Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0

Abstract

Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.     

The HORSE framework: A reference architecture for cyber-physical systems in hybrid smart manufacturing

In the Industry 4.0 era, manufacturers strive to remain competitive by using advanced technologies such as collaborative robots, automated guided vehicles, augmented reality support and smart devices. However, only if these technological advancements are integrated into their system context in a seamless way, they can deliver their full potential to a manufacturing organization. This integration requires a system architecture as a blueprint for positioning and interconnection of the technologies. For this purpose, the HORSE framework, resulting from the HORSE EU H2020 project, has been developed to act as a reference architecture of a cyber-physical system to integrate various Industry 4.0 technologies and support hybrid manufacturing processes, i.e., processes in which human and robotic workers collaborate. The architecture has been created using design science research, based on well-known software engineering frameworks, established manufacturing domain standards and practical industry requirements. The value of a reference architecture is mainly established by application in practice. For this purpose, this paper presents the application and evaluation of the HORSE framework in 10 manufacturing plants across Europe, each with its own characteristics. Through the physical deployment and demonstration, the framework proved its goal to be basis for the well-structured design of an operational smart manufacturing cyber-physical system that provides horizontal, cross-functional management of manufacturing processes and vertical control of heterogeneous technologies in work cells. We report on valuable insights on the difficulties to realize such systems in specific situations. The experiences form the basis for improved adoption, further improvement and extension of the framework. In sum, this paper shows how a reference architecture framework supports the structured application of Industry 4.0 technologies in manufacturing environments that so far have relied on more traditional digital technology.     

Towards sustainable industry 4.0: A green real-time IIoT multitask scheduling architecture for distributed 3D printing services

As the keystones of the personalized manufacturing, the Industrial Internet of Things (IIoT) consolidated with 3D printing pave the path for the era of Industry 4.0 and smart manufacturing. By resembling the age of craft manufacturing, Industry 4.0 expedites the alteration from mass production to mass customization. When distributed 3D printers (3DPs) are shared and collaborated in the IIoT, a promising dynamic, globalized, economical, and time-effective manufacturing environment for customized products will appear. However, the optimum allocation and scheduling of the personalized 3D printing tasks (3DPTs) in the IIoT in a manner that respects the customized attributes submitted for each model while satisfying not only the real-time requirements but also the workload balancing between the distributed 3DPs is an inevitable research challenge that needs further in-depth investigations. Therefore, to address this issue, this paper proposes a real-time green-aware multi-task scheduling architecture for personalized 3DPTs in the IIoT. The proposed architecture is divided into two interconnected folds, namely, allocation and scheduling. A robust online allocation algorithm is proposed to generate the optimal allocation for the 3DPTs. This allocation algorithm takes into consideration meeting precisely the customized user-defined attributes for each submitted 3DPT in the IIoT as well as balancing the workload between the distributed 3DPs simultaneously with improving their energy efficiency. Moreover, meeting the predefined deadline for each submitted 3DPT is among the main objectives of the proposed architecture. Consequently, an adaptive real-time multi-task priority-based scheduling (ARMPS) algorithm has been developed. The built ARMPS algorithm respects both the dynamicity and the real-time requirements of the submitted 3DPTs. A set of performance evaluation tests has been performed to thoroughly investigate the robustness of the proposed algorithm. Simulation results proved the robustness and scalability of the proposed architecture that surpasses its counterpart state-of-the-art architectures, especially in high-load environments.     

Real-time integrated production-scheduling and maintenance-planning in a flexible job shop with machine deterioration and condition-based maintenance

