Agent Based Modeling and Simulation Framework for Supply Chain Risk Management

This research develops a flexible agent-based modeling and simulation (ABMS) framework for supply chain risk management with significant enhancements to standard ABMS methods and supply chain risk modeling. Our framework starts with the use of software agents to gather and process input data for use in our simulation model. For our simulation model, we extend an existing mathematical framework for discrete event simulation (DES) to ABMS and then implement the concepts of variable resolution modeling from the DES domain to ABMS and provide further guidelines for aggregation and disaggregation of supply chain models. Existing supply chain risk management research focuses on consumable item supply chains. Since the Air Force supply chain contains many reparable items, we fill this gap with our risk metrics framework designed for reparable item supply chains, which have greater complexity than consumable item supply chains. We present new metrics, along with existing metrics, in a framework for reparable item supply chain risk management and discuss aggregation and disaggregation of metrics for use with our variable resolution modeling

Assimilation of web technologies in firms’ supply chain management: A case of the Ghanaian events Industry

Thesis submitted to the Department of Management Information Systems, Ashesi University College, in partial fulfillment of Bachelor of Science degree in Management Information Systems, April 2016This dissertation examines the supply chain framework of event planning firms in Ghana, with particular reference to the assimilation of technology in the supply chain function. The research seeks to ascertain how exactly, event firms integrate technology in their supply chain and what impact technology has on their supply chain framework. An emphasis was also placed on the type of technologies used in the industry and how quick events firms are in assimilating new technologies. The undergirding theory of the work was based on a supply chain frame work proposed by Lambart ., et al (19989) and Ranganathan ., et al(2006). The methodology employed in analyzing the supply chain framework and technology assimilation included phone and Skype interviews as well as questionnaires. Emails were sent to chief executive officers of event firms and Skype interviews were set. Questionnaires were sent to those who could not have time for interviews. The findings presented in this research consist of information obtained from a qualitative study of a sample of event planning firms in Accra. This study postulates that, there exists an inefficient supply chain frame work in the Ghanaian event firms due to long communication among stake holders. The Ghanaian events industry utilizes mobile applications more than web applications; however, the number of communication prolongs the process. Cross platform applications such as facebook and instagram can be used as web applications, however, industry members choose to use them as mobile applications because of their convenience and simplicity. The supply chain of the event planning industry can be improved by using a series of cross platform applications that can help reduce the communication process among the industry stakeholders. Technology assimilation is high and Social media is the main technology stream significantly used in the industry, the social media sector can be utilized to make communication faster and easier, rendering the supply chain framework efficient.Ashesi University Colleg

Integration of e-business strategy for multi-lifecycle production systems

Internet use has grown exponentially on the last few years becoming a global communication and business resource. Internet-based business, or e-Business will truly affect every sector of the economy in ways that today we can only imagine. The manufacturing sector will be at the forefront of this change. This doctoral dissertation provides a scientific framework and a set of novel decision support tools for evaluating, modeling, and optimizing the overall performance of e-Business integrated multi-lifecycle production systems. The characteristics of this framework include environmental lifecycle study, environmental performance metrics, hyper-network model of integrated e-supply chain networks, fuzzy multi-objective optimization method, discrete-event simulation approach, and scalable enterprise environmental management system design. The dissertation research reveals that integration of e-Business strategy into production systems can alter current industry practices along a pathway towards sustainability, enhancing resource productivity, improving cost efficiencies and reducing lifecycle environmental impacts. The following research challenges and scholarly accomplishments have been addressed in this dissertation: Identification and analysis of environmental impacts of e-Business. A pioneering environmental lifecycle study on the impact of e-Business is conducted, and fuzzy decision theory is further applied to evaluate e-Business scenarios in order to overcome data uncertainty and information gaps; Understanding, evaluation, and development of environmental performance metrics. Major environmental performance metrics are compared and evaluated. A universal target-based performance metric, developed jointly with a team of industry and university researchers, is evaluated, implemented, and utilized in the methodology framework; Generic framework of integrated e-supply chain network. The framework is based on the most recent research on large complex supply chain network model, but extended to integrate demanufacturers, recyclers, and resellers as supply chain partners. Moreover, The e-Business information network is modeled as a overlaid hypernetwork layer for the supply chain; Fuzzy multi-objective optimization theory and discrete-event simulation methods. The solution methods deal with overall system parameter trade-offs, partner selections, and sustainable decision-making; Architecture design for scalable enterprise environmental management system. This novel system is designed and deployed using knowledge-based ontology theory, and XML techniques within an agent-based structure. The implementation model and system prototype are also provided. The new methodology and framework have the potential of being widely used in system analysis, design and implementation of e-Business enabled engineering systems

