQ model which determines an optimal production run length in an deteriorating production process. The production process is subject to a random deterioration from an in-control state to an out-of-control state and thus producing some proportion of defective items. Defective items produced are re-processed in the rework process to convert them into non-defectives. Through the mathematical modeling, an optimal solution minimizing the average cost per unit time as well as minimum average cost are derived. Numerical experiment is carried out to examine the behavior of the proposed model depending on model parameters.

• Korean Journal of Chemical Engineering
• /
• v.36 no.3
• /
• pp.356-367
• /
• 2019

This work presents an advanced and systematic approach to analytically design the optimal parameters of a two parameter second-order internal model control (IMC) filter that satisfies operational constraints on the output process, the manipulated variable as well as rate of change of the manipulated variable, for a first-order plus dead time (FOPDT) process. The IMC parameters are designed to minimize a control objective function composed of the weighted sum of the error between the process variable and the set point, and the rate of change of the manipulated variable, and to satisfy the desired constraints. The feasible region of the constrained IMC control parameters was graphically analyzed, as the process parameters and the constraints varied. The resulting constrained IMC control parameters were also used to find the corresponding industrial proportional-integral controller parameters of a Smith predictor structure.

• IE interfaces
• /
• v.17 no.4
• /
• pp.414-425
• /
• 2004

This study presents the decision of priority for optimal design guide to improve disassembly process. Disassembly process is divided into recognition, transfer and disassembly of assembly point and recognition, transfer and remove of grasp point. Significant influential factors are derived from analyzing the above process. And those factors are used for making the check list to evaluate the properties of parts in each process. Furthermore, the weight with considering disassembly process is also used to determine weight of each process. On the base of the above sequence, qualitative score of disassemblability of each process that is enabled to compare different disassembly processes can be acquired. Ultimately the score helps to decide the priority of design guide for disassembly process.

• Journal of Korean Society of Water and Wastewater
• /
• v.19 no.6
• /
• pp.781-790
• /
• 2005

Granular Activated Carbon(GAC) is widely used in drinking water treatment. Many of the problems occurring in the GAC process are associated with the operation goal and performance. The purpose of this study were to evaluate the design, operation, and performance of granular activated carbon process in D water treatment plant. The optimal operation conditions of GAC process such as backwashing condition, granular activated carbon replacement time were discussed. The design, operation and performance of GAC process is influenced by their raw water characteristics and placement within the treatment process sequence. A critical analysis of plants experience and the information from the literature identifies the effectiveness of GAC process and indicates where modifications in design and operation could lead to improved performance. It would be useful to evaluate and optimize the GAC process in other treatment plant.

• Journal of information and communication convergence engineering
• /
• v.15 no.2
• /
• pp.79-84
• /
• 2017

In a cognitive radio network (CRN), cognitive radio users (CUs) should be powered by a small battery for their operations. The operations of the CU often include spectrum sensing and data transmission. The spectrum sensing process may help the CU avoid a collision with the primary user (PU) and may save the energy that is wasted in transmitting data when the PU is present. However, in a time-slotted manner, the sensing process consumes energy and reduces the time for transmitting data, which degrades the achieved throughput of the CRN. Subsequently, the sensing process does not always offer an advantage in regards to throughput to the CRN. In this paper, we propose a scheme to find an optimal policy (i.e., perform spectrum sensing before transmitting data or transmit data without the sensing process) for maximizing the achieved throughput of the CRN. In the proposed scheme, the data collection period is considered as the main factor effecting on the optimal policy. Simulation results show the advantages of the optimal policy.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.04a
• /
• pp.1038-1043
• /
• 1997

To adapt the neural network proess for the purpose of determination of optimal utting onditions (optimal cutting speed and feed rate), some selection strategies for the machining factors are necessary, which is considered planning cutting process. In this case, factors that have both nonlinearity and strong relationship must be selected. Although tool grade and chemical properties of workpiece material have strong effect to cutting speed, it's not easy to find a analytic relation between them. In this paper, a mathematical method for determining the optimal amount of cutting (depth of cut, feed rate) is presented by tool goemetry and heat generation during cutting process. And various tool grade and workpiece material groups ase classified based on its chemical properties. Thier chemical composition and hardness are used as input pattern for neural network learnig. The result of learning shows the relationship between tool grade and workpiece material and it is proved that it can be used as a sub-system for automatic process planning system.