A Real-Time Service-Oriented Architecture for Industrial Automation

Industrial automation platforms are experiencing a paradigm shift. New technologies are making their way in the area, including embedded real-time systems, standard local area networks like Ethernet, Wi-Fi and ZigBee, IP-based communication protocols, standard service oriented architectures (SOAs) and Web services. An automation system will be composed of flexible autonomous components with plug & play functionality, self configuration and diagnostics, and autonomic local control that communicate through standard networking technologies. However, the introduction of these new technologies raises important problems that need to be properly solved, one of these being the need to support real-time and quality-of-service (QoS) for real-time applications. This paper describes a SOA enhanced with real-time capabilities for industrial automation. The proposed architecture allows for negotiation of the QoS requested by clients from Web services, and provides temporal encapsulation of individual activities. This way, it is possible to perform an a priori analysis of the temporal behavior of each service, and to avoid unwanted interference among them. After describing the architecture, experimental results gathered on a real implementation of the framework (which leverages a soft real-time scheduler for the Linux kernel) are presented, showing the effectiveness of the proposed solution. The experiments were performed on simple case studies designed in the context of industrial automation applications

GWpilot: Enabling multi-level scheduling in distributed infrastructures with GridWay and pilot jobs

Current systems based on pilot jobs are not exploiting all the scheduling advantages that the technique offers, or they lack compatibility or adaptability. To overcome the limitations or drawbacks in existing approaches, this study presents a different general-purpose pilot system, GWpilot. This system provides individual users or institutions with a more easy-to-use, easy-toinstall, scalable, extendable, flexible and adjustable framework to efficiently run legacy applications. The framework is based on the GridWay meta-scheduler and incorporates the powerful features of this system, such as standard interfaces, fair-share policies, ranking, migration, accounting and compatibility with diverse infrastructures. GWpilot goes beyond establishing simple network overlays to overcome the waiting times in remote queues or to improve the reliability in task production. It properly tackles the characterisation problem in current infrastructures, allowing users to arbitrarily incorporate customised monitoring of resources and their running applications into the system. This functionality allows the new framework to implement innovative scheduling algorithms that accomplish the computational needs of a wide range of calculations faster and more efficiently. The system can also be easily stacked under other software layers, such as self-schedulers. The advanced techniques included by default in the framework result in significant performance improvements even when very short tasks are scheduled

Production Scheduling

Generally speaking, scheduling is the procedure of mapping a set of tasks or jobs (studied objects) to a set of target resources efficiently. More specifically, as a part of a larger planning and scheduling process, production scheduling is essential for the proper functioning of a manufacturing enterprise. This book presents ten chapters divided into five sections. Section 1 discusses rescheduling strategies, policies, and methods for production scheduling. Section 2 presents two chapters about flow shop scheduling. Section 3 describes heuristic and metaheuristic methods for treating the scheduling problem in an efficient manner. In addition, two test cases are presented in Section 4. The first uses simulation, while the second shows a real implementation of a production scheduling system. Finally, Section 5 presents some modeling strategies for building production scheduling systems. This book will be of interest to those working in the decision-making branches of production, in various operational research areas, as well as computational methods design. People from a diverse background ranging from academia and research to those working in industry, can take advantage of this volume

Scheduling Algorithms: Challenges Towards Smart Manufacturing

Collecting, processing, analyzing, and driving knowledge from large-scale real-time data is now realized with the emergence of Artificial Intelligence (AI) and Deep Learning (DL). The breakthrough of Industry 4.0 lays a foundation for intelligent manufacturing. However, implementation challenges of scheduling algorithms in the context of smart manufacturing are not yet comprehensively studied. The purpose of this study is to show the scheduling No.s that need to be considered in the smart manufacturing paradigm. To attain this objective, the literature review is conducted in five stages using publish or perish tools from different sources such as Scopus, Pubmed, Crossref, and Google Scholar. As a result, the first contribution of this study is a critical analysis of existing production scheduling algorithms\u27 characteristics and limitations from the viewpoint of smart manufacturing. The other contribution is to suggest the best strategies for selecting scheduling algorithms in a real-world scenario