Intelligent Manufacturing Process Research Articles

RESEARCH ON THE IMPLEMENTATION OF INDUSTRY 4.0 IN INTEGRATED MANUFACTURING SYSTEMS

In the context of Industry 4.0, manufacturing systems are being upgraded to a smart level. Intelligent manufacturing takes advantage of advanced technologies, information and manufacturing to achieve flexible, intelligent and reconfigurable manufacturing processes in order to address a dynamic and global market. It allows all physical processes and information flows to be available, when and where they are needed across supply chains, multiple industries, small and medium enterprises (SMEs) and large companies. Smart manufacturing requires certain core technologies to activate devices or machines in order to vary their behaviors in response to different situations and requirements based on past experiences and learning abilities. The technologies allow direct communication with the production, thus allowing the solution and adaptation of problems and decisions that must be taken in a timely manner.

Fuzzy testing decision-making model for intelligent manufacturing process with Taguchi capability index

Fuzzy testing decision-making model for intelligent manufacturing process with Taguchi capability index

Gépi látáson alapuló demonstrációs alkalmazások fejlesztése

A gépi látás rendszerek egyre gyakoribb alkalmazása tapasztalható a gyártásban, különösképpen a minőség-ellenőrzés területén, annak megbízhatósága, gyorsasága, pontossága és ismételhetősége végett. A negyedik ipari forradalomban támasztott irányelvek szerint a gyártás hatékonysága az adatok következetes gyűjtése- és feldolgozása által növelhető, melyben fontos szerepet kapnak a korszerű automatizálási technológiákkal támogatott intelligens gyártási folyamatok. A cikkben a gépi látás rendszerek tervezéséhez szükséges ismeretek összefoglalása után oktatási céllal készült alkalmazási példák és projektfeladatok kerülnek bemutatásra.

A Hybrid Fuzzy Convolutional Neural Network Based Mechanism for Photovoltaic Cell Defect Detection with Electroluminescence Images

In the intelligent manufacturing process of solar photovoltaic (PV) cells, the automatic defect detection system using the Industrial Internet of Things (IIoT) smart cameras and sensors cooperated in IIoT has become a promising solution. Many works have been devoted to defect detection of PV cells in a data-driven way. However, because of the subjectivity and fuzziness of human annotation, the data contains a high quantity of noise and unpredictable uncertainties, which creates great difficulties in automatic defect detection. To address this problem, we propose a novel architecture named fuzzy convolution, which integrates fuzzy logic and convolution operations at microscopic level. Combining the proposed fuzzy convolution with the regular convolution, we build a network called Hybrid Fuzzy Convolutional Neural Network (HFCNN). Compared with convolutional neural networks (CNNs), HFCNN can address the uncertainties of PV cell data to improve the accuracy with fewer parameters, making it possible to apply our method in smart cameras. Experimental results on a public dataset show the superiority of our proposed method compared with CNNs.

Potential applications of 5G communication technologies in collaborative intelligent manufacturing

Nowadays most of the communication technologies used in the manufacturing industry are still wired, including various fieldbuses and dedicated industrial Ethernet technologies, though wireless communication technologies including WiFi and ZigBee are recently being adopted. This study is to investigate the integration of 5G wireless communication technologies with collaborative intelligent manufacturing (CIM) processes and systems. 5G technologies and typical scenarios including enhanced mobile broadband, massive machine type communications, and ultra-reliable low latency communication are introduced. Various possible applications or business slices of 5G in CIM are analysed, including human–machine interfaces and production IT, process automation, factory automation, logistics and warehousing, monitoring, and maintenance. These applications are analysed by the functions as modules with the extended 5C architecture. A modular collaborative production approach is suggested to combine modules to achieve on-demand resource allocation and complete flexible tasks in CIM systems. Related research challenges and opportunities are also discussed.

3D Printed Materials Based On Model Structure Optimization in Environmental Art Design Applications

3D printing materials are a rapidly evolving model intelligent manufacturing process that enables geometric modeling of any complex shape. In the practical application of environmental art design, we have begun to give full play to the technological advantages brought by 3D printing. Environmental art design is the subject of mainstream research in the current society. At the same time, it has a close relationship with social development and environmental construction. Applying 3D printing materials to the design of environmental art can not only further improve the level of environmental art design, but also effectively improve the overall quality of environmental design, while also saving production costs. The paper combines case studies to optimize consumables of environmental art crafts by using algorithms to reduce consumables and reduce the cost of 3D printing materials. At the same time, it points out the application prospects and directions of future 3D printing technologies and materials in environmental art design.

