• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.187-192
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• 2006

In the absence of a clear command and control structure, a key challenge in supply chain management is the coordination and alignment of the supply chain members who pursue divergent and often conflicting goals. The newsvendor model is typically used as a framework to quantify the cost of misalignment and to assess the impact of coordination initiatives. This paper considers a fuzzy approach for the newsvendor problem which includes a single manufacturer and a single retailer. We use several fuzzy parameters in the model such as the demand, the wholesale price, and the market sales price. We apply a coordination policy, referred to as buyback, to solve the fuzzy newsvendor problem. Based on the buyback policy, the optimal order quantity of the retailer can be computed, and the possible profits of the members in the supply chain can be calculated with minimum sharing of private information. Focusing on the fuzzy model with buyback policy for the newsvendor problem, we illustrate exemplary fuzzy models. We also illustrate an integration model, which extends a single-manufacturer-single-retailer model to the single-manufacturer-multiple-retailer setting. In the extended model, we consider three coordination policies including quantity discount, profit sharing, and buyback, as well as non-coordination case.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.136-144
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• 2014

The existing conventional motion controller does not perform well in the presence of nonlinear properties, uncertain factors, and servo lag phenomena of industrial actuators. Hence, a feasible and effective fuzzy self-tuning proportional integral derivative (PID) and feed-forward control scheme is introduced to overcome these problems. In this design, a fuzzy tuner is used to tune the PID parameters resulting in the rejection of the disturbance, which achieves better performance. Then, both velocity and acceleration feed-forward units are added to considerably reduce the tracking error due to servo lag. To verify the capability and effectiveness of the proposed control scheme, the hardware configuration includes digital signal processing (DSP) which plays the main role, dual-port RAM (DPRAM) to guarantee rapid and reliable communication with the host, field-programmable gate array (FPGA) to handle the task of the address decoder and receive the feed-back encoder signal, and several peripheral logic circuits. The results from the experiments show that the proposed motion controller has a smooth profile, with high tracking precision and real-time performance, which are applicable in various manufacturing fields.

• Smart Structures and Systems
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• v.21 no.6
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• pp.751-759
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• 2018

Glass fibre reinforced polymers (GFRP) are widely exploited in many industrial branches. Due to this Structural Health Monitoring systems containing embedded fibre optics sensors are applied. One of the problems that can influence on composite element durability is water contamination that can be introduced into material structure during manufacturing. Such inclusion can be a damage origin significantly decreasing mechanical properties of an element. A non-destructive method that can be applied for inspection of an internal structure of elements is THz spectroscopy. It can be used for identifications of material discontinuities that results in changes of absorption, refractive index or scattering of propagating THz waves. The limitations of THz propagation through water makes this technique a promising solution for detection of a water inclusion. The paper presents an application of THz spectroscopy for detection and localisation of a water drop inclusion embedded in a GFRP material between two fibre optics with fibre Bragg grating sensors. The proposed filtering method allowed to determine a 3D shape of the water drop.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.4
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• pp.436-445
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• 2011

As automation systems become intelligent and autonomous for productibility, industrial networks (fieldbuses) and network-based devices are essential components of intelligent manufacturing systems. However, there are obstacles for the wide acceptance of the network-based devices such as smart sensor and network-based actuator. First, there exist numerous fieldbus protocols that a network-based device should be able to support. Second, the whole network-based device has to be replaced when only the sensor of the module fails. In order to overcome these obstacles, a smart sensor/actuator is implemented as two units; one responsible for network communication and the other for sensor/actuator operations using IEEE 1451.0 standard. This paper presents a structure of the 1451.0-based smart sensor with multiple connectivity function designed by CANopen.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1235-1239
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• 2006

Fractal manufacturing system (FrMS) distinguishes itself from other manufacturing systems by the fact that there is a fractal repeated at every scale. A fractal is a volatile organization which consists of goal-oriented agents referred to as AIR-units (autonomous and intelligent resource units). AIR-units unrestrictedly reconfigure fractals in accordance with their own goals. Their goals can be dynamically changed along with the environmental status. Since goals of AIR-units are represented as fuzzy models, an AIR-unit itself is a fuzzy logic controller. This paper presents a goal regulation mechanism in the FrMS. In particular, a reinforcement learning method is adopted as a regulating mechanism of the fuzzy goal model, which uses only weak reinforcement signal. Goal regulation is achieved by building a feedforward neural network to estimate compatibility level of current goals, which can then adaptively improve compatibility by using the gradient descent method. Goal-oriented features of AIR-units are also presented.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.499-506
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• 2007

