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

European supply chain study

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 71-77).Introduction: Supply chain management has been defined as, "..a set of approaches utilized to efficiently integrate suppliers, manufacturers, warehouses and stores, so that merchandise is produced and distributed at the right quantities, to the right locations and at the right time, in order to minimize system-wide costs.... satisfying service level requirements.. " -- ".. integration of activities ..through improved supply chain relationships to achieve sustainable competitive advantage.. " -- "..coordination and collaboration with channel partners.. coordination of process and activities.. " [53] "..from the ore mine to the trash can... the production and distribution network that encompasses the sourcing, manufacturing, transportation, commercialization, distribution, consumption, and disposal of goods.. " -- "...flow of requirement information from buyer to seller which triggers all later activities, the movement of goods from sellers to buyers, transfer of ownership rights from seller to buyer and payment from buyer to seller. " The above definitions offer a broad spectrum of supply chain orientation and management choices available to companies. They could vary from a transactional orientation that is focused on low cost acquisition; to one where stronger relationships are established with key suppliers and customers in an effort to optimize and capture synergies; onward to a partnership orientation that is focused on supporting mutual goals for a sustainable competitive advantage. Making the right choice is essential. It can have a significant impact on a company's balance sheet and income statement. GSCF and SCOR are two popular process frameworks in supply chain management [36]. Corporate strategy is the starting point of the GSCF framework, with the operational aspects of customer relationship management and supplier relationship management linked to the strategy. Its process metrics are related to EVA. On the other hand, the SCOR framework focuses on transactional efficiency by integrating operational activities such as purchasing, operations, and logistics. It benchmarks process metrics to improve operational efficiency.by Mohitkumar Puri.S.M

Holistic Environmental Performance and Sustainability in Global Logistics Hubs: An Exploratory Multiple Case Study

In recent years, the emergence of global logistics hubs (GLHs) has been on the rise, with these hubs playing a critical role in facilitating the smooth flow of global trade through their strategic location and functions that support global supply chains. Furthermore, GLHs provide benefits to the regions hosting them through the attraction of foreign investment, enhancement of education, and creation of job opportunities. However, there are limited research studies on GLHs suggesting a gap in the current knowledge on the concept, which requires further exploration. Additionally, the accumulation of the functions and activities of existing and emerging GLHs is resulting in extensive environmental impact. The environmental performance and sustainability of GLHs is a topic that requires further exploration, particularly in light of the climate emergency, which is an urgent and pressing issue that requires immediate action (IPCC, 2022). The transportation and logistics sector, of which GLHs are heavily dependent on, is a significant contributor to greenhouse gas emissions and other environmental impacts. Therefore, it is imperative that GLHs are developed and operated in a sustainable and responsible manner given the global concentration of operations and activities in a specific location. This research aims to address this need by exploring the concept of GLHs and their environmental performance and sustainability. Adopting an inductive qualitative research approach and a multiple case study research method, this study focuses on four diverse GLH case studies: Rotterdam, Antwerp, Liverpool, and Suez Canal Economic Zone (SCZone) GLHs. The aim of the research is to establish a comprehensive understanding of GLHs, their environmental performance, and sustainability for academic and industrial applications for emerging and fully developed GLHs. The research contributes to the gap in knowledge by providing an up-to-date and clear definition of GLHs, their primary stakeholders and their operations, and a multi-stage development model. Additionally, a holistic conceptual environmental performance measurement framework for GLHs encompassing their primary stakeholders is developed. The research also highlights the level of connection between stakeholders in GLHs, the governance structure, and environmental sustainability responsibility in GLHs. Furthermore, this study explores the factors that drive or impede environmental performance and sustainability in GLHs, and provides an illustration of these factors using a fishbone diagram

Cyber Security in the Maritime Industry: A Systematic Survey of Recent Advances and Future Trends

The paper presents a classification of cyber attacks within the context of the state of the art in the maritime industry. A systematic categorization of vessel components has been conducted, complemented by an analysis of key services delivered within ports. The vulnerabilities of the Global Navigation Satellite System (GNSS) have been given particular consideration since it is a critical subcategory of many maritime infrastructures and, consequently, a target for cyber attacks. Recent research confirms that the dramatic proliferation of cyber crimes is fueled by increased levels of integration of new enabling technologies, such as IoT and Big Data. The trend to greater systems integration is, however, compelling, yielding significant business value by facilitating the operation of autonomous vessels, greater exploitation of smart ports, a reduction in the level of manpower and a marked improvement in fuel consumption and efficiency of services. Finally, practical challenges and future research trends have been highlighted