Evaluation of production control strategies for the co-ordination of work-authorisations and inventory management in lean supply chains

A decision support framework is proposed for assisting managers and executives to possibly utilise lean production control strategies to coordinate work authorisations and inventory management in supply chains. The framework allows decision makers to evaluate and compare the suitability of various strategies to their system especially when considering conflicting objectives, such as maximising customer service levels while minimising Work in Process (WIP) in a business environment distressed by variabilities and uncertainties in demand stemmed from customer power. Also, the framework provides decision guidance in selecting and testing optimal solutions of selected policies control parameters. The framework is demonstrated by application to a four-node serial supply-chain operating under three different pull-based supply chain strategies; namely CONWIP, Kanban, and Hybrid Kanban-CONWIP and exhibiting low, medium, and high variability in customer demand (i.e., coefficient of variation of 25%, 112.5%, and 200%). The framework consists of three phases; namely Modelling, Optimisation and Decision Support; and is applicable to both Simulation-Based and Metamodel-Based Optimisation. The Modelling phase includes conceptual modelling, discrete event simulation modelling and metamodels development. The Optimisation phase requires the application of multi-criteria optimisation methods to generate WIP-Service Level trade-off curves. The Curvature and Risk Analysis of the trade-off curves are utilised in the Decision Support phase to provide guidance to the decision maker in selecting and testing the best settings for the control parameters of the system. The inflection point of the curvature function indicates the point at which further increases in Service Level are only achievable by incurring an unacceptably higher cost in terms of average WIP. Risk analysis quantifies the risk associated with designing a supply chain system under specific environmental parameters. This research contributes an efficient framework that is applicable to solve real supply chain problems and better understanding of the potential impacts and expected effectiveness of different pull control mechanisms, and offers valuable insights on future research opportunities in this field to production and supply chain managers

Internet of Things-Enabled Dynamic Performance Measurement for Real-Time Supply Chain Management - Toward Smarter Supply Chain -

