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Supply Chain and Logistics Institute

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    Rethinking the Warehouse: Urban Space and Economy in an Age of Smart Logistics
    ( 2019-01-16) Leigh, Nancey Greene ; Georgia Institute of Technology. Supply Chain and Logistics Institute ; Georgia Institute of Technology. School of City and Regional Planning
    Urban logistics automation is collapsing traditional boundaries between storage and delivery, extending the warehouse presence in the built environment. At the same time, the growth of e-commerce combined with logistics' need to avoid pauses or "friction" means that unprecedented volumes of goods are in near constant motion. This talk explores the potential of e-commerce driven changes to supply chain logistics, as well as consumer and business purchasing patterns, to alter the pattern of warehousing and more within metropolitan areas. There are a broad range of accompanying impacts for urban and local economic development. These include impacts on retail stores, warehouses, land-uses, transportation networks, workforce, policy and regulations (e.g., zoning). They are distinguishable by whether they impact most the "last-mile" aspect of supply chain and logistics, or the larger supply chain network linked to distribution and fulfillment centers.
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    Digital Twin Design Requirements for Durable Goods Distribution in Physical Internet
    (Georgia Institute of Technology, 2021-06) Campos, Miguel ; Derhami, Shahab ; McGinnis, Leon F. ; Montreuil, Benoit ; Barenji, Ali ; Georgia Institute of Technology. Physical Internet Center ; Georgia Institute of Technology. H. Milton Stewart School of Industrial & Systems Engineering ; Binghamton University. School of Management
    Today the practice for distributing large products manufactured at few original equipment manufacturers (OEMs) consists of a dedicated Point-to-Point (PtP) logistics system, typically requiring long haul transport from the factory to the wholesale destination. A growing problem is the shortage of commercial drivers willing to be away from home for several days to move products cross-country. Hub relay network logistics systems are an alternative solution to P2P logistics systems that allow reducing drivers' away-from-home times. Operating a relay-based logistics system requires accounting for multiple interrelated operational decisions that become more complicated as the system becomes larger and encompasses more players. To deal with such complexity we propose utilizing a digital twin of the distribution and logistics system as a decision-making support tool to manage the system and make operational decisions efficiently. This paper explores the design and assessment of a hyperconnected relay network of transport hubs supporting the movement of durable goods from factory to wholesale destinations. It describes requirements and challenges in developing and implementing a digital twin for such systems.
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    Launched by Disruption
    ( 2019-03-13) Amling, Alan ; Georgia Institute of Technology. Supply Chain and Logistics Institute ; United Parcel Service
    E-commerce, globalization and urbanization, combined with new technologies and business models, are disrupting industry stalwarts. Today, no company is immune from disruption. How should companies respond? Can disruption be a launching pad to a better future? Learn how UPS is staying ahead of disruption and thriving using the example of 3D printing, a game-changing technology that represents both challenge and opportunity for companies around the globe. Lessons learned will be shared.
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    Supply Chain Innovation Showcase
    ( 2018-09-26) Noble, Paul ; Ruff, Amari ; Georgia Institute of Technology. Supply Chain and Logistics Institute ; Autit ; Sudu Logistics Inc.
    A special session where two early stage companies will talk individually about their unique characteristics/problems solved. Amari Ruff from Sudu will present "How startups are pushing the Future of Transportation" to discuss how technology is making its way into the transportation industry and changing the way large corporations do business. Paul Noble from Autit will present "The Intelligent Manufacturing Enterprise" where we will discuss the opportunities for frontier technologies (AI/ML) to enhance Legacy ERP platforms and how Autit is leading the way with data harmonization and predictive inventory for parts in manufacturing supply chains.
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    Predictive Analytics within the Service Supply Chain
    ( 2017-03-29) Gebraeel, Nagi ; Georgia Institute of Technology. Supply Chain and Logistics Institute ; Georgia Institute of Technology. School of Industrial and Systems Engineering
    The Stewart School of Industrial and Systems Engineering at Georgia Tech established the Center for Predictive Analytics and Real-Time Optimization. (PARO). The center focuses on two main thrust areas. The first thrust area focuses on developing Predictive Analytic tools capable of synthesizing and extracting information from multi-stream sensor signals to predict future performance of complex engineering systems. The second thrust area deals with the development of real-time enhanced optimization models that compute optimal decision by leveraging the information embedded in the data. The development of modern methodologies allow for efficient updating when information changes as well as automatic model calibration using techniques from machine learning, information theory, and statistics. Housed in the Supply Chain and Logistics Institute, the Center for Predictive Analytics and Real-Time Optimization brings together experts from various disciplines. Drs. Gebraeel, Kvam, Paynabar, Pokutta, Ramudhin and Shi provide expertise in Data Mining and Statistical Analysis, Optimization, Diagnostics and Prognostics, Supply Chain, and Reliability, with domain expertise in the following industrial sectors; Automotive, Energy, Logistics, Airlines, Steel, Nanomanufacturing, Wind Power, and others. We provide various types of industries with a vehicle for addressing their problems through a single point of contact using a problem-driven approach.
