An Ant Colony Optimization Algorithm(ACO) is one of the frequently used algorithms to solve the Traveling Salesman Problem(TSP). Since the ACO searches for the optimal value by updating the pheromone, it is difficult to consider the distance between the nodes and other variables other than the amount of the pheromone. In this study, fuzzy logic is added to ACO, which can help in making decision with multiple variables. The improved algorithm improves computation complexity and increases computation time when other variables besides distance and pheromone are added. Therefore, using the algorithm improved by the fuzzy logic, it is possible to solve TSP with many variables accurately and quickly. Existing ACO have been applied only to pheromone as a criterion for decision making, and other variables are excluded. However, when applying the fuzzy logic, it is possible to apply the algorithm to various situations because it is easy to judge which way is safe and fast by not only searching for the road but also adding other variables such as accident risk and road congestion. Adding a variable to an existing algorithm, it takes a long time to calculate each corresponding variable. However, when the improved algorithm is used, the result of calculating the fuzzy logic reduces the computation time to obtain the optimum value.

Meta-heuristic algorithms have been developed to efficiently solve difficult problems and obtain a global optimal solution. A common feature mimics phenomenon occurring in nature and reliably improves the solution through repetition. And at the same time, the probability is used to deviate from the regional optimal solution and approach the global optimal solution. This study compares the algorithm created based on the above common points with existed SA and HS to show advantages in time and accuracy of results. Existing algorithms have problems of low accuracy, high memory, long runtime, and ignorance. In a two-variable polynomial, the existing algorithms show that the memory increases and the accuracy decrease. In order to improve the accuracy, the new algorithm increases the number of initial inputs and increases the efficiency of the search by introducing a direction using vectors. And, in order to solve the optimization problem, the results of the last experiment were learned to show the learning effect in the next experiment. The new algorithm found a solution in a short time under the experimental conditions of long iteration counts using a two-variable polynomial and showed high accuracy. And, it shows that the learning effect is effective in repeated experiments.

It is one of the known methods to obtain the optimal solution using the Ant Colony Optimization Algorithm for the Traveling Salesman Problem (TSP), which is a combination optimization problem. In this paper, we solve the TSP problem by proposing an improved new ant colony optimization algorithm that combines genetic algorithm mutations in existing ant colony optimization algorithms to solve TSP problems in many cities. The new ant colony optimization algorithm provides the opportunity to move easily fall on the issue of developing local optimum values of the existing ant colony optimization algorithm to global optimum value through a new path through mutation. The new path will update the pheromone through an ant colony optimization algorithm. The renewed new pheromone serves to derive the global optimal value from what could have fallen to the local optimal value. Experimental results show that the existing algorithms and the new algorithms are superior to those of existing algorithms in the search for optimum values of newly improved algorithms.

This paper develops an algorithm to determine the batch size of the batch process in real time for improving production and efficient control of production system with multiple processes and batch processes. It is so important to find the batch size of the batch process, because the variability arising from the batch process in the production system affects the capacity of the production. Specifically, batch size could change system efficiency such as throughput, WIP (Work In Process) in production system, batch formation time and so on. In order to improve the system variability and productivity, real time batch size determined by considering the preparation time and batch formation time according to the number of operation of the batch process. The purpose of the study is to control the WIP by applying CONWIP production system method in the production line and implements an algorithm for a real time batch size decision in a batch process that requires long work preparation time and affects system efficiency. In order to verify the efficiency of the developed algorithm that determine the batch size in a real time, an existed production system with fixed the batch size will be implemented first and determines that batch size in real time considering WIP in queue and average lead time in the current system. To comparing the efficiency of a system with a fixed batch size and a system that determines a batch size in real time, the results are analyzed using three evaluation indexes of lead time, throughput, and average WIP of the queue.

