• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.40 no.4
• /
• pp.112-119
• /
• 2017

Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an "if-then" rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers' general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier's performance and eventually influence buyer's production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.

• Journal of Korea Society of Industrial Information Systems
• /
• v.6 no.3
• /
• pp.35-43
• /
• 2001

This thesis proposes a diagnostic formula for student's responses based on linguistic variable concept of fuzzy that makes domain expert to input the kernel elementeasily that constructs domain independent student module. And the domain expert can construct the rule with linguistic variable that is used to inference student's recognition state. This study designs a student module that can inference student's recognition state using this rule represented by linguistic variable.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2000.04a
• /
• pp.5-8
• /
• 2000

Vehicle travel time (empty travel time pius loaded travel time) is a key parameter for designing AGV-based material handling systems. Especially, the determination of empty vehicle travel time is difficult because of the stochastic nature of the empty vehicle locations. This paper presents a method to estimate vehicle travel times for AGV-based material transport systems. The model considers probabilistic aspects for the travel time and vehicle location under random vehicle selection rule and nearest vehicle selection rule. The estimation of empty travel time is of major effort. Simulation experiments are used to verify the proposed travel time model, and the simulation results show that the presented model provides reasonable travel time estimations.

• Journal of Korea Society of Industrial Information Systems
• /
• v.8 no.1
• /
• pp.75-82
• /
• 2003

Computer and network security has recently become a popular subject due to the explosive growth of the Internet Especially, attacks based on malformed packet are difficult to detect because these attacks use the skill of bypassing the intrusion detection system and Firewall. This paper designs and implements a network-based intrusion detection system (NIDS) which detects intrusions with malformed-packets in real-time. First, signatures, rules in NIDS like Snouts rule files, are classified using similar properties between signatures NIDS creates a rule tree applying hashing technique based on the classification. As a result the system can efficiently perform intrusion detection.

• Proceedings of the KIEE Conference
• /
• 1987.11a
• /
• pp.118-121
• /
• 1987

This paper presents a rule-based approach for automatically selecting critical contingencies in electric power systems. The rules required to perform the task are derived from inspection about results of simulation and expertise of operators. And inherent information of system, for example, topology of system configuration, and flow direction in a line by compensation theorem. etc., which are independent of operating point of system, is stored in the database using the off-line calculation. The approach was investigated using the study of a sample test system. Since it is based on the knowledge engineering technique, efficiency of selection can be improved by updating and adding the rules.

• ETRI Journal
• /
• v.41 no.4
• /
• pp.515-527
• /
• 2019

This paper discusses the design, implementation, and potential use of an ontology-based mobile pediatric consultation and monitoring system, which is a smart healthcare expert system for pediatric patients. The proposed system provides remote consultation and monitoring of pediatric patients during their illness at places distant from medical service areas. The system not only shares instant medical data with a pediatrician but also examines the data as a smart medical assistant to detect any emergency situation. In addition, it uses an inference engine to infer instant suggestions for performing certain initial medical treatment steps when necessary. The applied methodologies and main technical contributions have three aspects: (a) pediatric consultation and monitoring ontology, (b) semantic Web rule knowledge base, and (c) inference engine. Two case studies with real pediatric patients are provided and discussed. The reported results of the applied case studies are promising, and they demonstrate the applicability, effectiveness, and efficiency of the proposed approach.

• Transactions of the Korean hydrogen and new energy society
• /
• v.34 no.5
• /
• pp.490-496
• /
• 2023

Unmanned aerial vehicles (UAVs) research is recently actively underway. Especially, fuel cell battery hybrid systems are widely used to overcome the limitations of continuous operation. However, fuel cell systems must be operated in combination with a battery due to their low specific output characteristics. Therefore, a hybrid power system model for UAVs is developed. The rule-based strategy is applied to the model to properly distribute power to batteries and fuel cells. As a result, the designed rule-based power distribution control operates UAVs while maintaining battery state of charge(SOC) at an appropriate level.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.970-974
• /
• 1993

This paper is concerned with an automatic generation of BOM (Bill Of Material) for a bicycle frame set using a knowledge based system. The major components module system includes : (1) Part information retrieval in CAD drawing, (2) BOM code generation rule, and (3) Database interface. The knowledge based system includes a rule base and a fact base. The fact base consists of basic, variant, and optional components of the standard BOMs of frame sets. The rule contains rules for generating new BOM code in case that the specified is not in the database. The system was implemented on a SUN workstation under Open Windows environments. AutoCAD for CAD drawing was also used.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.6
• /
• pp.43-52
• /
• 1994

A design method of rule-based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of ``IF....,THEN...', using the theories of optimization theory , linguistic fuzzy implication rules and fuzzy c-means clustering. Three kinds of method for fuzzy modeling presented in this paper include simplified inference (type I), linear inference (type 2), and modified linear inference (type 3). In order to identify premise structure and parameter of fuzzy implication rules, fuzzy c- means clustering and modified complex method are used respectively and the least sequare method is utilized for the identification of optimum consequence parameters. Time series data for gas furance and those for sewage treatment process are used to evaluate the performance of the proposed rule-based fuzzy modeling. Comparison shows that the proposed method can produce the fuzzy model with higher accuracy than previous other studies.

• Journal of the Korean Society of Safety
• /
• v.16 no.2
• /
• pp.110-116
• /
• 2001

The objective of the Maintenance Rule (MR) is to require monitoring of the overall continuing effectiveness of licensee maintenance programs to ensure that the safety related and certain nonsafety-related SSCs are capable of performing their intended functions. In Korea, as risk informed applications and regulation become active, the necessity of Performance Based Regulation (PBR) has increased. The objective of this article is to study the effectiveness of MR based on performance and feasibility of MR adoption at Korean Nuclear Power Plants (NPPs) for effective maintenance and regulation.