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 산업공학과, 2018. 2. Park, Jinwoo.Supply chain performance measurement has become one of the most important and critical management strategies in the pursuit of perfection and in strengthening the competitive edges of supply chains to face the challenges in todays global markets. To constantly cope with the resulting rapid changes and adopt new process designs while reviving supply chain initiatives and keeping them alive, an effective real-time performance-based IT system should be developed. And there are many researches on supply chain performance measurement system based on the real-time information system. This thesis proposes a standard framework of a digitalized smart real-time performance-based system. The framework represents a new type of smart real-time monitoring and controlling performance-based IT mechanism for the next-generation of supply chain management practices with dynamic and intelligent aspects concerning strategic performance targets. The idea of this mechanism has been derived from the main concepts of traditional supply chain workflow and performance measurement systemswhere the time-based flow is greatly emphasized and considered as the most critical success factor. The proposed mechanism is called Dynamic Supply Chain Performance Mapping (DSCPM), a computerized event-driven performance-based IT system that runs in real-time according to supply chain management principles that cover all supply chain aspects through a diversity of powerful practices to effectively capture violations, and enable timely decision-making to reduce wastes and maximize value. The DSCPM is proposed to contain different types of engines of which the most important one is the Performance Practices and Applications Engine (PPAE) due to its involvement with several modules to guarantee the comprehensiveness of the real-time monitoring system. Each of these modules is specified to control a specific supply chain application that is equipped with suitable real-time monitoring and controlling rules called Real-Time Performance Control Rules (RT-PCRs), which are expressed using Complex Event Processing (CEP) method. The RT-PCRs enable DSCPM to detect any interruptions or violation smartly and accordingly trigger real-time decision-making warnings or re-(actions) to control the performance and achieve a smart real-time working environment. The contributions of this dissertation are as follows: (1) building a conceptual framework to digitalize the supply chain, based on their strategic performance targets, deploying IoT technologies to convert its resources to smart-objects and therefore enable a dynamic and real-time supply chain performance measurement and management. (2) Demonstrating the feasibility of the DSCPM concerning performance targets by developing some practices and tool modules that are supplied with RT-PCRs (e.g., Real-time Demand Lead-time Analysis, Real-time Smart Decision-making Analysis (RT-SDA), Real-time Supply Chain Cost Tracking System (RT-SCCT), etc.). (3) Verifying the effectiveness of RT-PCRs in RT-SDA and RT-SCCT modules by building simulation models using AnyLogic simulation software.Chapter 1. Introduction 1 1.1 OVERVIEW 1 1.2 PROBLEM STATEMENT AND MOTIVATION 4 1.3 RESEARCH OBJECTIVES 7 1.4 THESIS OUTLINE 11 Chapter 2. Background and Literature Review 12 2.1 INTRODUCTION 12 2.2 SUPPLY CHAIN PERFORMANCE MEASUREMENT 13 2.3 PROCESS-ORIENTED SCPM AND SCOR MODEL 25 2.4 IOT AND SCM 31 Chapter 3. Performance-based IoT Deployment for Digital Supply Chain Transformation 40 3.1 INTRODUCTION 40 3.2 DIGITAL SC TRANSFORMATION FRAMEWORK 42 3.3 FRAMEWORK DEMONSTRATION USING A THEORETICAL CASE STUDY 65 3.4 CONCLUSION 71 Chapter 4. IoT-enabled Dynamic Supply Chain Performance Mapping based on Complex Event Processing 73 4.1 INTRODUCTION 73 4.2 REAL-TIME ENTERPRISE INTEGRATION 74 4.3 INTEGRATION OF DSCPM IN REAL-TIME SUPPLY CHAIN INFRASTRUCTURE 76 4.4 DYNAMIC SUPPLY CHAIN PERFORMANCE MAPPING FRAMEWORK (DSCPM) 77 4.5 CONCLUSION 107 Chapter 5. DSCPM-enabled Smart Real-time Performance Measurement Environment 109 5.1 DSCPM-ENABLED REAL-TIME TIME AND PERFORMANCE-BASED ANALYSIS FRAMEWORK 109 5.2 DSCPM-ENABLED REAL-TIME SC COSTS TRACKING SYSTEM 132 Chapter 6. Managing Perishability in Dairy Supply Chain using DSCPM Framework (a case study scenario) 152 6.1 INTRODUCTION 152 6.2 ASSUMPTIONS AND NOTATION 153 6.3 SIMULATION EXPERIMENTS 158 6.4 RESULTS AND DISCUSSION 161 6.5 A NEW APPROACH, FOR DESIGNING AND MANAGING PERISHABLE PRODUCTS INVENTORY SYSTEM 168 6.6 DECISIONS SENSITIVITY ANALYSIS 172 6.7 IOT COSTS-BENEFITS ANALYSIS 173 6.8 CONCLUSIONS 176 Chapter 7. Conclusions 179 7.1 CONCLUSION 179 7.2 FUTURE RESEARCH 182 Bibliography 184Docto

An enhanced framework for blood supply chain risk management

A blood supply chain (BSC) is a very long and complex sequence of processes heavily sequential. If one of them is executed in an incorrect way and this error is not detected, it leads to an incorrect transfusion outcome, that could seriously affect patients. For this reason, there is a strong need to identify and prevent adverse events along the entire BSC, in order to reduce their probability of occurrence. This also helps improving BSC sustainability from both the environmental and the social perspectives. The paper extends an existing healthcare supply chain risk management framework already applied to the blood transfusion process to address multiple BSC echelons and identify the cause and effect relationships among the adverse events that might occur. To this end, Fault Tree Analysis is added to the risk management tools part of the original framework as well as Key Performance Indicators are applied to detect risky event manifestation. The first application of the proposed approach to a blood bank and a hospital ward revealed its effectiveness in identifying the BSC activities most subjected to risk. Also, connections between adverse events and causal relationships among their sources were found, leading to understanding whether an adverse event is caused by a risk source in the same echelon where it occurs or by the concurrent manifestation of several adverse events upstream in the BSC. Future research will be devoted to numerically evaluate probability of occurrence and impact of risky events as well as integrating the framework with a classification of criticalities based on their severity

A reference architecture for the collaborative planning modelling process in multi-tier supply chain networks: a Zachman-based approach

