Agile Factor Flexible Industry 4.0 with MES Manufacturing Execution System Along with ERP Back-End Integration: Ready-Made Garments as a Case Study

Industry 4.0, or the Fourth Industrial Revolution, is based on digitized the manufacturing process and makes use of all digital tools so its combination of various digital technologies computers, ERP software, IoT, machine learning and AI techniques, Manufacturing Execution Systems (MES), and big data analytics to create a new, fully digitized manufacturing system. The Critical Success Factors (CSFs) of MES adoption are both a quantitative and qualitative measurement. We use the case of ready-made garments to improve each of the three Overall Equipment Efficiency (OEE) factors: Availability, Performance, and Quality. In this study, we adopt real-time management of production activities on the shop floor from order receipt to finished products, then measure the improvement.

循环经济理念下的产业园4.0规划设计——以广州中创产业园为例

在国家推进碳中和的背景下,实现经济高质量发展尤为重要。循环经济具有降低能源消耗和碳排放的关键作用,是实现经济高质量发展的必由之路。以广州中创产业园为例,引入循环经济理念,对产业园区规划存在的问题进行分析,并进行系统性规划设计。同时,基于循环经济理念对产业园进行功能结构布局,进一步探讨物质循环系统、生态循环系统和智慧园区具体的规划策略。探索广州中创产业园4.0实现循环经济发展的路径与对策,为我国其他工业化地区建设面向循环经济的工业园区4.0提供参考。

面向物流4.0的高职物流工程综合实训室建设实践

实训室建设与管理是高等教育的重要内容,如何建设面向物流4.0的综合实训室是高职物流工程专业普遍关心的问题。介绍了物流4.0的概念,探讨其对从业能力的要求和对高职物流工程教育的挑战。分析了物流4.0对物流工程综合实训室和课程体系带来的变革要求。以浙江经济职业技术学院为例,详细介绍了物流工程综合实训室的建设过程,包括理念和目标、建设内容、建设成效和不足。可为我国高职院校物流工程教育中提供参考与借鉴。

Digital Evaluation of Sitting Posture Comfort in Human-vehicle System under Industry 4.0 Framework

Most of the previous studies on the vibration ride comfort of the human-vehicle system were focused only on one or two aspects of the investigation. A hybrid approach which integrates all kinds of investigation methods in real environment and virtual environment is described. The real experimental environment includes the WBV（whole body vibration） test, questionnaires for human subjective sensation and motion capture. The virtual experimental environment includes the theoretical calculation on simplified 5-DOF human body vibration model, the vibration simulation and analysis within ADAMS/VibrationTM module, and the digital human biomechanics and occupational health analysis in Jack software. While the real experimental environment provides realistic and accurate test results, it also serves as core and validation for the virtual experimental environment. The virtual experimental environment takes full advantages of current available vibration simulation and digital human modelling software, and makes it possible to evaluate the sitting posture comfort in a human-vehicle system with various human anthropometric parameters. How this digital evaluation system for car seat comfort design is fitted in the Industry 4.0 framework is also proposed.

Intelligent Manufacturing in the Context of Industry 4.0： A Review

Our next generation of industry-lndustry 4.0-holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. Intelligent manufacturing plays an important role in Industry 4.0. Typical resources are converted into intelligent objects so that they are able to sense, act, and behave within a smart environment. In order to fully understand intelligent manufacturing in the context of Industry 4.0, this paper provides a comprehensive review of associated topics such as intelligent manufacturing, Internet of Things （IoT）- enabled manufacturing, and cloud manufacturing. Similarities and differences in these topics are highlighted based on our analysis. We also review key technologies such as the loT, cyber-physical systems （CPSs）, cloud computing, big data analytics （BDA）, and information and communications technology （ICT） that are used to enable intelligent manufacturing. Next, we describe worldwide movements in intelligent manufacturing, including governmental strategic plans from different countries and strategic plans from major international companies in the European Union, United States, Japan, and China. Finally, we present current challenges and future research directions. The concepts discussed in this paper will spark new ideas in the effort to realize the much-anticipated Fourth Industrial Revolution.

Challenges and Requirements for the Application of Industry 4.0:A Special Insight with the Usage of Cyber-Physical System

Considered as a top priority of industrial devel- opment, Industry 4.0 （or Industrie 4.0 as the German ver- sion） has being highlighted as the pursuit of both academy and practice in companies. In this paper, based on the review of state of art and also the state of practice in dif- ferent countries, shortcomings have been revealed as the lacking of applicable framework for the implementation of Industrie 4.0. Therefore, in order to shed some light on the knowledge of the details, a reference architecture is developed, where four perspectives namely manufacturing process, devices, software and engineering have been highlighted. Moreover, with a view on the importance of Cyber-Physical systems, the structure of Cyber-Physical System are established for the in-depth analysis. Further cases with the usage of Cyber-Physical System are also arranged, which attempts to provide some implications to match the theoretical findings together with the experience of companies. In general, results of this paper could be useful for the extending on the theoretical understanding of Industrie 4.0. Additionally, applied framework and proto- types based on the usage of Cyber-Physical Systems are also potential to help companies to design the layout of sensor nets, to achieve coordination and controlling of smart machines, to realize synchronous production with systematic structure, and to extend the usage of information and communication technologies to the maintenance scheduling.