The tiny camera module used in a modern cellular phone requires precise assembly processes. To meet the requirement of high resolution and functionality, the number of parts used in a camera module becomes larger and larger. As the market grows rapidly, an automatic camera phone assembly process is required. However, diverse production line and short life cycle make it difficult to build an affordable assembly line. To attack this problem, a flexible and expandable lens assembly system is proposed. To save the manufacturing line set-up time, modular concept is adopted. Also, each module is designed to have intelligence to simplify the set-up process. The assembly system is built up on the standard flat-form that includes a vibration free base, air and electric supplies, and electronic controllers, etc. Furthermore, the assembly cell has the capability of handling tiny, thin, or transparent parts which are very difficult to identify without machine vision.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.649-652
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• 2005

The camera cellular phone has a large portion of cellular phone market in recent year. The variety of a customer demand makes a fast model change and the spatial resolution is changed from VGA to multi-mega pixel. The 1.3 mega pixel (MP) camera cellular phone was first released into the Korean market in October 2003. The major cellular phone companies released a 2MP camera cellular phone that supports zoom function and a 2MP camera cellular phone is settled down with the Korea cellular phone market. It makes a keen competition in price and demands automation for phone camera module. There is an increasing requirement for the automatic assembly to correspond to a fast model change. The hard automation techniques that rely on dedicated manufacturing system are too inflexible to meet this requirement. Therefore in this study, this system is designed with the flexibility concept in order to cope with phone camera module change. The system has a same platform that has X-Y-Z motion or X-Z motion with ${\mu}m$order accuracy. It has a special gripper according to the type of a component to be put together. If the camera model changes, the gripper may be updated to fit for the camera module. The controller of this system acquires the data sets that have the information about the assembly part by the tray. This information is obtained ahead of an inspection step. The controller excludes an inferior part to be assembled by using this information to diminish the inferior goods. The assembly jig used in this system has a function of self adjustment that reduces the tact time and also diminish the inferior goods. Finally, the intelligent assembly system for phone camera module will be designed to get a flexibility to meet model change and a high productivity with a high reliability.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.43-57
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• 2021

Smart factories can be defined as intelligent factories that produce products through IoT-based data. In order to build and operate a smart factory, various new technologies such as CPS, IoT, Big Data, and AI are to be introduced and utilized, while the implementation of a MES system that accurately and quickly collects equipment data and production performance is as important as those new technologies. First of all, it is very essential to build a smart factory appropriate to the current status of the company. In this study, what are the essential prerequisite factors for successfully implementing a smart factory was investigated. A case study has been carried out to illustrate the effect of implementing ERP and MES, and to examine the extensibilities into a smart factory. ERP and MES as an integrated manufacturing information system do not imply a smart factory, however, it has been confirmed that ERP and MES are necessary conditions among many factors for developing into a smart factory. Therefore, the stepwise implementation of intelligent MES through the expansion of MES function was suggested. An intelligent MES that is capable of making various decisions has been investigated as a prototyping system by applying data mining techniques and big data analysis. In the end, in order for small and medium enterprises to implement a low-cost, high-efficiency smart factory, the level and goal of the smart factory must be clearly defined, and the transition to ERP and MES-based intelligent factories could be a potential alternative.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.348-353
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• 2006

Autonomous and intelligent resource model (AIR-model) defines a building-block of complex systems to pursue value creation by means of diverse resources, referred to as an AIR-unit, and presents a collaboration model with the AIR-units. An AIR-unit represents a piece of resources, such as machines, labor, raw materials, and other assets, considered individually by a complex system as means to accomplish given tasks. It is defined with its own service capability and a goal, and pursues achieving the goal by means of the capability. Moreover, an Air-unit is equipped with autonomy and intelligence, whereby it makes a decision on its course of action on its own initiative. Air-units collaborate on system operations with each other through goal-oriented negotiations. In this research, distinctive features of the AIR-model are addressed and described in detail. Principal components of the AIR-model are also designed via object-oriented modeling techniques. A prototype system based on the AIR-model is finally presented as an embodiment tool of a fractal manufacturing system (FrMS).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.1
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• pp.78-85
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• 2013

Since the basic built-in-test, prognostic health management (PHM) has evolved into more sophisticated and complex systems with advanced warning and failure detection devices. Aerospace and military systems, manufacturing equipment, structural monitoring, automotive electronic systems and telecommunication systems are examples of fields in which PHM has been fully utilized. Nowadays, the automotive electronic system has become more sophisticated and increasingly dependent on accurate sensors and reliable microprocessors to perform vehicle control functions which help to detect faults and to predict the remaining useful life of automotive parts. As the complication of automotive system increases, the need for intelligent PHM becomes more significant. Given enormous potential to be developed lays ahead, this paper presents findings and discussions on the trends of automotive PHM research with the expectation to offer opportunity for further improving the current technologies and methods to be applied into more advanced applications.