Development of an Industrial Internet of Things (IIoT) based Smart Robotic Warehouse Management System

According to data of Census and Statistics Department, freight transport and storage services contributed to 90% of the employment of logistics sector in the period from 2010 to 2014. Traditional warehouse operations in Hong Kong are labor-intensive without much automation. With the rapid increasing transaction volume through multi-channel, the preference for next-day delivery service has been increasing. As a result, 3rd party logistics providers have realized the importance of operational efficiency. With the advent of Industry 4.0 emerging technologies including Autonomous Robots, Industrial Internet of Things (IIoT), Cloud Computing, etc., a smart robotic warehouse management system is proposed as it redefines the warehouse put-away and picking operations from man-to-goods to goods-to-man using autonomous mobile robots. This paper aims to develop and implement an IIoT-based smart robotic warehouse system for managing goods and autonomous robots, as well as to make use of the autonomous mobile robots to deliver the goods automatically for put-away and picking operations. The significance of the paper is to leverage the Industry 4.0 emerging technologies to implement the concept of smart warehousing for better utilization of floor space and labor force so as to improve logistics operational efficiency

A WOA-based optimization approach for task scheduling in cloud Computing systems

Task scheduling in cloud computing can directly affect the resource usage and operational cost of a system. To improve the efficiency of task executions in a cloud, various metaheuristic algorithms, as well as their variations, have been proposed to optimize the scheduling. In this work, for the first time, we apply the latest metaheuristics WOA (the whale optimization algorithm) for cloud task scheduling with a multiobjective optimization model, aiming at improving the performance of a cloud system with given computing resources. On that basis, we propose an advanced approach called IWC (Improved WOA for Cloud task scheduling) to further improve the optimal solution search capability of the WOA-based method. We present the detailed implementation of IWC and our simulation-based experiments show that the proposed IWC has better convergence speed and accuracy in searching for the optimal task scheduling plans, compared to the current metaheuristic algorithms. Moreover, it can also achieve better performance on system resource utilization, in the presence of both small and large-scale tasks

A flexible platform for intermodal transportation and integrated logistics

This paper proposes an application of Information and Communications Technology (ICT) tools and Internet of Things to support intermodal transport and integrated logistics. In particular, the design and development of a new ICT platform is presented in order to facilitate the connectivity of the logistics systems, applications or objects from stakeholders to any logistics collaborative environment. The proposed platform aims to i) provide technological solutions to enhance and simplify collaboration among actors along the supply chain; ii) adopt and provide core functionalities to improve, optimise and automate transport and logistics operations within supply collaborations; iii) simplify information exchange within an integrated security framework. Finally, we show a case study in order to enlighten the effectiveness of the proposed ICT platform

An Edge Computing Based Smart Healthcare Framework for Resource Management

The revolution in information technologies, and the spread of the Internet of Things (IoT) and smart city industrial systems, have fostered widespread use of smart systems. As a complex, 24/7 service, healthcare requires efficient and reliable follow-up on daily operations, service and resources. Cloud and edge computing are essential for smart and efficient healthcare systems in smart cities. Emergency departments (ED) are real-time systems with complex dynamic behavior, and they require tailored techniques to model, simulate and optimize system resources and service flow. ED issues are mainly due to resource shortage and resource assignment efficiency. In this paper, we propose a resource preservation net (RPN) framework using Petri net, integrated with custom cloud and edge computing suitable for ED systems. The proposed framework is designed to model non-consumable resources and is theoretically described and validated. RPN is applicable to a real-life scenario where key performance indicators such as patient length of stay (LoS), resource utilization rate and average patient waiting time are modeled and optimized. As the system must be reliable, efficient and secure, the use of cloud and edge computing is critical. The proposed framework is simulated, which highlights significant improvements in LoS, resource utilization and patient waiting time

