Sustainable supply chain management in the digitalisation era: The impact of Automated Guided Vehicles

Internationalization of markets and climate change introduce multifaceted challenges for modern supply chain (SC) management in the today's digitalisation era. On the other hand, Automated Guided Vehicle (AGV) systems have reached an age of maturity that allows for their utilization towards tackling dynamic market conditions and aligning SC management focus with sustainability considerations. However, extant research only myopically tackles the sustainability potential of AGVs, focusing more on addressing network optimization problems and less on developing integrated and systematic methodological approaches for promoting economic, environmental and social sustainability. To that end, the present study provides a critical taxonomy of key decisions for facilitating the adoption of AGV systems into SC design and planning, as these are mapped on the relevant strategic, tactical and operational levels of the natural hierarchy. We then propose the Sustainable Supply Chain Cube (S2C2), a conceptual tool that integrates sustainable SC management with the proposed hierarchical decision-making framework for AGVs. Market opportunities and the potential of integrating AGVs into a SC context with the use of the S2C2 tool are further discussed

Intelligent Autonomous Vehicles in digital supply chains: A framework for integrating innovations towards sustainable value networks

The principal objective of this research is to provide a framework that captures the main software architecture elements for developing highly customized simulation tools that support the effective integration of Intelligent Autonomous Vehicles (IAVs) in sustainable supply networks, as an emerging field in the operations management agenda. To that end, the study's contribution is fourfold including: (i) a review of software simulation tools and platforms used in assessing the performance of IAVs interlinked with sustainability ramifications in supply chain (SC) ecosystems, (ii) an integrated software framework for monitoring and assessing the sustainability performance of SCs defined by the utilisation of innovative IAVs in operations, (iii) a translation of the proposed SC framework into a corresponding software application through a robust five-stage stepwise process, and (iv) a demonstration of the developed software tool through its application on the case of an IAV system operating in a customisable warehouse model. Our analysis highlights the flexibility resulting from a decentralised software management architecture, thus enabling the dynamic reconfiguration of a SC network. In addition, the developed pilot simulation tool can assist operations managers in capturing the operational needs of facilities and assessing the performance of IAV systems while considering sustainability parameters

Agros: A robot operating system based emulation tool for agricultural robotics

This research aims to develop a farm management emulation tool that enables agrifood producers to effectively introduce advanced digital technologies, like intelligent and autonomous unmanned ground vehicles (UGVs), in real-world field operations. To that end, we first provide a critical taxonomy of studies investigating agricultural robotic systems with regard to: (i) the analysis approach, i.e., simulation, emulation, real-world implementation; (ii) farming operations; and (iii) the farming type. Our analysis demonstrates that simulation and emulation modelling have been extensively applied to study advanced agricultural machinery while the majority of the extant research efforts focuses on harvesting/picking/mowing and fertilizing/spraying activities; most studies consider a generic agricultural layout. Thereafter, we developed AgROS, an emulation tool based on the Robot Operating System, which could be used for assessing the efficiency of real-world robot systems in customized fields. The AgROS allows farmers to select their actual field from a map layout, import the landscape of the field, add characteristics of the actual agricultural layout (e.g., trees, static objects), select an agricultural robot from a predefined list of commercial systems, import the selected UGV into the emulation environment, and test the robot’s performance in a quasi-real-world environment. AgROS supports farmers in the ex-ante analysis and performance evaluation of robotized precision farming operations while lays the foundations for realizing “digital twins” in agriculture

Data-driven secure, resilient and sustainable supply chains: gaps, opportunities, and a new generalised data sharing and data monetisation framework

The increasing exposure of global supply chains to severe disruptions such as the ones related to the COVID-19 pandemic, clearly demonstrated the need for novel data-driven risk management paradigms that monetise data from internal and external stakeholders to support supply chain security, resilience, and sustainability. We first motivate the challenges that supply chains are facing under the new realities. We then provide a critical taxonomy of the relevant literature and identify gaps which include: (i) the impact of security on supply chain operations; (ii) cost effective resiliency strategies and practices; and (iii) the social and labour dimensions of sustainability. We then propose a new generalised framework that encompasses all the identified challenges, gaps in literature and in practice, and opportunities in supply chain management research. The proposed framework is validated through a real-world case study of the organic food supply chain. This validation further highlights the need for data-driven digital technologies that enable data collection and management, secure storage and effective data processing towards data monetisation for supply chain security, cost-competitive resilience, and sustainability across end-to-end operations