A prominent and contemporary challenge for supply chain (SC) managers concerns the coordination of the efforts of the nodes of the SC in order to mitigate unpredictable market behaviour and satisfy variable customer demand. A productive response to this challenge is to share pertinent market-related information, on a timely basis, in order to effectively manage the decision-making associated with the SC production and transportation planning processes. This paper analyses the most well-known reference modelling languages and frameworks in the collaborative SC field and proposes a novel reference architecture, based upon the Zachman Framework (ZF), for supporting collaborative plan- ning (CP) in multi-level, SC networks. The architecture is applied to an automotive supply chain configuration, where, under a collaborative and decentralised approach, improvements in the service levels for each node were observed. The architecture was shown to provide the base discipline for the organisation of the processes required to manage the CP activity.The authors thanks the support from the project 'Operations Design and Management in Global Supply Chains (GLOBOP)' (Ref. DPI2012-38061-C02-01), funded by the Ministry of Science and Education of Spain, for the supply chain environment research contribution.Hernández Hormazábal, JE.; Lyons, AC.; Poler, R.; Mula, J.; Goncalves, R. (2014). A reference architecture for the collaborative planning modelling process in multi-tier supply chain networks: a Zachman-based approach. Production Planning and Control. 25(13-14):1118-1134. https://doi.org/10.1080/09537287.2013.808842S111811342513-14Al-Mutawah, K., Lee, V., & Cheung, Y. (2008). A new multi-agent system framework for tacit knowledge management in manufacturing supply chains. Journal of Intelligent Manufacturing, 20(5), 593-610. doi:10.1007/s10845-008-0142-0Baïna, S., Panetto, H., & Morel, G. (2009). New paradigms for a product oriented modelling: Case study for traceability. Computers in Industry, 60(3), 172-183. doi:10.1016/j.compind.2008.12.004Berasategi, L., Arana, J., & Castellano, E. (2011). A comprehensive framework for collaborative networked innovation. Production Planning & Control, 22(5-6), 581-593. doi:10.1080/09537287.2010.536628Chan, H. K., & Chan, F. T. S. (2009). A review of coordination studies in the context of supply chain dynamics. International Journal of Production Research, 48(10), 2793-2819. doi:10.1080/00207540902791843Chen, D., Doumeingts, G., & Vernadat, F. (2008). Architectures for enterprise integration and interoperability: Past, present and future. Computers in Industry, 59(7), 647-659. doi:10.1016/j.compind.2007.12.016Choi, Y., Kang, D., Chae, H., & Kim, K. (2006). An enterprise architecture framework for collaboration of virtual enterprise chains. The International Journal of Advanced Manufacturing Technology, 35(11-12), 1065-1078. doi:10.1007/s00170-006-0789-7Choi, Y., Kim, K., & Kim, C. (2005). A design chain collaboration framework using reference models. The International Journal of Advanced Manufacturing Technology, 26(1-2), 183-190. doi:10.1007/s00170-004-2262-9COLQUHOUN, G. J., BAINES, R. W., & CROSSLEY, R. (1993). A state of the art review of IDEFO. International Journal of Computer Integrated Manufacturing, 6(4), 252-264. doi:10.1080/09511929308944576Danilovic, M., & Winroth, M. (2005). A tentative framework for analyzing integration in collaborative manufacturing network settings: a case study. Journal of Engineering and Technology Management, 22(1-2), 141-158. doi:10.1016/j.jengtecman.2004.11.008Derrouiche, R., Neubert, G., Bouras, A., & Savino, M. (2010). B2B relationship management: a framework to explore the impact of collaboration. Production Planning & Control, 21(6), 528-546. doi:10.1080/09537287.2010.488932Dudek, G., & Stadtler, H. (2005). Negotiation-based collaborative planning between supply chains partners. European Journal of Operational Research, 163(3), 668-687. doi:10.1016/j.ejor.2004.01.014Gruat La Forme, F.-A., Genoulaz, V. B., & Campagne, J.-P. (2007). A framework to analyse collaborative performance. Computers in Industry, 58(7), 687-697. doi:10.1016/j.compind.2007.05.007Gutiérrez Vela, F. L., Isla Montes, J. L., Paderewski Rodríguez, P., Sánchez Román, M., & Jiménez Valverde, B. (2007). An architecture for access control management in collaborative enterprise systems based on organization models. Science of Computer Programming, 66(1), 44-59. doi:10.1016/j.scico.2006.10.005Hernández, J. E., Poler, R., Mula, J., & Lario, F. C. (2010). The Reverse Logistic Process of an Automobile Supply Chain Network Supported by a Collaborative Decision-Making Model. Group Decision and Negotiation, 20(1), 79-114. doi:10.1007/s10726-010-9205-7Hernández, J. E., J. Mula, R. Poler, and A. C. Lyons. 