RETRACTED ARTICLE: Research on application of the Internet of things technology in financial leasing of intelligent manufacturing enterprises

In 2015, the State Council issued “Made in China 2025,” stating that the deep integration of information technology and manufacturing should be accelerated, and intelligent manufacturing should be the main direction of integration. In this context, China’s manufacturing-led cities have implemented the “machine substitution” program to upgrade traditional machinery and equipment to intelligent machinery and equipment, which has led to the development of traditional financial leasing models in China, such as capital. Constraints, financing channel constraints, risk constraints, and information constraints have severely constrained the advancement of the intelligent manufacturing process. In this context, the paper discusses the use of the Internet of things as a technical means to help the existing smart manufacturing enterprises to access the financing channels and open up new financing channels.

Construction of theoretical model of traditional Chinese medicine intelligent manufacturing

In the process of transforming and upgrading of traditional Chinese medicine( TCM) intelligent manufacturing,the TCM enterprises lack systematic and in-depth research on intelligent manufacturing of TCM,leading to insufficient understanding of relevant concepts,development direction,development content and other aspects,to some extent,causing fuzzy and chaotic phenomena. The theoretical model,as a higher expression level of scientific thinking,has the function of interpretation and prediction,and can provide theoretical basis as well as guide for scientific research. Therefore,this article aims to construct a theoretical model of TCM intelligent manufacturing based on the concept of flexible production and intelligent equipment for some unhealthy phenomena in the development process of TCM intelligent manufacturing. In the TCM intelligent manufacturing system,with theory model as the core,the new-generation information technology was integrated with the TCM manufacturing technology to realize the integration of informationization and industrilization as well as the landing of theoretical model. Then,a 3 D simulation model was established to provide a visual environment for intelligent manufacturing of TCM and simulate the virtual reality throughout the TCM intelligent manufacturing process. The new theoretical model in this paper,to a certain extent,can play a guiding role in the development of TCM intelligent manufacturing,and can also provide reference for the realization of TCM intelligent manufacturing.

In-process complex machining condition monitoring based on deep forest and process information fusion

Abnormal machining condition causes losses of quality for finished part. A machining condition monitoring system is considerably vital in the intelligent manufacturing process. Existing machining condition monitoring methods usually detect only one single abnormal condition under the same machining process, which is unrealistic and impractical for real complicated machining process. In this paper, a novel hybrid condition monitoring approach for multiple abnormal conditions’ detection of complicated machining process by using deep forest and multi-process information fusion is proposed. First, various process data are obtained from a triaxial accelerometer and a sound sensor mounted on the spindle of CNC. Then, the time domain, frequency domain, and time-frequency domain features extracted from the multiple sensory signals are simultaneously optimized to select a subset with key features by the lasso technique. Furthermore, deep forest is utilized as a condition classifier by using the selected features. Finally, cutting experiments are designed and conducted, and the results show that the proposed method can effectively detect the multiple abnormal conditions under the different machining parameters.

LSTM and Edge Computing for Big Data Feature Recognition of Industrial Electrical Equipment

With the rapid development of Industrial Internet of Things, the category and quantity of industrial equipment will increase gradually. For centralized monitoring and management of numerous and multivariate equipment in the intelligent manufacturing process, the equipment categories shall be identified first. However, manual labeling of electrical equipment needs high costs. For the purpose of recognizing industrial equipment accurately in manufacturing systems, this study adopts the long short-term memory to analyze big data features and build a nonintrusive load monitoring system. Edge computing is used to implement parallel computing to improve the efficiency of equipment identification. Considering the practical popularity, the fairly priced low-frequency Smart Meter is used to collect the appliance data. According to the proposed optimal adjustment strategy of parameter model, the average random recognition rate can achieve 88% and the average recognition rate of the continuous data of a single electrical equipment can achieve 83.6%.