Intelligent autonomous vehicles in digital supply chains: From conceptualisation, to simulation modelling, to real-world operations

Purpose: The purpose of this paper is twofold: first, to discuss key challenges associated with the use of either simulation or real-world application of intelligent autonomous vehicles (IAVs) in supply network operations; and second, to provide a theoretical and empirical evidence-based methodological framework that supports the integrated application of conceptualisation, simulation, emulation and physical application of IAVs for the effective design of digital supply networks. Design/methodology/approach: First, this study performs a critical review of the extant literature to identify major benefits and shortcomings related to the use of either simulation modelling or real-word application of physical IAVs. Second, commercial and bespoke software applications, along with a three-dimensional validation and verification emulation tool, are developed to evaluate an IAV’s operations in a conceptual warehouse. Third, a commercial depth-sensor is used as a test bed in a physical setting. Findings: The results demonstrate that conceptual and simulation modelling should be initially used to explore alternative supply chain operations in terms of ideal performance while emulation tools and real-world IAV test beds are eminent in validating preferred digital supply chain design options. Research limitations/implications: The provided analysis framework was developed using literature evidence along with experimental work and research experience, without consulting any industry experts. In addition, this study was developed based on the application of a single physical device application as a test bed and, thus, the authors should further progress with the testing of a physical IAV in an industrial warehouse. Practical implications: The study provides bespoke simulation modelling and emulation tools that can be useful for supply chain practitioners in effectively designing network operations. Originality/value: This work contributes in the operations management field by providing both a multi-stage methodological framework and a practical “toolbox” for the proactive assessment and incorporation of IAVs in supply network operations

Intelligent autonomous vehicles in digital supply chains: From conceptualisation, to simulation modelling, to real-world operations

PurposeThe purpose of this paper is twofold: first, to discuss key challenges associated with the use of either simulation or real-world application of intelligent autonomous vehicles (IAVs) in supply network operations; and second, to provide a theoretical and empirical evidence-based methodological framework that supports the integrated application of conceptualisation, simulation, emulation and physical application of IAVs for the effective design of digital supply networks.Design/methodology/approachFirst, this study performs a critical review of the extant literature to identify major benefits and shortcomings related to the use of either simulation modelling or real-word application of physical IAVs. Second, commercial and bespoke software applications, along with a three-dimensional validation and verification emulation tool, are developed to evaluate an IAV’s operations in a conceptual warehouse. Third, a commercial depth-sensor is used as a test bed in a physical setting.FindingsThe results demonstrate that conceptual and simulation modelling should be initially used to explore alternative supply chain operations in terms of ideal performance while emulation tools and real-world IAV test beds are eminent in validating preferred digital supply chain design options.Research limitations/implicationsThe provided analysis framework was developed using literature evidence along with experimental work and research experience, without consulting any industry experts. In addition, this study was developed based on the application of a single physical device application as a test bed and, thus, the authors should further progress with the testing of a physical IAV in an industrial warehouse.Practical implicationsThe study provides bespoke simulation modelling and emulation tools that can be useful for supply chain practitioners in effectively designing network operations.Originality/valueThis work contributes in the operations management field by providing both a multi-stage methodological framework and a practical “toolbox” for the proactive assessment and incorporation of IAVs in supply network operations.This research has received funding from the Engineering and Physical Sciences Research Council (EPSRC) Reference No. EP/K02888X/1, Project Title: “Engineering Driven Sustainable Supply Networks - A UK/India Collaborative Study”, and the Advanced Manufacturing Supply Chain Initiative (AMSCI) Grant No. TS/L006529/1, Project Title: “ReMediES – Reconfiguring Medicines End-to-End Supply”