2013. “Collaborative Planning in Multi-Tier Supply Chains Supported by a Negotiation-Based Mechanism and Multi-Agent System.”Group Decision and Negotiation Journal. doi:10.1007/s10726-013-9358-2.Jardim-Goncalves, R., Grilo, A., Agostinho, C., Lampathaki, F., & Charalabidis, Y. (2013). Systematisation of Interoperability Body of Knowledge: the foundation for Enterprise Interoperability as a science. Enterprise Information Systems, 7(1), 7-32. doi:10.1080/17517575.2012.684401Kampstra, R. P., Ashayeri, J., & Gattorna, J. L. (2006). Realities of supply chain collaboration. The International Journal of Logistics Management, 17(3), 312-330. doi:10.1108/09574090610717509Kim, W., Chung, M. J., Qureshi, K., & Choi, Y. K. (2006). WSCPC: An architecture using semantic web services for collaborative product commerce. Computers in Industry, 57(8-9), 787-796. doi:10.1016/j.compind.2006.04.007Ku, K.-C., Kao, H.-P., & Gurumurthy, C. K. (2007). Virtual inter-firm collaborative framework—An IC foundry merger/acquisition project. Technovation, 27(6-7), 388-401. doi:10.1016/j.technovation.2007.02.010LEE, J., GRUNINGER, M., JIN, Y., MALONE, T., TATE, A., YOST, G., & OTHER MEMBERS OF THE PIF WORKING GROUP. (1998). The Process Interchange Format and Framework. The Knowledge Engineering Review, 13(1), 91-120. doi:10.1017/s0269888998001015Lee, J., Chae, H., Kim, C.-H., & Kim, K. (2009). Design of product ontology architecture for collaborative enterprises. Expert Systems with Applications, 36(2), 2300-2309. doi:10.1016/j.eswa.2007.12.042Liu, J., Zhang, S., & Hu, J. (2005). A case study of an inter-enterprise workflow-supported supply chain management system. Information & Management, 42(3), 441-454. doi:10.1016/j.im.2004.01.010Marques, D. M. N., & Guerrini, F. M. (2011). Reference model for implementing an MRP system in a highly diverse component and seasonal lean production environment. Production Planning & Control, 23(8), 609-623. doi:10.1080/09537287.2011.572469Mula, J., Peidro, D., & Poler, R. (2010). The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand. International Journal of Production Economics, 128(1), 136-143. doi:10.1016/j.ijpe.2010.06.007Murata, T. (1989). Petri nets: Properties, analysis and applications. Proceedings of the IEEE, 77(4), 541-580. doi:10.1109/5.24143Noran, O. (2003). An analysis of the Zachman framework for enterprise architecture from the GERAM perspective. Annual Reviews in Control, 27(2), 163-183. doi:10.1016/j.arcontrol.2003.09.002Olorunniwo, F. O., & Li, X. (2010). Information sharing and collaboration practices in reverse logistics. Supply Chain Management: An International Journal, 15(6), 454-462. doi:10.1108/13598541011080437Recker, J., Rosemann, M., Indulska, M., … Green, P. (2009). Business Process Modeling- A Comparative Analysis. Journal of the Association for Information Systems, 10(04), 333-363. doi:10.17705/1jais.00193Rodriguez, K., & Al-Ashaab, A. (2005). Knowledge web-based system architecture for collaborative product development. Computers in Industry, 56(1), 125-140. doi:10.1016/j.compind.2004.07.004Romero, F., Company, P., Agost, M.-J., & Vila, C. (2008). Activity modelling in a collaborative ceramic tile design chain: an enhanced IDEF0 approach. Research in Engineering Design, 19(1), 1-20. doi:10.1007/s00163-007-0040-zSandberg, E. (2007). Logistics collaboration in supply chains: practice vs. theory. The International Journal of Logistics Management, 18(2), 274-293. doi:10.1108/09574090710816977Spekman, R. E., & Carraway, R. (2006). Making the transition to collaborative buyer–seller relationships: An emerging framework. Industrial Marketing Management, 35(1), 10-19. doi:10.1016/j.indmarman.2005.07.002Stevens, W. P., Myers, G. J., & Constantine, L. L. (1974). Structured design. IBM Systems Journal, 13(2), 115-139. doi:10.1147/sj.132.0115Ulieru, M. (2000). A multi-resolution collaborative architecture for web-centric global manufacturing. Information Sciences, 127(1-2), 3-21. doi:10.1016/s0020-0255(00)00026-8Van der Aalst, W. M. P. (1999). Formalization and verification of event-driven process chains. Information and Software Technology, 41(10), 639-650. doi:10.1016/s0950-5849(99)00016-6Zachman, J. A. (1987). A framework for information systems architecture. IBM Systems Journal, 26(3), 276-292. doi:10.1147/sj.263.0276Zapp, M., Forster, C., Verl, A., & Bauernhansl, T. (2012). A Reference Model for Collaborative Capacity Planning Between Automotive and Semiconductor Industry. Procedia CIRP, 3, 155-160. doi:10.1016/j.procir.2012.07.028Zeng, Y., Wang, L., Deng, X., Cao, X., & Khundker, N. (2012). Secure collaboration in global design and supply chain environment: Problem analysis and literature review. Computers in Industry, 63(6), 545-556. doi:10.1016/j.compind.2012.05.00

