Research Problem Presentation - Research in Supply Chain Digital Twins
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Slide deck prepared for a post-graduate course ' ESM 600 - Research Methodology', introducing the research problem, aim, and objectives. Program: Masters in Engineering Systems Management Affiliation: American University of Sharjah, College of Engineering, Department of Industrial Engineering
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Research Problem Presentation - Research in Supply Chain Digital Twins
- 1. Digital Twin Technology for Cold Supply Chain Optimization: A Theoretical Framework Research Problem Presentation By: Group D
- 2. Outline INTRODUCTION, BACKGROUND & RATIONALE THE RESEARCH GAP STATEMENT OF THE RESEARCH PROBLEM AIM, OBJECTIVES & ANTICIPATED RESEARCH OUTCOMES RESEARCH QUESTIONS LIMITATIONS, ASSUMPTIONS & DELIMITATIONS PLAN OF WORK & TIME SCALE
- 3. Introduction & Background • Supply Chain • Network connecting (Company, suppliers, buyers). • Entities include: Producers, Vendors, Warehouses, Transportation companies, Distribution centers, and Retailers. • Examples: Amazon, DHL, Nike etc.… • Cold Supply Chain • Same concept & network. • Temp. controlled Products • Examples: fruits, milk, meat, vaccines.
- 4. Introduction & Background • Digital Twins • Digital replica of a physical object or system. • First implemented by NASA. • Implemented in Automotive, Manufacturing, & Healthcare Industries. • Digital twins are NOT Simulations! • Provide real time data. • Predict In-efficiencies & issues.
- 5. Rationale • The Ripple Effect • Caused by a disruption or issue in 1 part of the supply chain. • Lower revenues • Delivery delays • Market share losses • Drops in stock returns • Main source of Ripple Effect: • Lack of end-to-end visibility.
- 6. Solution Information Sharing! Applying IoT, Big Data, & Deep Learning. Create a Digital Twin of the Supply Chain. Benefits: Predictive Maintenance Contingency Plan Simulations Lower Financial Risk
- 7. The Research Gap • A global logistics leader (DHL) is already developing: • Material Digital Twins for packaging and containers • Shipments • Warehouses & Distribution Centers • Logistics Infrastructures DT of Global Supply Chain Network? Still largely an aspiration! “In logistics, the ultimate digital twin would be a model of an entire network including not just logistics assets but also oceans, railway lines, highways, streets, and customer homes and workplaces.” - Gesing, B., Kückelhaus, M., in DHL Trend Research, 2019
- 8. Statement of the Research Problem Optimization of Cold Supply Chains (SCs) is of utmost importance to manufacturers, distributors, retailers and end-consumers, as it results in delivering goods affordably to the market on time and in acceptable quality as well as creating profit for the companies along the SC. However, for optimization techniques to yield meaningful results, they require data which is complete, comprehensive, accurate and timely. Such high-quality data as well as high-processing power have become accessible in the recent times with the advent of new technologies, namely: IoT, Big Data Analytics, Artificial Intelligence, and Blockchain. These technologies can be leveraged to create a Digital Twin of a global SC network, which can then be used for monitoring, risk prediction, diagnostics, and simulation of contingency plans. Hence, this research presents a theoretical framework for integrating the said technologies to create a digital twin of an exemplary cold supply chain network and addresses the concerns that hinder SC companies from adopting Digital Twins.
- 9. The Research Aim & Objectives Develop a framework for applying Digital Twin (DT) technology to Cold Supply Chain in order to improve its efficiency and resilience without compromising product quality. Explore the applications of IoT sensing in Cold Supply Chain Investigate the applications of Blockchain Technology in Cold Supply Chain Identify appropriate Analytics, AI tools and algorithms to optimize the Cold Supply Chain Integrate proposed systems of IoT, Blockchain and AI into unified framework Critically examine the literature concerning the drawbacks of DT for a global supply chain network Suggest solutions to such drawbacks that hinder SC companies from adopting DT technology globally
- 10. Research Questions • Four Research Question 1. What data will be needed in order to implement DT in Cold SC? (Waffa) 2. How can Blockchain Technology be of use to Cold SCs? (Mahmoud) 3. How can Artificial Intelligence (AI) be used to handle risks and disruptions in the SC? (Arwa) 4. What are the drawbacks that hinder SC companies from adopting DT and the possible solutions to mitigate them? (Raed)
- 11. Research Questions • IoT (Sensors, electronic devices, controllers) Data Collection • Algorithms • Big Data analytics • Block Chain Data Analysis • Artificial Intelligence • Machine Learning Data Computation • Adoption Concerns • Solutions Evaluations
- 12. Research Focus • Integration of digital twin with emerging technologies • A theoretical framework to develop a digital twin of Supply Chain • Adaption Concerns • Address the issues regarding adaption of SC Digital Twin by Professional World • Propose solutions to eliminate or mitigate those issues
- 13. Preliminary Assumptions • Prices of Cloud storage and Cloud computing capabilities will continue to decrease • Blockchain technology will become accessible to enterprises in the next 5-10 years • Agents along the supply chain can (and would be willing to) collaborate and share necessary information and data for the DT to work • Agents will be willing to set up a shared fund to finance this project and share the installation, maintenance and operational costs
- 14. • Time • Resource • Expertise • Type of supply chain • Simple consumer products • Not consider of after-sales maintenance or reverse logistics • Not consider limitations of the IT infrastructure in storage and streaming Limitations & Delimitations Limitations Delimitations
- 15. Targeted Audience • Companies with huge SC network • Large Logistics Companies • Hospital Management • Pharmaceutical Companies
- 16. Anticipated Research Outcomes • Double shelf life for fresh agricultural produce, seafood, frozen food, etc. • Enforcing effective cold chain logistics • Reduce food spoilage by 30%-50% • Improve food distribution efficiency by 30%-50%
- 17. Beneficiaries Catering Companies Fresh Vegetable Companies Bakery Products companies Chicken, meat and fish providers Pharmaceuticals Floristry Companies
- 18. Time Scale & Plan of Work