Future Digital Design and Manufacturing: Embracing Industry 4.0 and Beyond

Digital design and manufacturing have been around for several decades from the numerical control of machine tools and automating engineering design in 1960s, through early Computer Aided Design （CAD）/Computer Aided Engineering analysis （CAE）/Computer Aided Manufacturing （CAM）, to modem digital design and manufacturing [1], and cloud manufacturing [2] converging into product lifecycle management （PLM） [3, 4] and Internet-enabled personalized manufacturing [5].

工业4.0下的质量管理

全球工业正面临第四次工业革命,即工业4.0。它指的是系统的连接和集成,以收集和分析数据,并将组织机构的运营数字化。质量4.0是与第四次工业革命相关的概念,指工业4.0背景下质量工作的数字化。探讨了质量4.0如何成为质量工作演进的一部分,重点是了解组织应如何过渡到质量4.0。提出了质量4.0的定义,并提出了过渡到质量4.0的总体过程,包括6个连续阶段,适用于计划过渡到质量4.0的不同组织机构。

Industry 4.0: Architecture and Equipment Revolution

The development of science and technology has led to the era of Industry 4.0.The core concept is the combination of“material and informationization”.In the supply chain and manufacturing process,the“material”of the physical entity world is realized by data,identity,intelligence,and information.Industry 4.0 is a disruptive transformation and upgrade of intelligent industrialization based on the Internet-of-Things and Big Data in traditional industrialization.The goal is“maximizing production efficiency,minimizing production costs,and maximizing the individual needs of human beings for products and services.”Achieving this goal will surely bring about a major leap in the history of the industry,which will lead to the“Fourth Industrial Revolution.”This paper presents a detailed discussion of industrial big data,strategic roles,architectures,characteristics,and four types of innovative business models that can generate profits for enterprises.The key revolutionary aspect of Industry 4.0 is explained,which is the equipment revolution.Six important attributes of equipment are explained under the Industry 4.0 perspective.

Resilient Fault Diagnosis Under Imperfect Observations–A Need for Industry 4.0 Era

In smart industrial systems,in many cases,a fault can be captured as an event to represent the distinct nature of subsequent changes.Event-based fault diagnosis techniques are capable model-based methods for diagnosing faults from a sequence of observable events executed by the system under diagnosis.Most event-based diagnosis techniques rely on perfect observations of observable events.However,in practice,it is common to miss an observable event due to a problem in sensorreadings or communication/transmission channels.This paper develops a fault diagnosis tool,referred to as diagnoser,which can robustly detect,locate,and isolate occurred faults.The developed diagnoser is resilient against missed observations.A missed observation is detected from its successive sequence of events.Upon detecting a missed observation,the developed diagnoser automatically resets and then,asynchronously resumes the diagnosis process.This is achieved solely based on postreset/activation observations and without interrupting the performance of the system under diagnosis.New concepts of asynchronous detectability and asynchronous diagnosability are introduced.It is shown that if asynchronous detectability and asynchronous diagnosability hold,the proposed diagnoser is capable of diagnosing occurred faults under imperfect observations.The proposed technique is applied to diagnose faults in a manufacturing process.Illustrative examples are provided to explain the details of the proposed algorithm.The result paves the way towards fostering resilient cyber-physical systems in Industry4.0 context.

Industry 4.0新工业革命与工业自动化转型升级

随着新一代信息技术的发展,世界各国都在加快推进新的技术和工业革命。物联网、服务网以及信息物理系统已进入制造环境。论述了Industry 4.0战略产生的背景、目标以及主要特征,较深入地解析了作为Industry 4.0核心的智能工厂的体系架构。阐述了借鉴Industry 4.0的理念、方案与路线图,勇于创新,打造国内工业自动化升级版的愿景。

Macro Perspective of Industry 4.0： Factors Affecting Value Creation Modules

Business needs to manage such a variety of things inside the firm or outside the business consistently. This factor affects the business in various ways. The factor which affects the business is clients, suppliers, distributors and so on. These all components are isolated from two sections full-scale environment and miniaturized scale environment. Macro perspective environment components are those external variables which are past the association＇s control. The problem of this study is guaranteeing a supportable evolvement of human presence in its social, ecological, and monetary measurement. So, we have to adapt test in order to outfit toward manageability. As for the method used in this study, it depends on using empirical framework to meet the interest of capital and buyer, in addition to supporting human presence in its social, ecological, monetary measurement. The paper is organised as following sections： first section is the introduction, second section is the literature review, the third section includes the research method, fourth one discusses the analysis, while the conclusion is in the fifth section.