Framework For Effective Resilience Managmenet Of Complex Supply Networks

In today\u27s environment with high global and complex supply chains for engineered products, the ability to assess and manage the resilience of supply chains is not a luxury but a fundamental prerequisite for business continuity and success. This is particularly true for firms with deep-tier supply chains, such as the automotive original equipment manufacturers (OEMs) and their suppliers. Automotive supply networks are particularly facing growing challenges due to their complexity, globalization, economic volatility, rapidly changing technologies, regulations, and environmental/political shocks. These risks and challenges can disrupt and halt operations in any section of the supply network. Given that supply chains have become quite lean in the 21st century with relatively little slack, the COVID-19 pandemic has fully exposed these vulnerabilities. According to Allianz\u27s Business Risk Report from 2014, half of all supply chain disruptions stemming from tier-2 and tier-3 suppliers. However, the industry\u27s supply network assessment practice is primarily limited to immediate (i.e., tier-1 ) suppliers with no real consideration for the deep-tiers. The added complication due to poor supplier relations is that there is no visibility to the upstream deeper-tiers of the supply network, which could lead to severe vulnerabilities and impose massive disruption costs. Our research goal is to enhance the resilience of deep-tier automotive supply networks through improved resilience assessment and management mechanisms. In this collaborative study with a global automotive OEM (Ford Motor Company), we seek to develop methods to assess and manage the resilience of deep-tier supply networks. This research considers the multi-dimensional nature of resilience management, focusing on metrics around cost efficiency, effective inventory management, demand fulfillment, capacity management, and delivery performance. We develop and evaluate our proposed resilience assessment and management framework with a real case study supply network for an automotive climate control system. The supply network contains 20 firms (nodes) located in various global regions and 21 connections (edges) between firms. The network includes three tiers of suppliers with different transportation modes, making the network a rich illustrative example for proposed resilience assessment and management methods and analysis. All inventory and shipping policies with related parameters have been defined and set for each supplier and their connections. The proposed resilience assessment framework relies on discrete-event simulation for effectiveness; computational efficiency is maintained by relying on modern open-source packages for modeling, optimization, and analysis. The framework starts by generating a digital supply network model that includes the focal firm and its suppliers and deeper-tiers based on the available visibility. Disruption scenarios, including disruption sources, frequency, and severity, are then efficiently generated using private and public regional risk sources. For illustrative purposes, we primarily relied on public secondary data sources. The secondary regional risk indices that we relied upon aggregate political, economic, legal, operational, and security risks for the given region. Finally, the digital supply network is simulated with an adequate number of replications for reliable assessment. In this research, discrete-event simulation is implemented using NetworkX and SimPy Python packages. We employ the network analysis techniques combined with discrete-event simulation informed by secondary data sources for improving the assessment framework. Our resilience assessment results confirm that visibility into the deeper-tiers of the supply network (through primary or secondary data sources) leads to a more accurate network resilience assessment. Finally, we offer a global sensitivity analysis procedure to determine the supply network players, parameters, and policies that most influence the network performance. We also propose an effective resilience management framework that efficiently leverages simulation-based optimization. For illustrative purposes, we considered the mitigation strategies typical in the automotive industry, such as dual sourcing, reserve capacities (at primary or secondary suppliers), and contracts with backup suppliers besides carrying safety stock. Sourcing and transportation mode decisions can be easily incorporated into the framework. The method seeks to minimize the cost of risk mitigation strategies while attaining the target resilience. The framework is flexible and can entertain other objectives and constraints. Given that simulation-based optimization methods can be computationally expensive, we employ surrogate models that relate supply network resilience performance to network design parameters within our mathematical programming formulation. Without loss of generality, the surrogate models are based on linear regression models that define the relationship between the focal firm and tier-1 suppliers\u27 resilience levels and network design decision variables. The imperfections of the regression models are accounted for in the formulation through constraints with slack (function of the RMSE of the regression model). We demonstrate that optimal resilience management would stem from jointly allocating safety buffers (e.g., capacity, inventory levels) across the network and not by independently applying a simplistic/static set of rules for all nodes/arcs. Our validation experiments with a real-world case study informed by secondary data from public data sources confirm the effectiveness and efficiency of the proposed supply network resilience management method