The introduction of modern technologies in manufacturing is contributing to the emergence of smart (and data-driven) manufacturing systems, known as Industry 4.0. The benefits of adopting such technologies can be fully utilized by presenting optimization models in every step of the decision-making process. This includes the optimization of maintenance plans and production schedules, which are two essential aspects of any manufacturing process. In this paper, we consider the real-time joint optimization of maintenance planning and production scheduling in smart manufacturing systems. We have considered a flexible job shop production layout and addressed several issues that usually take place in practice. The addressed issues are: new job arrivals, unexpected due date changes, machine degradation, random breakdowns, minimal repairs, and condition-based maintenance (CBM). We have proposed a real-time optimization-based system that utilizes a modified hybrid genetic algorithm, an integrated proactive-reactive optimization model, and hybrid rescheduling policies. A set of modified benchmark problems is used to test the proposed system by comparing its performance to several other optimization algorithms and methods used in practice. The results show the superiority of the proposed system for solving the problem under study. The results also emphasize the importance of the quality of the generated baseline plans (i.e., initial integrated plans), the use of hybrid rescheduling policies, and the importance of rescheduling times (i.e., reaction times) for cost savings.     

低能耗蓝牙4.0协议原理与实现方法

介绍了最新的蓝牙技术规范4.0协议中低能耗部分的协议原理以及协议架构。讨论了在分层结构通信协议实现中遇到的主要问题和应对的策略。结合通信协议实现的通常策略,讨论了低能耗蓝牙4.0协议实现的方法与策略。     

Observer模式在．NET多线程并行计算中的应用

对观察者（Observer）设计模式进行了分析,并利用．NET框架对其进行了改进;基于．NET Framework4．0,将改进后的模型应用到多线程并行程序的设计中,从而简化了开发过程,并且使系统结构更清晰,便于扩展和维护。     

A DLT-based framework for secure IoT infrastructure in smart communities

In the field of smart communities, significant progress has been made in recent years. The objective of constructing smart communities is to improve the quality of life of their inhabitants. To accomplish this objective, technologies such as Internet of Things (IoT) and Artificial Intelligence (AI) were deployed. The data gathered and processed by IoT devices, particularly those with centralized control, are however susceptible to availability, integrity, and privacy risks. Due to its inherent properties of transparency, immutability, and underlying secure-by-design architecture, Distributed Ledger Technology (DLT) and Smart Contracts enable distributed, decentralized, automated workflows that can be incorporated to automate the management of the next generation of IoT networks. Using a potential use case, a conceptual architecture for securing smart communities with DLT is developed and explained. In this paper, a framework for IoT eco-systems is proposed that provides seamless integration between IoT and DLT to create a decentralized trusted architecture that ensures the trustworthiness of IoT eco-systems at design time and a trust reputation model based on the architecture to protect it at run-time. In addition, the initial implementation steps are described for this framework.     

IIS的安全性

IIS4．0用来将WindowsNT的文件、网络及应用程序服务提供给基于web的客户机。本文介绍了IIS4．0应用的安全防护方法。IIS的安全性建立在WindowsNT安全性之上,其安全性与WindowsNT的安全性紧密相联。     

iFIX与西门子PLC通过SI7的通讯配置

通过例证,详细介绍了西门子S7-PLC与iFIX通过SI7的通讯配置.     

Towards Precision Medicine for Osteoarthritis: Focus on the Synovial Fluid Proteome

Osteoarthritis (OA) is a joint degenerative disease that most affects old age. The study of proteomics in synovial fluid (SF) has the task of providing additional elements to diagnose and predict the progress of OA. This review aims to identify the most significant biomarkers in the study of OA and to stimulate their routine use. Some of the major components of the ECM, such as proteoglycan aggrecan and decorin, were found considerably reduced in OA. Some biomarkers have proved useful for staging the temporality of OA: Periostin was found to be increased in early OA, while CRTA1 and MMPs were found to be increased in late OA. In its natural attempt at tissue regeneration, Collagen III was found to be increased in early OA while decreased in late OA. Some molecules studied in other areas, such as ZHX3 (oncological marker), LYVE1, and VEGF (lymph and angiogenesis markers), also have been found to be altered in OA. It also has been recorded that alteration of the hormonal pathway, using a dosage of PPAR-γ and RETN, can influence the evolution of OA. IL-1, one of the most investigated biomarkers in OA-SF, is not as reliable as a target of OA in recent studies. The study of biomarkers in SF appears to be, in combination with the clinical and radiological aspects, an additional weapon to address the diagnosis and staging of OA. Therefore, it can guide us more appropriately towards the indication of arthroplasty in patients with OA.