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Grant: Discovery Grants Program - Individual

University of Ontario Institute of Technology

$12,907.00

Disruption Risk Management in Multi-Echelon Supply Networks

FY 2018-19

Summary
The globalization of supply chains and increased interdependence among the supply chain partners have resulted in more complex supply networks that can exacerbate the effect of disruptions on the supply chain partners. Also, the frequency and extent of the disruption have increased lately and many companies have become more concerned about their ability to manage risks and respond to the disruptions. For example, the Global Procurement Study found that 80% of companies are vulnerable to a major disruption. In addition, it is very difficult to anticipate disruptions and after occurrence, they cause huge negative financial impacts for companies and recovery from disruption to return to normal conditions is often slow. Therefore, without proper mitigation and recovery strategies, supply chains may suffer significant losses while recovering from disruptions. This has led many supply chains to reconsider their supply network configuration. For example, after the 2011 earthquake in Japan the major auto manufacturers starts asking questions about how their supply network should be designed, in particular the question of adding redundancy through either extra inventory, extra capacity or redundant facilities.*The existing literature assumes a single type of mitigation or recovery strategies and considers the known disruption factors. This research aims to address this gap by developing mathematical models, analytical approaches and solution techniques to: (1) better estimation of disruption and recovery probabilities/rates and develop models that perform effective even when the disruption parameters are unknown, (2) develop a systematic approach to manage disruptions in multi echelon supply systems that disruption happens in more than one level and impact of disruptions in different levels may be dependent, and (3) develop multi mitigation and recovery strategies simultaneously and study the value of multi strategies approach. The outcomes of this research will provide insight for researchers and practitioners of Canadian companies, develop a comprehensive methodology to manage disruptions and enhance the effectiveness of the decisions which are made for pre- and post-disruption periods. Finally, High Quality Personnel (both PhD and MSc students) will be trained in supply chain management, risk management, stochastic programming and large-scale optimization that will prepare them for employment in academics and industry.
Program
Discovery Grants Program - Individual
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RGPIN-2017-05793
Name nom
Azad, Nader
Department département
Finance, Information Systems, and Management Science
Organization id
19222
Institution établissement
University of Ontario Institute of Technology
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2017
Award amount
12907
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
1509
Committee name en
Civil, Industrial and Systems Engineering
Committee name fr
Génie civil, industriel et des systèmes
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
1603
Research subject group en
Industrial engineering
Research subject group fr
Génie industriel
Research subject en
Logistics
Research subject fr
Logistique
Partie
2
Nb partie
5
Application title
Disruption Risk Management in Multi-Echelon Supply Networks
Keyword
NSERC
Application summary
The globalization of supply chains and increased interdependence among the supply chain partners have resulted in more complex supply networks that can exacerbate the effect of disruptions on the supply chain partners. Also, the frequency and extent of the disruption have increased lately and many companies have become more concerned about their ability to manage risks and respond to the disruptions. For example, the Global Procurement Study found that 80% of companies are vulnerable to a major disruption. In addition, it is very difficult to anticipate disruptions and after occurrence, they cause huge negative financial impacts for companies and recovery from disruption to return to normal conditions is often slow. Therefore, without proper mitigation and recovery strategies, supply chains may suffer significant losses while recovering from disruptions. This has led many supply chains to reconsider their supply network configuration. For example, after the 2011 earthquake in Japan the major auto manufacturers starts asking questions about how their supply network should be designed, in particular the question of adding redundancy through either extra inventory, extra capacity or redundant facilities.*The existing literature assumes a single type of mitigation or recovery strategies and considers the known disruption factors. This research aims to address this gap by developing mathematical models, analytical approaches and solution techniques to: (1) better estimation of disruption and recovery probabilities/rates and develop models that perform effective even when the disruption parameters are unknown, (2) develop a systematic approach to manage disruptions in multi echelon supply systems that disruption happens in more than one level and impact of disruptions in different levels may be dependent, and (3) develop multi mitigation and recovery strategies simultaneously and study the value of multi strategies approach. The outcomes of this research will provide insight for researchers and practitioners of Canadian companies, develop a comprehensive methodology to manage disruptions and enhance the effectiveness of the decisions which are made for pre- and post-disruption periods. Finally, High Quality Personnel (both PhD and MSc students) will be trained in supply chain management, risk management, stochastic programming and large-scale optimization that will prepare them for employment in academics and industry.