This paper seeks to present a multi-control method that can contribute to effective control of the production line with multiple bottleneck processes. The multi-control method is the production system that complements shortcomings of CONWIP and DBR, and it is designed to determine the raw material input according to the WIP level of two bottleneck processes and WIP level of total process. The effectiveness of the production system developed by applying the multi-control method was verified by the following three procedures. Raw material input conditions of the multi-control method are as follows. First, raw materials are go into the production line when the number of the total process WIP is lower than established number of WIP in total process and first process is idle. Second, raw materials are introduced when the number of WIP of two bottleneck processes is lower than the established number of WIP of each bottleneck process. Third, raw materials are introduced when the first process and in front of bottleneck process are idle even if the number of WIP in the total process is less than established number of WIP of the total process. The production line with two bottleneck processes was selected as the condition for production environment, and the production process modeling of CONWIP, DBR and multi-control production method was defined according to the production condition. And the optimum limited WIP level suitable for each system was obtained by applying a genetic algorithm to determine the total limited number of WIP of CONWIP, the limited number of WIP of DBR bottleneck process, the number of WIP in the total process of multi-control method and the limited number of WIP of bottleneck process. The limited number of WIP of CONWIP, DBR and multi-control method obtained by the genetic algorithm were applied to ARENA modeling, which is simulation software, and a simulation was conducted to derive result values on the basis of three criteria such as production volume, lead time and number of goods in-progress.

This research focused on deciding optimal manufacturing WIP (Work-In-Process) limit for a small production system. Reducing WIP leads to stable capacity, better manufacturing flow and decrease inventory. WIP is the one of the important issue, since it can affect manufacturing area, like productivity and line efficiency and bottlenecks in manufacturing process. Several approaches implemented in this research. First, two strategies applied to decide WIP limit. One is roulette wheel selection and the other one is elite strategy. Second, for each strategy, JIT (Just In Time), CONWIP (Constant WIP), Gated Max WIP System and CWIPL (Critical WIP Loops) system applied to find a best material flow mechanism. Therefore, pull control system is preferred to control production line efficiently. In the production line, the WIP limit has been decided based on mathematical models or expert’s decision. However, due to the complexity of the process or increase of the variables, it is difficult to obtain optimal WIP limit. To obtain an optimal WIP limit, GA applied in each material control system. When evaluating the performance of the result, fitness function is used by reflecting WIP parameter. Elite strategy showed better performance than roulette wheel selection when evaluating fitness value. Elite strategy reach to the optimal WIP limit faster than roulette wheel selection and generation time is short. For this reason, this study proposes a fast and reliable method for determining the WIP level by applying genetic algorithm to pull system based production process. This research showed that this method could be applied to a more complex production system.

In this research, technology innovation capability evaluation model for small and medium enterprises was developed. To develop technology innovation capability evaluation model, two analytic technic was used. First one is AHP (Analytic Hierarchy Process) to give weight to each main index. Second one is fuzzy set theory to represent ambiguous index to numerical value. Finally, technology innovation capability evaluation model was achieved in combination with the same weight to AHP analysis and fuzzy set theory. With these results, small and medium enterprises can know important point in terms of strengthening the innovation capability evaluation.

본 연구는 대구경북의 중소기업을 대상으로 전략유형과 성과관리시스템이 경영성과에 미치는 영향에 대한 연구를 통해 중소기업에 적합한 전략유형을 알아보고 그에 맞는 성과관리시스템의 설계를 통해 기업의 경영성과를 개선하고자 하였다. 연구결과 전략유형 중에서 기술혁신형과 생산중점형은 경영성과에 유의적인 영향을 미치는 것으로 나타났으며, 성과관리시스템은 재무적성과와 비재무적성과에 부분적으로 영향을 미치는 것으로 나타났다. 또한 전략유형과 성과관리시스템의 상호작용은 기술혁신형 기업의 경영성과에 유의적인 영향을 미치는 것으로 나타났다. 이러한 결과는 중소기업들이 전략유형에 맞는 성과관리시스템의 구축을 통해 경영성과를 향상 시킬 수 있음을 지지하고, 이를 통해 기업들은 자원의 제약과 무한 경쟁을 이겨내고 지속적인 성장을 할 수 있을 것으로 보인다.

Supply Chain Management(SCM) is getting important, because size of the company is getting bigger and the kinds of product are various. In the case of manufacturing corporation, for the optimization of SCM, we have to make production and distribution plan by considering the various fluctuation in the aspect of integration. In this paper, first, It proposed the reasonable operational way of the SCM about when the customer’s demanding is various and demanding expectation fluctuates in capacity standardization of producer stage. Second, the paper proposed the management way for demanding by considering confirmed demanding information, related inventory expense and demanding shortage expense when we make production and distribution plan. The paper applied the genetic algorithm proved for current usefulness. it proposed the optimal operational way for SCM by dividing into 2 ways for dealing with the duration of confirmed demanding information and various fluctuation.