Mutated Leader Sine-Cosine Algorithm for Secure Smart IoT-Blockchain of Industry 4.0

In modern scenarios,Industry 4.0 entails invention with various advanced technology,and blockchain is one among them.Blockchains are incorporated to enhance privacy,data transparency aswell as security for both large and small scale enterprises.Industry 4.0 is considered as a new synthesis fabrication technique that permits the manufacturers to attain their target effectively.However,because numerous devices and machines are involved,data security and privacy are always concerns.To achieve intelligence in Industry 4.0,blockchain technologies can overcome potential cybersecurity constraints.Nowadays,the blockchain and internet of things(IoT)are gaining more attention because of their favorable outcome in several applications.Though they generate massive data that need to be effectively optimized and in this research work,deep learning-based techniques are employed for this.This paper proposes a novel mutated leader sine cosine algorithm-based deep convolutional neural network(MLSC-DCNN)in order to attain a secure and optimized IoT blockchain for Industry 4.0.Here,an MLSC is hybridized using a mutated leader and sine cosine algorithm to enhance the weight function and minimize the loss factor of DCNN.Finally,the experimentation is carried out for various simulation measures.The comparative analysis is made for Best Tip Selection Method(BTSM),Smart Block-Software Defined Networking(SDN),and the proposed approach.The evaluation results show that the proposed approach attains better performances than BTSM and SDN.

Industry 4.0新工业革命与工业自动化转型升级思路构架

文章主要论述的是Industry 4.0新工业革命与工业自动化转型升级思路构架,在具体展开论述的过程中首先从Industry4.0新工业革命的概述入手去论述,其次论述了Industry 4.0新工业革命的进程及其特点,最后重点论述了Industry 4.0新工业革命与工业自动化转型升级的思路构架。

Fault Handling in PLC-Based Industry 4.0 Automated Production Systems as a Basis for Restart and Self-Configuration and Its Evaluation

Industry 4.0 and Cyber Physical Production Systems (CPPS) are often discussed and partially already sold. One important feature of CPPS is fault tolerance and as a consequence self-configuration and restart to increase Overall Equipment Effectiveness. To understand this challenge at first the state of the art of fault handling in industrial automated production systems (aPS) is discussed as a result of a case study analysis in eight companies developing aPS. In the next step, metrics to evaluate the concept of self-configuration and restart for aPS focusing on real-time capabilities, fault coverage and effort to increase fault coverage are proposed. Finally, two different lab size case studies prove the applicability of the concepts of self-configuration, restart and the proposed metrics.

FogQSYM: An Industry 4.0 Analytical Model for Fog Applications

Industry 4.0 refers to the fourth evolution of technology development,which strives to connect people to various industries in terms of achieving their expected outcomes efficiently.However,resource management in an Industry 4.0 network is very complex and challenging.To manage and provide suitable resources to each service,we propose a FogQSYM(Fog—Queuing system)model;it is an analytical model for Fog Applications that helps divide the application into several layers,then enables the sharing of the resources in an effective way according to the availability of memory,bandwidth,and network services.It follows theMarkovian queuing model that helps identify the service rates of the devices,the availability of the system,and the number of jobs in the Industry 4.0 systems,which helps applications process data with a reasonable response time.An experiment is conducted using a Cloud Analyst simulator with multiple segments of datacenters in a fog application,which shows that the model helps efficiently provide the arrival resources to the appropriate services with a low response time.After implementing the proposed model with different sizes of fog services in Industry 4.0 applications,FogQSYM provides a lower response time than the existing optimized response time model.It should also be noted that the average response time increases when the arrival rate increases.

ChainApparel: A Trustworthy Blockchain and IoT-Based Traceability Framework for Apparel Industry 4.0

Trustworthiness and product traceability are essential factors in the apparel industry 4.0 for establishing successful business relationships among stakeholders such as customers,manufacturers,suppliers,and consumers.Each stakeholder has implemented different technology-based systems to record and track product transactions.However,these systems work in silos,and there is no intra-system communication,leading to a lack of complete supply chain traceability for all apparel stakeholders.Moreover,apparel stakeholders are reluctant to share their business information with business competitors;thus,they involve third-party auditors to ensure the quality of the final product.Furthermore,the apparel manufacturing industry faces challenges with counterfeit products,making it difficult for consumers to determine the authenticity of the products.Therefore,in this paper,a trustworthy apparel product traceability framework called ChainApparel is developed using the Internet of Things(IoT)and blockchain to address these challenges of authenticity and traceability of apparel products.Specifically,multiple smart contracts are designed and developed for registration,process execution,audit,fault,and product traceability to authorize,validate,and trace every business transaction among the apparel stakeholders.Further,the real-time performance analysis of ChainApparel is carried out regarding transaction throughput and latency by deploying the compute nodes at different geographical locations using Hyperledger Fabric.The results conclude that ChainApparel accomplished significant performance under diverse workloads while ensuring complete traceability along the complex supply chain of the apparel industry.Thus,the ChainApparel framework helps make the apparel product more trustworthy and transparent in the market while safeguarding trust among the industry stakeholders.