Industry 4.0: Sustainable material handling processes in industrial environments

Responding to the intensified shareholders’ pressure for economic growth, stringent health regulatory schemes and increased consumers’ environmental awareness Industry 4.0 and the Internet of Things (IoT) revolution provide opportunities for developing effective industrial applications that efficiently tackle the triple-helix sustainability challenges associated with operations in industrial systems. Our ongoing research demonstrates that Automated Guided Vehicles (AGVs) are a rapidly emerging research field with existing studies focusing more on economic ramifications by addressing network optimization and distribution problems, and less on developing integrated methodological approaches for promoting environmental and social sustainability. This study aims at motivating the role of AGVs as enablers of sustainability in modern manufacturing systems while focusing more on the environmental sustainability echelon. We first provide an overview of the updated AGVs’ capabilities in the Industry 4.0 era through reviewing successful case studies. The study focuses on material handling and manufacturing industries while it provides insights for approaching the process industries. Furthermore it indicates the economic, environmental and social aspects at the industrial environment and pinpoints critical KPIs of the system. Prospective research avenues and business opportunities for AGV systems that need to be considered by academicians and practitioners to foster the transition towards a more sustainable future are highlighted as well

Intelligent Autonomous Vehicles in digital supply chains: A framework for integrating innovations towards sustainable value networks

The principal objective of this research is to provide a framework that captures the main software architecture elements for developing highly customised simulation tools that support the effective integration of Intelligent Autonomous Vehicles (IAVs) in sustainable supply networks, as an emerging field in the operations management agenda. To that end, the study's contribution is fourfold including: (i) a review of software simulation tools and platforms used in assessing the performance of IAVs interlinked with sustainability ramifications in supply chain (SC) ecosystems, (ii) an integrated software framework for monitoring and assessing the sustainability performance of SCs defined by the utilisation of innovative IAVs in operations, (iii) a translation of the proposed SC framework into a corresponding software application through a robust five-stage stepwise process, and (iv) a demonstration of the developed software tool through its application on the case of an IAV system operating in a customisable warehouse model. Our analysis highlights the flexibility resulting from a decentralised software management architecture, thus enabling the dynamic reconfiguration of a SC network. In addition, the developed pilot simulation tool can assist operations managers in capturing the operational needs of facilities and assessing the performance of IAV systems while considering sustainability parameters

A Blockchain Framework for Containerized Food Supply Chains

Global agricultural trade flows demonstrated a three-fold growth during the past decade particularly in emerging economies. At the same time, global food scandals in conjunction with the spillover effects in economy and society highlight the unreliability of existing food tracking systems and the inefficiency in monitoring food quality and fraud incidents across global food supply chains (SCs). Blockchain technology (BCT), which has already been successfully applied on the financial industry to validate critical transactions, seems to be a promising option. This research investigates a two-stage containerized food SC by implementing a demonstrator application at the Hyperledger Fabric framework. The study findings indicates that on one hand BCT has entered its maturity phase while on the other hand its adoption in food SC operations could add significant value by authenticating critical parameters and providing enhanced traceability. At the same time, BCT enabled by other digital technologies could allow for the optimization of global food SCs. Thus, BCT constitutes a promising digital technology that provides the capability to food SC stakeholders to securely share information, enhance process control and traceability and prevent potential risks

Unmanned Ground Vehicles in Precision Farming Services: An Integrated Emulation Modelling Approach

Autonomous systems are a promising alternative for safely executing precision farming activities in a 24/7 perspective. In this context Unmanned Ground Vehicles (UGVs) are used in custom agricultural fields, with sophisticated sensors and data fusion techniques for real-time mapping and navigation. The aim of this study is to present a simulation software tool for providing effective and efficient farming activities in orchard fields and demonstrating the applicability of simulation in routing algorithms, hence increasing productivity, while dynamically addressing operational and tactical level uncertainties. The three dimensional virtual world includes the field layout and the static objects (orchard trees, obstacles, physical boundaries) and is constructed in the open source Gazebo simulation software while the Robot Operating System (ROS) and the implemented algorithms are tested using a custom vehicle. As a result a routing algorithm is executed and enables the UGV to pass through all the orchard trees while dynamically avoiding static and dynamic obstacles. Unlike existing sophisticated tools, the developed mechanism could accommodate an extensive variety of agricultural activities and could be transparently transferred from the simulation environment to real world ROS compatible UGVs providing user-friendly and highly customizable navigation