Software framework for the development of context-aware reconfigurable systems

In this project we propose a new software framework for the development of context-aware and secure controlling software of distributed reconfigurable systems. Context-awareness is a key feature allowing the adaptation of systems behaviour according to the changing environment. We introduce a new definition of the term “context” for reconfigurable systems then we define a new context modelling and reasoning approach. Afterwards, we define a meta-model of context-aware reconfigurable applications that paves the way to the proposed framework. The proposed framework has a three-layer architecture: reconfiguration, context control, and services layer, where each layer has its well-defined role. We define also a new secure conversation protocol between distributed trustless parts based on the blockchain technology as well as the elliptic curve cryptography. To get better correctness and deployment guarantees of applications models in early development stages, we propose a new UML profile called GR-UML to add new semantics allowing the modelling of probabilistic scenarios running under memory and energy constraints, then we propose a methodology using transformations between the GR-UML, the GR-TNCES Petri nets formalism, and the IEC 61499 function blocks. A software tool implementing the methodology concepts is developed. To show the suitability of the mentioned contributions two case studies (baggage handling system and microgrids) are considered.In diesem Projekt schlagen wir ein Framework für die Entwicklung von kontextbewussten, sicheren Anwendungen von verteilten rekonfigurierbaren Systemen vor. Kontextbewusstheit ist eine Schlüsseleigenschaft, die die Anpassung des Systemverhaltens an die sich ändernde Umgebung ermöglicht. Wir führen eine Definition des Begriffs ``Kontext" für rekonfigurierbare Systeme ein und definieren dann einen Kontextmodellierungs- und Reasoning-Ansatz. Danach definieren wir ein Metamodell für kontextbewusste rekonfigurierbare Anwendungen, das den Weg zum vorgeschlagenen Framework ebnet. Das Framework hat eine dreischichtige Architektur: Rekonfigurations-, Kontextkontroll- und Dienste-Schicht, wobei jede Schicht ihre wohldefinierte Rolle hat. Wir definieren auch ein sicheres Konversationsprotokoll zwischen verteilten Teilen, das auf der Blockchain-Technologie sowie der elliptischen Kurven-Kryptographie basiert. Um bessere Korrektheits- und Einsatzgarantien für Anwendungsmodelle zu erhalten, schlagen wir ein UML-Profil namens GR-UML vor, um Semantik umzufassen, die die Modellierung probabilistischer Szenarien unter Speicher- und Energiebeschränkungen ermöglicht. Dann schlagen wir eine Methodik vor, die Transformationen zwischen GR-UML, dem GR-TNCES-Petrinetz-Formalismus und den IEC 61499-Funktionsblöcken verwendet. Es wird ein Software entwickelt, das die Konzepte der Methodik implementiert. Um die Eignung der genannten Beiträge zu zeigen, werden zwei Fallstudien betrachtet

Checking Data-Flow Errors Based on The Guard-Driven Reachability Graph of WFD-Net

In order to guarantee the correctness of workflow systems, it is necessary to check their data-flow errors, e.g., missing data, inconsistent data, lost data and redundant data. The traditional Petri-net-based methods are usually based on the reachability graph. However, these methods have two flaws, i.e., the state space explosion and pseudo states. In order to solve these problems, we use WFD-nets to model workflow systems, and propose an algorithm for checking data-flow errors based on the guard-driven reachability graph (GRG) of WFD-net. Furthermore, a case study and some experiments are given to show the effectiveness and advantage of our method

TRACKING AND TRACING PORTAL FOR PROJECT LOGISTICS. A Review on the Interconnectivity of EDI, ERP and Cloud-based Systems

Tracking and tracing is becoming an essential factor for the success of project logistics. The safety and on-time arrival of shipments has become the primary concerns for manufacturing companies. The paper has introduced an overall approach to track and trace their deliveries from the starting point to the end-customer. Detail implementation of the whole solution will not be presented, yet each component in the system will be analyzed and discussed. Electronic Data Exchange (EDI) has been around for the last 30 years and is known for providing logistics companies a fast, reliable way to exchange information electronically. EDI, together with Enterprise Resource Planning (ERP), are considered as one of the remarkable emerging technologies which play an important role in supply chain management tracking network. Although the implementation of EDI and ERP systems is not straight forward and not easy to established, many logistics companies are still seeing this as a vital factor which can help companies to establish a sustainable development, increase productivity and reduce costs. In this paper, the interconnectivity of EDI, ERP, and cloud-based systems in tracking and tracing portal will be analyzed in business perspective in order to define what benefits it could achieve for logistics and supply chain management tracking network. A case study of Logistics Tracking Network (LogTrack) project is presented and examined with the view to implement, evaluate and manage the interconnectivity of EDI, ERP, and cloud-based systems in a practical point of view. Information collected from this research project will be analyzed to provide a list of mapping attributes between these systems and used as a basic for the further development of tracking and tracing portal. The impacts and implications of such system for managing the business logistics are discussed and presented in conclusion.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