From the Current Industrial Stage to the Industry 4.0： Transformation Processes and Case Analysis of the FESTO Company

Despite of the acceleration of investments and the expansion of countries towards the Industry 4.0, companies have difficulties in planning the transition processes and implementation of the scenarios of Industry 4.0. To benefit from the Industry Approach 4.0, it is necessary to take technological and organizational transition processes into account, since the phenomenon involves interoperability between humans; between humans and machines; and between machines and production. This paper proposes to examine the transformation processes of the current industrial model to the Industry 4.0 model of FESTO AG, in addition to the framework proposition for the analysis of transformation processes for Industry 4.0. Through the face-to-face interviews and the institutional materials of FESTO, it was observed that the company inserted in its strategy of products and innovation the concept of Industry 4.0. To do so, FESTO planned and built a new production plant based on connectivity, sustainability, and collaborative environment, especially between man and machine. To support this orientation, FESTO has strengthened its technological base, culture, training of its productive, commercial, and management teams.

Optimal Deep Learning Model Enabled Secure UAV Classification for Industry 4.0

Emerging technologies such as edge computing,Internet of Things(IoT),5G networks,big data,Artificial Intelligence(AI),and Unmanned Aerial Vehicles(UAVs)empower,Industry 4.0,with a progressive production methodology that shows attention to the interaction between machine and human beings.In the literature,various authors have focused on resolving security problems in UAV communication to provide safety for vital applications.The current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification(CSODL-SUAVC)model for Industry 4.0 environment.The suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such as secure communication via image steganography and image classification.Primarily,the proposed CSODL-SUAVC method involves the following methods such as Multi-Level Discrete Wavelet Transformation(ML-DWT),CSO-related Optimal Pixel Selection(CSO-OPS),and signcryption-based encryption.The proposed model deploys the CSO-OPS technique to select the optimal pixel points in cover images.The secret images,encrypted by signcryption technique,are embedded into cover images.Besides,the image classification process includes three components namely,Super-Resolution using Convolution Neural Network(SRCNN),Adam optimizer,and softmax classifier.The integration of the CSO-OPS algorithm and Adam optimizer helps in achieving the maximum performance upon UAV communication.The proposed CSODLSUAVC model was experimentally validated using benchmark datasets and the outcomes were evaluated under distinct aspects.The simulation outcomes established the supreme better performance of the CSODL-SUAVC model over recent approaches.

Real Time Automation and Ratio Control Using PLC&SCADA in Industry 4.0

Industrial Control Systems(ICS)and SCADA(Supervisory Control and Data Acquisition)systems play a critical role in the management and regulation of critical infrastructure.SCADA systems brings us closer to the real-time application world.All process and equipment control capability is typically provided by a Distributed Control System(DCS)in industries such as power stations,agricultural systems,chemical and water treatment plants.Instead of control through DCS,this paper proposes a SCADA and PLC(Programmable Logic Controller)system to control the ratio control division and the assembly line division inside the chemical plant.A specific design and implementation method for development of SCADA/PLC based real time ratio control and automated assembly line system in a chemical plant is introduced.The assembly line division is further divided into sorting stage,filling stage and the auxiliary stage,which includes the capping unit,labelling unit and then the storage.In the ratio control division,we have defined the levels inside the mixer and ratio of the raw materials through human machine interface(HMI)panel.The ratio of raw materials is kept constant on the basis of flow rates of wild stream and manipulated stream.There is a flexibility in defining new levels and the ratios of the raw materials inside the mixer.But here we taken the predefined levels(low,medium,high)and ratios(3:4,2:1,2:5).Control valves are used for regulating the flow of the compositions.In the assembly line division,the containers are sorted on the basis of size and type of material used i.e.,big sized metallic containers and small sized non-metallic containers by inductive and capacitive proximity sensors.All the processes are facilitated with laser beam type or reflective type sensors on the conveyor system.Building a highly stable and dependable PLC/SCADA system instead of Distributed Control System is required to achieve automatic management and control of chemical industry processes to reduce waste manpower and physical resources,as well as to improve worker safety.