Poster Session 3 p .124 A New GA-based RBF Neural p.l25 Constructing Model of Network with Optimal Organizational Internal

12/11/2009 10:30 . 11 :00 Selection Clustering Knowledge Integration Based Room: Longchamps I & II Algorithm for SINS Fault on Cultural Algorithm

Diagnosis Sihua chen', Changqi tao', Wei he• Zhide Liu', Jiabin Chen', 'JiangXi University of Finance And

p.123 Kinematic Analysis and Yongqiang Han', Chunlei Song' Economics, China Post-Processing Algorithm 18eijing Institute ofTeclmology, China Research for S-A xis CNC p.l25 The Empirical Study on the Machine Tools with a p.124 A Smart Model for Urban Creation of Corporate Universal Head Ticketing Based on RFID Intellectual Capital from the Chun Xie', Weimin Zhang', Applications Perspective of Social Capital XinyuanHe' Maria Grazia Gnoni', Alessandra Jun-yiRen' 1Tongji University, Chirzn Rollo', Piergiuseppe Tundo' 1Yantai University, Chi>ta 'Shenyang Machine Tool !Group) CO., 1 Dept. of Engmeering for LTD, China llmovation/University of salento, Italy p .125 International Comparison on

p.124 Applying Fuzzy Ruled Based the Coordination Degree p .l23 The Simulation of Cutting Between Economic Force of Free-form Surface to Flexible Routing Problem

Development and BERD Machining with Ball-end in a Flexible Manufacturing Investment Milling Cutter System Haifeng Wang1, Yafei Luo' l.ei Shi1

, En Fu Liu', Yi Zhang', lraj Mahdavi', Amirhosein Fekri 18eijing University of Technology, Peng Chen1, Zongbin Li' Moghaddam Azar', Morteza China 'Xi' an ]iaotong University, China Bagherpour' 2Hebei University of Science and 1Mazandaran University of Science p .125 A New Classification Method Technology, China and Technology, Iran

on the Basis of a ' Islamic Azad University of Shiraz, Patent-Science Relationship p.l23 Cold Nosing Process Iran Yan-Ru Li', Tzu-Ying Li' Modeling and Simulation for

p.l24 A Multi-Agent and Extremal 1 University of Alefheia, Taiwan Manufacturing of Aluminium

Optimization System for :' Conical Milk Can "Steelmaking-Continuous p.l25 Research on Parameter Jinn-Jong Sheu1, Hsien-Hsiu Su•

Transferring Complexity of 'National Kaohsiung University of Casting-Hot Strip Mill" Assembly Variant Design Applied Sciences, Taiwan Integrated Scheduling Xinsheng Xu1, Xin Cheng', Rigeng]i', Yong-Zai Lu• Zhengxiang Li' p.123 A Manufacturing 1Zhejiang University, China 'China Jiliang University, China Performance Evaluation

p. 124 Forecasting Stock Price Using 'Zhejiang University, China Model for Notebook Computer Manufacturers Nonlinear Independent p.l25 Customer-Oriented Library Rong-Hwa Huang', Chang-Lin Component Analysis and

Services for Chinese Higher Yang', Hui-lung Shih1 Support Vector Regression Education •Fu fen Catholic U11iversity, Taiwan Chi-Jie Lu', Jui-Yu Wu2, Jiahui Jiang', Yongbing Zhang2 Cheng-Ruei Fan>, Chih-Chou Chiu' 1 Library of Southwestem University of p.l23 Noise Identification and Fault 1Ching Yun University, Taiwan Finance and Economics, China

Diagnosis for the New ' Lunghwa University of Science a11d 'University ofTsukuba, Japan Technology, Taiwan Products of ~e Automobile

'National Taipei University of p.l26 An Ubiquitous Infrastructure Gearbox

Technology, Taiwan Wenli shang'. Yigong yan2, Haibo Applications to Support shi' p.l24 Estimating the Inquiring Museum's Service ' Shenya>tg Institute of

Time Interval for the Patent Chen-Wo Kuo', Johannes K. Automation,Chi11ese ACIJdemy of Analysis by the Technology Chiang' Science, China