Inferring Complex Activities for Context-aware Systems within Smart Environments

The rising ageing population worldwide and the prevalence of age-related conditions such as physical fragility, mental impairments and chronic diseases have significantly impacted the quality of life and caused a shortage of health and care services. Over-stretched healthcare providers are leading to a paradigm shift in public healthcare provisioning. Thus, Ambient Assisted Living (AAL) using Smart Homes (SH) technologies has been rigorously investigated to help address the aforementioned problems. Human Activity Recognition (HAR) is a critical component in AAL systems which enables applications such as just-in-time assistance, behaviour analysis, anomalies detection and emergency notifications. This thesis is aimed at investigating challenges faced in accurately recognising Activities of Daily Living (ADLs) performed by single or multiple inhabitants within smart environments. Specifically, this thesis explores five complementary research challenges in HAR. The first study contributes to knowledge by developing a semantic-enabled data segmentation approach with user-preferences. The second study takes the segmented set of sensor data to investigate and recognise human ADLs at multi-granular action level; coarse- and fine-grained action level. At the coarse-grained actions level, semantic relationships between the sensor, object and ADLs are deduced, whereas, at fine-grained action level, object usage at the satisfactory threshold with the evidence fused from multimodal sensor data is leveraged to verify the intended actions. Moreover, due to imprecise/vague interpretations of multimodal sensors and data fusion challenges, fuzzy set theory and fuzzy web ontology language (fuzzy-OWL) are leveraged. The third study focuses on incorporating uncertainties caused in HAR due to factors such as technological failure, object malfunction, and human errors. Hence, existing studies uncertainty theories and approaches are analysed and based on the findings, probabilistic ontology (PR-OWL) based HAR approach is proposed. The fourth study extends the first three studies to distinguish activities conducted by more than one inhabitant in a shared smart environment with the use of discriminative sensor-based techniques and time-series pattern analysis. The final study investigates in a suitable system architecture with a real-time smart environment tailored to AAL system and proposes microservices architecture with sensor-based off-the-shelf and bespoke sensing methods. The initial semantic-enabled data segmentation study was evaluated with 100% and 97.8% accuracy to segment sensor events under single and mixed activities scenarios. However, the average classification time taken to segment each sensor events have suffered from 3971ms and 62183ms for single and mixed activities scenarios, respectively. The second study to detect fine-grained-level user actions was evaluated with 30 and 153 fuzzy rules to detect two fine-grained movements with a pre-collected dataset from the real-time smart environment. The result of the second study indicate good average accuracy of 83.33% and 100% but with the high average duration of 24648ms and 105318ms, and posing further challenges for the scalability of fusion rule creations. The third study was evaluated by incorporating PR-OWL ontology with ADL ontologies and Semantic-Sensor-Network (SSN) ontology to define four types of uncertainties presented in the kitchen-based activity. The fourth study illustrated a case study to extended single-user AR to multi-user AR by combining RFID tags and fingerprint sensors discriminative sensors to identify and associate user actions with the aid of time-series analysis. The last study responds to the computations and performance requirements for the four studies by analysing and proposing microservices-based system architecture for AAL system. A future research investigation towards adopting fog/edge computing paradigms from cloud computing is discussed for higher availability, reduced network traffic/energy, cost, and creating a decentralised system. As a result of the five studies, this thesis develops a knowledge-driven framework to estimate and recognise multi-user activities at fine-grained level user actions. This framework integrates three complementary ontologies to conceptualise factual, fuzzy and uncertainties in the environment/ADLs, time-series analysis and discriminative sensing environment. Moreover, a distributed software architecture, multimodal sensor-based hardware prototypes, and other supportive utility tools such as simulator and synthetic ADL data generator for the experimentation were developed to support the evaluation of the proposed approaches. The distributed system is platform-independent and currently supported by an Android mobile application and web-browser based client interfaces for retrieving information such as live sensor events and HAR results