This study develops a dynamic scheduling model for parallel machine scheduling problem based on genetic algorithm (GA). GA combined with discrete event simulation to minimize the makespan and verifies the effectiveness of the developed model. This research consists of two stages. In the first stage, work sequence will be generated using GA, and the second stage developed work schedule applied to a real work area to verify that it could be executed in real work environment and remove the overlapping work, which causes bottleneck and long lead time. If not, go back to the first stage and develop another schedule until satisfied. Small size problem was experimented and suggested a reasonable schedule within limited resources. As a result of this research, work efficiency is increased, cycle time is decreased, and due date is satisfied within existed resources.

When developing a product, ensuring the quality and reliability is essential. Reliability process is always underestimated compared to its importance, especially in the field of domestic medical devices. In this paper, reliability process developed for near-infrared solid microscope, based on a variety of existing practices and other product process. The following findings were obtained as research progressed. First, learning about the medical equipment needed to assure the quality and reliability standards. Second, reliability process established to design a product in the field of medical devices

Cleanroom could be largely classified into industrial cleanroom that can be contaminated by particles and bio-cleanroom that can be contaminated by biological particles. Electrical manufacturing companies producing precision machines and electrical parts essentially have industrial cleanroom facilities and clean technologies to produce defects free products due to particles. Industrial cleanroom should be controlled in respect of 4M1E to prevent from foreign materials of sub-micro unit and to keep out contamination sources from outside. In this paper, a concept for a quantitative methodology to measure the particles from running components was suggested by combining both newly making clean booth such as wear tester and laser particle counter.

Ensure the quality and reliability of the developing product should be considered essential. Reliability process is lacking compared to its importance, especially in the field of domestic medical devices. In this paper is Reliability process formulation ofnear-infrared solid microscope for ophthalmic surgery, based on a variety of existing practices and other product process to ensure product reliability, reliability process was established.Together domestic and international standards were investigated that essential in order to maintain a high level of reliability and quality. In this paper, the following findings were obtained. First, learned about the medical equipment needed to ensure quality and reliability standards. Second, reliability ensure process design and formulation were studied.

Cleanroom could be largely classified into industrial cleanroom that can be contaminated by particlesand bio-cleanroom that can be contaminated by biological particles. Electrical manufacturing companies such as precision machines and electrical parts essentially have industrial cleanroom facilities and clean technologies to produce defects free products due to particles.Industrial cleanroom should be controlled in respect of 4M1E to prevent from foreign materials of submicro unit and to keep out contamination sources from outside. In this paper, a concept for a quantitative methodology to measure the particles from running components was suggested by combining both newly making clean booth such as wear tester and laser particle counter.

In this research, customized management performance index for small and medium enterprises in solar energy area was developed. To acquire management performance index, first Delphi technique is applied and secondly, AHP(Analytic Hierarchy Process) used to give weight to each main index and then final management performance index was achieved. By developing management performance index, top management could manage their company more efficiently.

This study is designed to predict the overall electric power load, to apply the method of time sharing and to reduce simultaneous load factor of electric power when authorized by user entering demand plans and using schedules into the user’s interface for a certain period of time. This is about smart grid, which reduces electric power load through simultaneous load factor of electric power reduction system supervision agent. Also, this study has the following characteristics. First, it is the user interface which enables authorized users to enter and send/receive such data as demand plan and using schedule for a certain period of time. Second, it is the database server, which collects, classifies, analysis, save and manage demand forecast data for a certain period of time. Third, is the simultaneous load factor of electric power control agent, which controls usage of electric power by getting control signal, which is intended to reduce the simultaneous load factor of electric power by the use of the time sharing control system, form the user interface, which also integrate and compare the data which were gained from the interface and the demand forecast data of the certain period of time.

To meet the needs of customer, manufacturing companies are diversifying product making methods. In order to adapt to changes, companies are trying to find a new manufacturing system. In this research, MTS(Make to Stock) and MTO(Make to Order) production m

This study looks at a company which introduced SAP program, one type of ERP systems, and how the firm copes with the problems which happen in business process. The research tried to solve the problem by IDEAL method of process software improvement methodo