'National Chengchi University, Taiwan 2Changchun University of Technology, Obsolescence Cycle China Hsiao-Chung Wu1, Hung-Yi Chen'

p.l26 The Valuation of Money-Back 1Chaoyang University of Technology, Guarantees in Retailing p.l23 Analysis of the Forming Taiwan Markets: A Real Option Defects of the Trapezoidal

p .l24 Demonstration Study on Approach Inner-gear Spinning Lieh-Ming Luo1, Hui-Tzu Lee2, Qin-xiang Xia1, Ling-yan Sun•, Small and Medium High-tech Yu-Ping Hsieh' Xiu-quan Cheng', Bang-yan Ye1 Enterprises Growth: The Case 1 Fu Jen Catholic University, Tniwa11 'South Chi11a U>riversity of Technology, ofDalian 'National Chung Hsing University, China Lin Li', Pengfei Zhou2, Yan Wang' Taiwan ' Guangzhou Civil Aviation College, 'Dalian ]iaofong University, China 'Chihlee Institute of Technology, China 2Dalian University of Technology, Taiwan China

p.l23 Research on Tool Path p.l26 Research on the Planning for Five-Axis p.125 The Antecedents and

Service-oriented Machining Consequences of Customer Manufacturing Model Peinan Li', Ruifeng Guo•, Pin Knowledge Development in Na Gao1, Songzheng Zhao', Xiaodi Wang', Yan Huang' New Product Development Zhang' 1Shenyang Institute of Computiltg Yen-Tsung Huang', 1-Chun Chen' 1 Northwestern Polytechnical Technology, Chinese ACIJdemy of 'Tunghai University, Taiwan University, China Sciences, China

p.l24 Stock Index Prediction: A p.125 Computer-aided p.l26 Reachability Analysis of

Classification of Patents Service Process Model Based Comparison of MARS, BPN Oriented to TRIZ on Polychromatic Sets and SVR in an Emerging Yanhong Liang', Runhua Tan', Xinqin Gao', Yan Li', Mingshun Market Chaoyang Wang', Zlti-Guang Li' Yang1, Qilong Yuan1 Clti-Jie Lu', Chih-Hsiang Chang2, 1Hebei University of Technology, China 1Xi'an UniversityofTeclmology, China Chien-Yu Chen1, Chih-Chou Cltiu', 2Hebei Polytechnic University, China Tian-Shyug Lee'

1Ching Yun University, Taiwan 'National Taipei University of Technology, Taiwa11 'Fu ]en Catholic University, Taiwan

44

p.l26

p.126

p.126

p.126

p.l27

Safety Feasibility Analysis on the Liquid Organic Heat Transfer Material Heater Used in the Production Process of Bleaching Powder Concentrate Hui Cui', Zhisheng Xu1, Wenhua Song' •Central South Universrty, Chma 'Tranjin University of Technology, China

Stochastic Analysis on Probability of Fire Scenarios in Risk Assessment to Occupant Evacuation Guanquan Chu', )inhui Wang' •Waterborne Transportation Institute, Ministry of Transport, China •Shanghai Maritime University, China

The Characteristics of Temperature Near the Ceiling of Liquid Fires in Vertical Laminar Clean Room Environments Yan Huo', Ye Gao1, Hong Mei Wu1,

jian He Zhao' 1Harbin Engineering University, China

Large Eddy Simulation of Smoke Movement in a Teaching Building jian He Zhao', Ye Gao', Hong Mei Wu', Yan Huo1

•Harbin Engineering Ut1iversity, China

Study on the Assessment Method of Agroecosystem Health Based on the Pressure-State-Response Model Bo Li', H. L. Xie', H. H. Guo', Ying Hou' 1Beijing Normal University, China 'fiangxi University of Finance & Economics, Chir1a

p.l27 Modeling and Analyzing Safety-critical Parallel-series System Safety Qing Sun', Lirong Cui', Rong Pan' 1Beijing Institute of Technology, China 'Arizona State University, United States

p.l27 Integrating Socio-technological Factors Analysis Into Nuclear Power Plant Event Report and Safety Evaluation: A Systematic Framework Ziqing Zhai1

•Shanghai Jiao Tong University, China

p.l27 Comparsion the Maintenance Between Two-Unit Parallel Standby Systems and 2-out-of-3 Stand by Systems MinWang1

1Chaoyang University of Technology, Taiwan

p.l27 Risk Analysis of the City Gas Pipeline Network Based on the Fault Tree Yi-lin Yin1, Guang-li Lin1

1 Tianji11 University, China

p.127

p.127

p.127

The Empirically Comparative Analysis of Advanced Manufacturing Paradigm of Chinese, Japanese and South Korean Enterprises }un-yi Ren' 1Yantai University. Chma

Maintenance Behavior-Based Prediction System Using Data Mining Pedro Bastos', Rui Lopes', Luis Pires1, Tiago Pedrosa' 'lnstituto Politecnico de Bragan~a, Portugal

Concept Analysis for Service Oriented Manufacturing Based on Interpretive Structural Modeling Yi-song(Lydia) Zheng', Dong Li', FengZhao' 'Nankai University, China