LOGIC AND CONSTRAINT PROGRAMMING FOR COMPUTATIONAL SUSTAINABILITY

Computational Sustainability is an interdisciplinary field that aims to develop computational and mathematical models and methods for decision making concerning the management and allocation of resources in order to help solve environmental problems. This thesis deals with a broad spectrum of such problems (energy efficiency, water management, limiting greenhouse gas emissions and fuel consumption) giving a contribution towards their solution by means of Logic Programming (LP) and Constraint Programming (CP), declarative paradigms from Artificial Intelligence of proven solidity. The problems described in this thesis were proposed by experts of the respective domains and tested on the real data instances they provided. The results are encouraging and show the aptness of the chosen methodologies and approaches. The overall aim of this work is twofold: both to address real world problems in order to achieve practical results and to get, from the application of LP and CP technologies to complex scenarios, feedback and directions useful for their improvement

TRACKING AND TRACING PORTAL FOR PROJECT LOGISTICS. A Review on the Interconnectivity of EDI, ERP and Cloud-based Systems

Tracking and tracing is becoming an essential factor for the success of project logistics. The safety and on-time arrival of shipments has become the primary concerns for manufacturing companies. The paper has introduced an overall approach to track and trace their deliveries from the starting point to the end-customer. Detail implementation of the whole solution will not be presented, yet each component in the system will be analyzed and discussed. Electronic Data Exchange (EDI) has been around for the last 30 years and is known for providing logistics companies a fast, reliable way to exchange information electronically. EDI, together with Enterprise Resource Planning (ERP), are considered as one of the remarkable emerging technologies which play an important role in supply chain management tracking network. Although the implementation of EDI and ERP systems is not straight forward and not easy to established, many logistics companies are still seeing this as a vital factor which can help companies to establish a sustainable development, increase productivity and reduce costs. In this paper, the interconnectivity of EDI, ERP, and cloud-based systems in tracking and tracing portal will be analyzed in business perspective in order to define what benefits it could achieve for logistics and supply chain management tracking network. A case study of Logistics Tracking Network (LogTrack) project is presented and examined with the view to implement, evaluate and manage the interconnectivity of EDI, ERP, and cloud-based systems in a practical point of view. Information collected from this research project will be analyzed to provide a list of mapping attributes between these systems and used as a basic for the further development of tracking and tracing portal. The impacts and implications of such system for managing the business logistics are discussed and presented in conclusion.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Case Study on Utilizing Machine Learning in Corporate Default Risk Prediction : A practical Implementation to Credit Risk Management Process

The purpose of the case study is to create an in-house corporate default risk prediction model that outperforms the external corporate credit rating which the case company is currently using for this purpose. In addition, the study sets the framework for implementing the model into current system architecture and credit risk management process. The study consists of literature review and empirical analysis where the default prediction models are built and tested and the proposal for implementing the model into case company’s system architecture and processes is given. The data used in this study consists of historical financial figures & ratios, payment behaviour information and other background information of 2471 Finnish companies from period 2009-2017 of which 22,6% defaulted during this period. MissForest method was used in imputation of the missing values. The models used in this study are Multivariate Discriminant Analysis, Logistics Regression, Random Forest, CART, AdaBoost, Support Vector Machine and Neural Network. The dataset was split with 70/30 ratio to training and test set and 10-fold cross validation was used in training, feature selection and hyperparameter optimization for each model. Model performance was also tested over a two-year time horizon. The models’ performance was measured with ROC AUC & PR AUC and Brier Score. All the models overperformed the external credit rating with the selected metrics. The best performing model was the black box model Adaboost and the best performing white box model was the logistic regression with LASSO method used for the predictor variable selection