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, ma...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.展开更多
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....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.展开更多
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 th...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.展开更多
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-tim...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.展开更多
文摘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.
基金support provided in part by the National Key Research and Development Program of China under Grant 2020YFB1005804part by the National Natural Science Foundation of China under Grant 62372121,and in part by the NRPU 20-15516,HEC,Pakistan.
文摘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.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through the small Groups Project under grant number(168/43)Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R151),Princess Nourah bint Abdulrahman University,Riyadh,Saudi ArabiaThe authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:(22UQU4310373DSR59).
文摘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.
文摘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.
