Grant: Discovery Grants Program - Individual
Université du Québec à Trois-Rivières
$15,000.00
Modeling, optimization of complex dynamic manufacturing systems
FY 2006-07
Summary
This research aims at studying how to model and optimize complex manufacturing systems when dynamic product demands and changes in product mix are present or anticipated. For such manufacturing problems, dynamic Cellular Manufacturing (CM) systems are expected to perform better than a static CM system in terms of efficiency and flexibility. Following dynamic CM approach, optimization modeling, effective/efficient solution procedures will be investigated to analyse how movable machines affect the production process in such dynamic manufacturing environments. On application side, the developed models and solution methods will be applied to address real-life system design/operation control problems in industry where it is often required to reorganize the work shop to meet changing requirements. Two important issues in dynamic manufacturing system design will be addressed: when and how to configure a manufacturing system. In this research, a decentralized decision making scheme will be developed and used to characterize the dynamic manufacturing process. In this scheme, the master problem deals with the job loading, system reconfiguration (physical reconfiguration). The sub-problems at lower level address the virtual cell formation (virtual reconfiguration) and scheduling for processing the jobs assigned to a given time period. Considering system performances at the lower level, the master problem adjusts the job loading strategies and physically reconfigures the system for "optimal" global system performance. Modeling and solution procedure development in this scheme will be studied. The novelty of the proposed research is in the methodology and the methods to be developed for handling dynamic product demands and changes in the product mix. The development of integrated models and effective solutions enables us to describe the problems more accurately and intelligently. The research will eventually lead to more desirable manufacturing designs with higher productivity and better manufacturing processes.
Program
Discovery Grants Program - Individual
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
311712-2006
Name nom
Cao, Dong
Department département
Génie industriel
Organization id
59
Institution établissement
Université du Québec à Trois-Rivières
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2006
Competition year année de concours
2006
Award amount
15000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
20
Committee name en
Industrial Engineering
Committee name fr
Génie industriel
Area of application code
520
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Production and operations management
Area of application fr
Production et gestion des opérations
Research subject code
1600
Research subject group en
Industrial engineering
Research subject group fr
Génie industriel
Research subject en
Industrial engineering
Research subject fr
Génie industriel
Partie
1
Nb partie
5
Application title
Modeling, optimization of complex dynamic manufacturing systems
Keyword
NA
Application summary
This research aims at studying how to model and optimize complex manufacturing systems when dynamic product demands and changes in product mix are present or anticipated. For such manufacturing problems, dynamic Cellular Manufacturing (CM) systems are expected to perform better than a static CM system in terms of efficiency and flexibility. Following dynamic CM approach, optimization modeling, effective/efficient solution procedures will be investigated to analyse how movable machines affect the production process in such dynamic manufacturing environments. On application side, the developed models and solution methods will be applied to address real-life system design/operation control problems in industry where it is often required to reorganize the work shop to meet changing requirements. Two important issues in dynamic manufacturing system design will be addressed: when and how to configure a manufacturing system. In this research, a decentralized decision making scheme will be developed and used to characterize the dynamic manufacturing process. In this scheme, the master problem deals with the job loading, system reconfiguration (physical reconfiguration). The sub-problems at lower level address the virtual cell formation (virtual reconfiguration) and scheduling for processing the jobs assigned to a given time period. Considering system performances at the lower level, the master problem adjusts the job loading strategies and physically reconfigures the system for "optimal" global system performance. Modeling and solution procedure development in this scheme will be studied. The novelty of the proposed research is in the methodology and the methods to be developed for handling dynamic product demands and changes in the product mix. The development of integrated models and effective solutions enables us to describe the problems more accurately and intelligently. The research will eventually lead to more desirable manufacturing designs with higher productivity and better manufacturing processes.