45

MAINTENANCE BEHAVIOUR-BASED PREDICTION SYSTEM USING DATA MINING Pedro Bastos, Rui Lopes, Luís Pires, Tiago Pedrosa,

Instituto Politécnico de Bragança, Campus de Santa Apolónia, Apartado 1038 - 5301-854 Bragança- Portugal (bastos@ipb.pt, rlopes@ipb.pt, luica@ipb.pt, pedrosa@ipb.pt)

 

In the last years we have assisted to several and deep changes in industrial manufacturing. Induced by the need of increasing efficiency, bigger flexibility, better quality and lower costs, it became more complex. The complexity of this new scenario has caused big pressure under enterprises production systems and consequently in its maintenance systems. Manufacturing systems recognize high level costs due equipment breakdown, motivated by the time spent to repair, which corresponds to no production time and scrapyard, and also money spent in repair actions. Usually, enterprises do not share data produced from their maintenance interventions. This investigation intends to create an organizational architecture that integrates data produced in factories on their activities of reactive, predictive and preventive maintenance. The main idea is to develop a decentralized predictive maintenance system based on data mining concepts. Predicting the possibility of breakdowns with bigger accuracy will increase systems reliability.

Perspec(ves   Maintenance function is seen to the enterprise as a cost;   Maintenance function, seen as a one, became more and more requested to contribute to cost

reduction, based on bigger and consistent equipment reliability   Manufacturing systems recognize high level costs due equipment breakdown, related with

inspection costs, repair costs as well as costs associated with non production time or equipment non utilization;

  Enterprises need to cope with market expectations, incorporating in their production philosophies new paradigms such as JIT- Just in time, MTO- Make to order, Mass Customization, Agile or Lean manufacturing.

Mo(va(on/Objec(ves   In literature there are some approaches that use data mining concepts to improve

manufacturing activities.

  It isn’t so common to find approaches that use it to improve the capacity of predicting behaviors based on historical data.

  In fact, if the case is the possibility of a distributed collaboration of independent enterprises sharing data between them, even if they are competitors, the examples are even reduced.

  Create a system that will help enterprises to collect, extract and create knowledge in a way that

enterprises will predict with more accuracy the moment to realize maintenance actions and thus improve the productivity of manufacturing process.

Pressure/support factors 

► Globalization, new markets coming in sight

► Bigger exigency in products quality

$ $$

► Development and incorporation of information and communication technologies

► Products life cycle and time to market decreasing

► Technological changes and products bigger complexity.

► Mass Customization

7 56

121110

8 4

21

9 3

Remote data management

and communication

A1

P. 3

Knowledge Prediction System

A2

P. 4 Information Synthesis and

event generation

A3

Predictive Maintenance dataPreventive Maintenance dataReactive Maintenance dataManufacturers dataPartners Information

Status eventAlert event

Request Knowledge Base Event

Active Knowledge Base

Specification parameters

C1 Artificial neural networks

C6 Data Visualization

C2 Rule Induction

C3 Nearest neighbor method

C5 Genetic Algorithms

C4 Decision Trees

Behaviour Matrix

M1Prospective Agents

M2 Knowledge data engineM3 Pattern recognition AlgorithmsM4Communication chanel and tools

Behaviour Data Storing

I1Predictive Maintenance data

I2 Preventive Maintenance data

I3 Reactive Maintenance data

I4 Manufacturers data

I5 Partners Information

C2

Request Knowledge Base

C1

Event

Data request analisis and specification

A11

Data Management and Selection

A12

Knowledge Base definition

A13

Decision Support

formalization

A14O2

Alert eventO1

Status event

Selection specifications

Selection constrains

O3Active Knowledge Base

O4Specification parameters

M2Communication chanel and tools M1Prospective Agents

M3Knowledge data engine

I6 Behaviour Data Storing

O1Request Knowledge Base

I1Active Knowledge Base

I2Specification parameters

C1Artificial neural networks C2 Rule InductionC3 Nearest neighbor method

C4 Decision TreesC5 Genetic Algorithms

C6 Data Visualization

O2Behaviour Matrix

Data Mining processing

A21

Pattern Behaviour generation

A22

Proactive Faillure

detection module

A23

Organizational KnowledgeRelations IdentificationData InterpretationRules

M2Knowledge data engine

M3Pattern recognition Algorithms

M1Communication chanel and tools

Proactive faillure notification

I3Partners Information

M. Preven(va M. Predi(va M. Correc(va

M. Preven(va M. Predi(va M. Correc(va

M. Preven(va M. Predi(va M. Correc(va

Behavior Pa;ern genera(on ayer 

Events dessimina(on

SYSTEM FUNCIONALITY