Department of Industrial
& Management Engineering

Logistics Information Technology LAB

Logistics Information Technology LAB

We develop algorithms of optimal solutions which can unsolved problems in industrial engineering(computer science, mathematics) and have an effort to apply this rhythms both scientifically and practically. For instance, we study a wide field of imization and information technology such as environment technology, medical/life information technology and SCM information technology for manufacturing industry.

SCM(Supply Chain Management) LAB

Supply Chain Management

The SCM lab puts focus on the planning, organizing, and controlling of any logistics activities throughout SCM. System modeling and simulation are widely used to estimate and evaluate SCM systems. The lab members are conducting research on a comprehensive and state-of-the-art treatment of all the important aspects of a simulation study, including modeling, simulation software, model verification and validation, input modeling, random-number generators, generating random variates and processes, statistical design and analysis of simulation experiments, and to motivate highlight major application areas such as manufacturing.

Management Engineering & Operations Research LAB

The Management Science, sometimes called Operations Research, has played a major role in developing and improving the industrial systems around us. The members of Management Engineering & Operations Research lab. are the professionals researching on developing new theories and applying the existing theories to the variety of industrial systems. The systems we are concerned include, to name a few, logistics systems, service systems, financial systems, and transportation systems. What we are focusing recently is the amalgamation of the several fields of research areas. What really important to the companies is the concepts of demand, profit, pricing, and market analysis. The final goal that should be sought all the time is the profit maximization.

SEAQ(Statistical Engineering for Advances Quality) LAB

ACD&FD (Applied Computational Design & Fluid Dynamics) laboratory try to overcome the disadvantages of the experimental system such as space limitation, high cost of manufacturing and time through the mechanical engineering simulation. Moreover, The laboratory struggle to achieve the academic and technical development in fluid dynamics field via joint project/ technical transfer wiSEAQ Lab is to continually develop and improve the theories and methods of statistical process control(SPC) and reliability. We develop user-friendly software and other statistical tools that help business and their employees implement SPC and Six Sigma, as well as tools to help students understand the concepts of SPC and Six Sigma. In addition, much of our research focuses on combining SPC Knowledge with IT, BT, NT, and ET. Specifically, statistical process control, regression analysis, design of experiment, reliability engineering, service quality, and quality management are main disciplines in our lab. th our own know-how.

  • Hanyang University Korean Standards Association ez SPC(statistlcal Process Control) Version 1.0 
					Statistical Engineering for Advanced Quality Lab Copyright (C) 2003 by SEAQ Lab. All rights reserved Designed by indi+plus lnc.
  • 중소기업청 한국표준협회 100PPM 품질혁신 소프트웨어 Version 2.0 한양대학교 품질시스템 연구실 Quality System Research Lab.(QSRL) Tel:031-400-5264 Fax:031-408-5098 Copyright(c) 1998 by Qulity System Research Lab. All rights reserved Designed by Fomax Design consulting Group

ErgoMechanics LAB

레오나르도 다 빈치 인체해부도

The ErgoMechanics lab. conducts research on biomechanics, cognitive ergonomics, and affective ergonomics. Specifically, analysis of kinematics and electromyography, MSD evaluation and prevention, and ergonomic product design are pursued for physical Ergonomics. As for cognitive ergonomics, usability testing methodology, human-computer interface design, and cognitive system design for safety are studied. Recent increasing interest in affective ergonomics is also accommodated by studying affective robotics, Kansei engineering methodology, and affective communication system design.

Probability Application LAB

Ubiquitous Environmnets

Probability theory is the only scientific tool to evaluate the systems with uncertainties and predict their performances. Especially, queueing theory is one of the most powerful tools which can analyze the systems which evolve in time probabilistically. Our research area includes telecommunication system, manufacturing system, supply chain management, etc. Recently, we focus on the performance of stations which deal with Internet data and information, with which the best strategic plan can be derived.

Information Analysis & Decision System LAB

Bayesian Paradigm

For the best choice among alternatives, we study on the systematic information analysis. We focus on two things. The first is a decision system whose four phases are measurement, assessment, management and prediction. We here apply the Bayesian paradigm for translating uncertainties in the nature into the well-formed information. The second is a graphical presentation for making decisions. Its logical expression will facilitate the decision processes.

Complex Systems Interaction LAB

Ubiquitous Computing Environmnet

FData-driven formal modeling and control of complex systems focusing on human-machine(automated systems) interface.

Production Engineering & Operations Management LAB

The lab focuses on various topics related to production engineering and operations managements. The goal of our research is to provide various optimal inventory policies for different types of production systems. The research topics of this research area include the followings:
Inventory management: Optimal ordering policies, centralize-decentralized decision mechanism, deterministic and stochastic models, distribution free approach, optimization techniques.
Advance manufacturing and process optimization: Decision making model for augmented production system, total productive maintenance for machine life improvement, optimum inspection and defect detection strategies.
Human factors and reverse logistics: Closed-loop supply chain management, Container management and product collection for reuse through third party logistics (3PL).
Disruption management in production system: Goal programming and multi-item production system.
Humanitarian supply chain management: Inspection errors, Quality of human labors, environmental impact, and transportation.
Fuzzy: Uncertainty/ imprecise in optimization.
Optimization: Analytical techniques and numerical methods.