Risk Assessment in Intelligent Manufacturing Process: A Case Study of an Optical Cable Automatic Arranging Robot

Intelligent manufacturing is one of the indispensable parts in Industry 4.0, where the smart machines can perceive and operate automatically in production process to provide higher and more convenient efficiency. Nevertheless, some potential failures influencing the manufacturing may exist. It is necessary to identify the potential failures and evaluate their risk. Meanwhile, resources and environment protections have been the consensus around the world. For enterprises, they must take measures to reduce the negative environmental impacts during the industrial production to maintain their sustainable development. Failure mode and effects analysis (FMEA) can effectively recognize failures and evaluate their risk in a production process or a system. However, environmental aspects of the identified failure modes are often ignored in the FMEA. Besides, conventional FMEA usually uses the risk priority number to obtain the failures' risk, which has a lot of shortcomings in the industrial application, such as the equal weights for different risk factors, crisp numbers used in the evaluation without considering vagueness, and so on. Based on the above two main problems, this paper develops an extended FMEA which introduces environmental impacts as one of the risk factors and utilizes Technique for order preference by similarity to an ideal solution (TOPSIS) method based on rough sets to cope with vague information. Finally, the developed FMEA is applied to evaluate the potential failure risk of an optical cable automatic arranging robot to verify its feasibility and effectiveness.

Accurate and Real-Time 3-D Tracking for the Following Robots by Fusing Vision and Ultrasonar Information

Acquiring the accurate three-dimensional (3-D) position of a target person around a robot provides valuable information that is applicable to a wide range of robotic tasks, especially for promoting the intelligent manufacturing processes of industries. This paper presents a real-time robotic 3-D human tracking system that combines a monocular camera with an ultrasonic sensor by an extended Kalman filter (EKF). The proposed system consists of three submodules: a monocular camera sensor tracking module, an ultrasonic sensor tracking module, and the multisensor fusion algorithm. An improved visual tracking algorithm is presented to provide 2-D partial location estimation. The algorithm is designed to overcome severe occlusions, scale variation, target missing, and achieve robust redetection. The scale accuracy is further enhanced by the estimated 3-D information. An ultrasonic sensor array is employed to provide the range information from the target person to the robot, and time of flight is used for the 2-D partial location estimation. EKF is adopted to sequentially process multiple, heterogeneous measurements arriving in an asynchronous order from the vision sensor, and the ultrasonic sensor separately. In the experiments, the proposed tracking system is tested in both a simulation platform and actual mobile robot for various indoor and outdoor scenes. The experimental results show the persuasive performance of the 3-D tracking system in terms of both the accuracy and robustness.

An Improved Message Filter and Routing Algorithm Based on Topic and Eigenvalue Similarity

This paper discusses on the cyber-physical system technology that assures the interoperability of manufacturing control system and equipment in intelligent manufacturing domain. This technology involves an information exchange and communication process, where broad manufacturing resources of production workshops in advanced manufacturing industries such as control system, equipment, personnel, and materials may freely enter or exit from the distributed self-organizing peer-to-peer network as independent message nodes. In this process, an improved filtering and routing algorithm based on topic and eigenvalue similarity is also employed to group and compress massive manufacturing messages in the light of semantics and message clusters for the purpose of intelligently identifying, positioning, tracking, monitoring and managing manufacturing resources. Based on the features of manufacturing process, this paper filters messages and implements end-to-end batch compression and transmission so as to ensure that the massive messages transmitted among different manufacturing resources in the intelligent manufacturing process are equipped with the advantages like real time, fault tolerance and high robustness when data validity is guaranteed.

A Smart Building as a Cyber Pyhsical System

In recent years, systems consisting of both physical and computational elements, called Cyber Physical Systems (CPSs), have entered into our lives. These systems are becoming increasingly important because of their wide application area such as smart buildings, intelligent manufacturing processes, energy grids, healthcare devices, smart agriculture and etc. In this work, CPSs are considered by means of a smart building application. Firstly, CPSs are introduced and their features are explained. Then, a smart building is considered for emphasizing and illustrating the importance of CPSs. In order to display working mechanism of computational and physical components of the building and to provide easy trace of the evolution of overall system, some physical components (smart AC, lighting system and smart TV) are developed via Petri net, which is a mathematical and graphical tool for modelling and analysing discrete event systems.

Research of Mass Redundant Data Deleting Algorithm for Intelligent Manufacturing Process

Information management systems become more common and more important in all walks of life. Many serious problems such as multi-source information heterogeneity, mass redundant data, and data security occur in the systems as the explosive increment of data. A novel redundant data deleting algorithm based on the cloud storage platform was proposed in this paper to deal with the problem of mess data storing. Storage space division algorithm and different users were divided in an appropriate way to improve the efficiency of reading and writing. A typical information management system was used to verify the feasibility and effectiveness of the algorithms proposed in this paper.