Logistics Guideline for Youth to Business Forum event of AIESEC in the Nordic countries

This is a project-oriented thesis, of which product is a logistics guideline for Youth to Busi-ness Forum event of AIESEC in the Nordic countries. The product of this thesis will help the organization in planning and organizing Youth to Business Forum event and streamline their preparation process. Youth to Business Forum is an event initiated by AIESEC, a youth run organization that focus on developing leadership. The event aims to bring together youth and businesses in a unique dialogue through interactions that generate actionable ideas for youth and society. The project started in August 2014 and ended in February 2015. The thesis consists of three parts: theoretical framework, research, and the logistics guideline. The theoretical framework is based on event management and supply chain management. The aspect of event logistics is the main focus in the framework with the support the pur-chasing and service process theories. In the research, qualitative research is conducted with AIESEC in Finland, Sweden, and Denmark to gain understanding of organizing pro-cess in different Nordic countries. Afterward, the logistics guideline is written from theoretical framework, research’s out-comes, and experience of the author. As a result, the final product is beyond satisfaction to AIESEC organization

Hybrid Simulation-based Planning Framework for Agri-Fresh Produce Supply Chain

The ever-increasing demand for fresh and healthy products raises the economic importance of managing Agri-Fresh Produce Supply Chain (AFPSC) effectively. However, the literature review has indicated that many challenges undermine efficient planning for AFPSCs. Stringent regulations on production and logistics activities, production seasonality and high yield variations (quantity and quality), and products vulnerability to multiple natural stresses, alongside with their critical shelf life, impact the planning process. This calls for developing smart planning and decision-support tools which provides higher efficiency for such challenges. Modelling and simulation (M&S) approaches for AFPSC planning problems have a proven record in offering safe and economical solutions. Increase in problem complexity has urged the use of hybrid solutions that integrate different approaches to provide better understanding of the system dynamism in an environment characterised by multi-firm and multi-dimensional relationships. The proposed hybrid simulation-based planning framework for AFPSCs has addressed internal decision-making mechanisms, rules and control procedures to support strategic, tactical and operational planning decisions. An exploratory study has been conducted using semi-structured interviews with twelve managers from different agri-fresh produce organisations. The aim of this study is to understand management practices regarding planning and to gain insights on current challenges. Discussions with managers on planning issues such as resources constraints, outsourcing, capacity, product sensitivity, quality, and lead times have formed the foundation of process mapping. As a result, conceptual modelling process is then used to model supply chain planning activities. These conceptual models are inclusive and reflective to system complexity and decision sensitivity. Verification of logic and accuracy of the conceptual models has been done by few directors in AFPSC before developing a hybrid simulation model. Hybridisation of Discrete Event Simulation (DES), System Dynamics (SD), and Agent-Based Modelling (ABM) has offered flexibility and precision in modelling this complex supply chain. DES provides operational models that include different entities of AFPSC, and SD minds investments decisions according to supply and demand implications, while ABM is concerned with modelling variations of human behaviour and experience. The proposed framework has been validated using Table Grapes Supply Chain (TGSC) case study. Decision makers have appreciated the level of details included in the solution at different planning levels (i.e., operational, tactical and strategic). Results show that around 58% of wasted products can be saved if correct hiring policy is adopted in the management of seasonal labourer recruitment. This would also factor in more than 25% improved profits at packing house entity. Moreover, an anticipation of different supply and demand scenarios demonstrated that inefficiency of internal business processes might undermine the whole business from gaining benefits of market growth opportunities