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    Physical Internet: Concept, Research and Innovation
    (Georgia Institute of Technology, 2017-02-22) Montreuil, Benoit ; Georgia Institute of Technology. Supply Chain and Logistics Institute ; Georgia Institute of Technology. School of Industrial and Systems Engineering
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    Design of a Simulation-Based Experiment for Assessing the Relevance of the Physical Internet Concept for Humanitarian Supply Chains
    (Georgia Institute of Technology, 2021-06) Grest, Manon ; Inan, Mahmut Metin ; Cohen, Yaarit M. ; Barenji, Ali ; Dahan, Mathieu ; Lauras, Matthieu ; Montreuil, Benoit ; Center of Industrial Engineering, University of Toulouse, IMT Mines Albi, France ; Georgia Institute of Technology. Physical Internet Center ; Georgia Institute of Technology. Supply Chain and Logistics Institute ; Georgia Institute of Technology. H. Milton Stewart School of Industrial & Systems Engineering ; Georgia Institite of Technology. Center for Health and Humanitarian Systems
    The challenges faced in delivering relief items to victims of natural disasters and the growing external pressures urge humanitarian supply chain organizations to initiate some change. In this regard, the physical internet concept can offer a paradigm shift in relief organization and resource mobilization. To convince humanitarian actors to embrace this path, we propose a rigorous methodology leveraging a prototypical agent-oriented discrete-events simulator built within the AnyLogic platform, to conduct scientific experiments enabling to investigate the suitability and relevance of PI concepts for HSCs by systematically quantifying their benefits and drawbacks on HSC performance, sustainability, and resilience. We provide preliminary experimental results contrasting the baseline shaped by the current HSC structures, behaviors and practices, notably relative to sourcing, transporting, and warehousing, with those of hyperconnected HSCs in line with the Physical Internet at distinct degrees of maturity. In the experiment, we study past disaster scenarios that occurred in Indonesia and response efforts under different behaviors simulated with this platform. Initial results show that PI concepts are smoothly fitted to HSCs and the performance of hyperconnected HSCs is better than the current baseline.
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    Scalable On-demand Mobility Services
    ( 2018-11-14) Van Hentenryck, Pascal ; Georgia Institute of Technology. Supply Chain and Logistics Institute ; Georgia Institute of Technology. School of Industrial and Systems Engineering
    The convergence of several technology enablers, including ubiquitous connectivity, autonomous vehicles, and sophisticated analytics, provides unique opportunities to fundamentally transform mobility in the next decade. Ride-sourcing services have already modernized taxi services but they have also increased congestion and widened inequalities in accessibility. This talk looks at mobility from a logistics and supply chain angle and presents novel on-demand mobility services that have the potential to be scalable, and sustainable, handling both the first/last mile problem and congestion. Case studies will also be presented.
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    Enhancing Logistics Demand Prediction Accuracy Through Client–Vendor Provider Hyperconnected Data Ensembles
    (Georgia Institute of Technology, 2021-06) Pan, Xinyue ; Pothen, Ashwin ; Boerger, Jana ; Wang, He ; Montreuil, Benoit ; Georgia Institute of Technology. Physical Internet Center ; Georgia Institute of Technology. Supply Chain and Logistics Institute ; Georgia Institute of Technology. H. Milton Stewart School of Industrial & Systems Engineering
    In this paper, we present a hyperconnected data ensemble framework under the Physical Internet (PI) paradigm. As the current world is more volatile, uncertain, complex and ambiguous than before, it is well known that today’s logistics and supply chain management (LSCM) is facing greater difficulties and the idea of PI is introduced as a solution to the logistics sustainability grand challenge. PI aims to achieve significant logistics system efficiency and sustainability improvement through universal interconnectivity and smart open coordination. Meanwhile, PI will facilitate data sharing among supply chain parties. Instead of traditional data sharing by integrating datasets in common cases, we suppose that the hyperconnected data ensembles require as minimal data as possible. With the utilization of aggregated information, such as the overall activity forecast, the hyperconnected data ensembles can enhance the accuracy of the logistic demand prediction while preserving data privacy. A framework of logistics demand prediction with hyperconnected data ensembles is established and results of some experiments conducted based on the framework support our hypothesis that the demand prediction accuracy can be increased by integrating the forecast data that clients are willing to provide.
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    Advances in Last Mile Logistics
    ( 2017-04-26) Erera, Alan L. ; Savelsbergh, Martin W. P. ; Georgia Institute of Technology. Supply Chain and Logistics Institute ; Georgia Institute of Technology. School of Industrial and Systems Engineering