Shared and service-oriented CNC machining system for intelligent manufacturing process

To improve efficiency, reduce cost, ensure quality effectively, researchers on CNC machining have focused on virtual machine tool, cloud manufacturing, wireless manufacturing. However, low level of information shared among different systems is a common disadvantage. In this paper, a machining database with data evaluation module is set up to ensure integrity and update. An online monitoring system based on internet of things and multi-sensors “feel” a variety of signal features to “percept” the state in CNC machining process. A high efficiency and green machining parameters optimization system “execute” service-oriented manufacturing, intelligent manufacturing and green manufacturing. The intelligent CNC machining system is applied in production. CNC machining database effectively shares and manages process data among different systems. The prediction accuracy of online monitoring system is up to 98.8% by acquiring acceleration and noise in real time. High efficiency and green machining parameters optimization system optimizes the original processing parameters, and the calculation indicates that optimized processing parameters not only improve production efficiency, but also reduce carbon emissions. The application proves that the shared and service-oriented CNC machining system is reliable and effective. This research presents a shared and service-oriented CNC machining system for intelligent manufacturing process.

Implementation of Web based Technique into the Intelligent Manufacturing System

Intelligent Manufacturing System (IMS) shall be considered as a system integrated with different intelligent subsystems, which completes the distributed solution procedure on the basis of exchanging large quantities of materials, energy and information. Any intelligent manufacturing process selfregulates and self-controls itself in manufacturing the products within the design specifications. It incorporates introduction of human-like decision-making capabilities into the manufacturing system that brings the intelligence. The system however requires complete information of the requirements and processing of production system to generate appropriate decisions. This paper provides a comprehensive review of research on web-enabled e-Manufacturing technology which bridges certain aspects of manufacturing system like Customer Relationship Management (CRM), Enterprise Resource Planning (ERP), and Supply Chain Management (SCM). Web-based systems have been implemented to provide remote service and manufacturing for rapid prototyping, enhance the availability of facilities and improve the capability of rapid product development for various enterprises. Web-based technique is utilized to derive the availability of information anytime, anywhere and by the persons who are authorized to deal with it. The eManufacturing production system can substantially reduce product cost and delivery cycle for manufacturing systems.

Proposal of a concept of future oriented machine tools for advanced manufacturing systems

In order to satisfy the recent various consumers’ needs, an advanced manufacturing system will be required. So, the innovative concept of Future Oriented Machine Tools (FOMT), which consists of four function blocks to realize the advanced manufacturing system, is proposed. The four function blocks are Management, Prediction, Observation and Strategy, and intelligent manufacturing processes are realized by utilizing these function blocks. FOMT can make a significant contribution in four stages: design stage, production scheduling stage, machining stage and post-machining stage. In the design stage, the product information such as accuracy can be evaluated in CAD, considering the manufacturing ability concurrently. In the production scheduling stage, the product schedules can be generated automatically and flexibly for the various products. In the machining stage, cutting conditions adjusted autonomously according to the machining status and machining problems. In the post-machining stage, the machining know-how data are accumulated and stored for future production and human engineers. The feasibility of it, especially the machining stage, is discussed using the developed cutting process simulator called VMSim (virtual machining simulator) from the view points of cutting force, machining error and environmental burden (CO2 emission).

Contribution of Fuzzy Logic to Modelling Expertise in Intelligent Manufacturing Process Planning Systems

This paper aims at describing how fuzzy logic can be used to model process planning expertise in an integrated design context. The presented approach is AI-based : process planning rules do not have the same importance in every case, and this importance depends on the context related to the given problem. This context is expressed through rules that are often imprecise, as they are strongly related to know-how, experience..... It is this context modelling that can handle fuzzy logic concepts through expert rules dynamic weighting.

Three-Dimensional Object Perception for Automated Assembly by the Structured Light Method using Cone Sections

Abstract Intelligent manufacturing processes require intelligent sensor integration. For automated assembly this means integration of three-dimensional scene perception. Existing approaches use or to reconstruct the 3-D objects. In this paper the 3-D objects are reconstructed by their planar surfaces. The extraction of these surfaces is done using a with . The object planes are estimated by intersecting the generating cones for the projected disks and the image ellipses. The new method is especially addressed to problems arising in robotics and assembly tasks, where it is necessary to recognize a priori known objects and to estimate their pose.