Дисертації з теми "Knowledge based smart manufacturing system"
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Cao, Qiushi. "Semantic technologies for the modeling of predictive maintenance for a SME network in the framework of industry 4.0 Smart condition monitoring for industry 4.0 manufacturing processes: an ontology-based approach Using rule quality measures for rule base refinement in knowledge-based predictive maintenance systems Combining chronicle mining and semantics for predictive maintenance in manufacturing processes." Thesis, Normandie, 2020. http://www.theses.fr/2020NORMIR04.
Повний текст джерелаIn the manufacturing domain, the detection of anomalies such as mechanical faults and failures enables the launching of predictive maintenance tasks, which aim to predict future faults, errors, and failures and also enable maintenance actions. With the trend of Industry 4.0, predictive maintenance tasks are benefiting from advanced technologies such as Cyber-Physical Systems (CPS), the Internet of Things (IoT), and Cloud Computing. These advanced technologies enable the collection and processing of sensor data that contain measurements of physical signals of machinery, such as temperature, voltage, and vibration. However, due to the heterogeneous nature of industrial data, sometimes the knowledge extracted from industrial data is presented in a complex structure. Therefore formal knowledge representation methods are required to facilitate the understanding and exploitation of the knowledge. Furthermore, as the CPSs are becoming more and more knowledge-intensive, uniform knowledge representation of physical resources and reasoning capabilities for analytic tasks are needed to automate the decision-making processes in CPSs. These issues bring obstacles to machine operators to perform appropriate maintenance actions. To address the aforementioned challenges, in this thesis, we propose a novel semantic approach to facilitate predictive maintenance tasks in manufacturing processes. In particular, we propose four main contributions: i) a three-layered ontological framework that is the core component of a knowledge-based predictive maintenance system; ii) a novel hybrid semantic approach to automate machinery failure prediction tasks, which is based on the combined use of chronicles (a more descriptive type of sequential patterns) and semantic technologies; iii) a new approach that uses clustering methods with Semantic Web Rule Language (SWRL) rules to assess failures according to their criticality levels; iv) a novel rule base refinement approach that uses rule quality measures as references to refine a rule base within a knowledge-based predictive maintenance system. These approaches have been validated on both real-world and synthetic data sets
蕭世良 and Sai-leung Siu. "A knowledge based process planning system for prismatic parts." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1991. http://hub.hku.hk/bib/B31232784.
Повний текст джерелаGovindan, Saravana. "A task based manufacturing knowledge maintenance method." Thesis, Loughborough University, 2013. https://dspace.lboro.ac.uk/2134/12414.
Повний текст джерелаRoy, Asok K. "Development of a knowledge based vision system for automated inspection." Thesis, Glasgow Caledonian University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.363131.
Повний текст джерелаWondoloski, Karen M. "A knowledge-based cell controller and its integration in a manufacturing system." Thesis, Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/23341.
Повний текст джерелаSun, Qi-zhi. "Knowledge-based interactive real-time control system in product-focused manufacturing environment." Thesis, University of Portsmouth, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.292501.
Повний текст джерелаAl-Awadhi, Waleed. "Integrating machine grouping and layout by using knowledge based system approach." Thesis, Brunel University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.242982.
Повний текст джерелаAl-Khawaldeh, Mustafa Awwad Salem. "Ubiquitous robotics system for knowledge-based auto-configuration system for service delivery within smart home environments." Thesis, De Montfort University, 2014. http://hdl.handle.net/2086/10202.
Повний текст джерелаMahmood, Tariq. "Knowledge-based process planning and design system for the cold forging of steel." Thesis, Imperial College London, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.264352.
Повний текст джерелаChun-Kit, Kwong. "A computer-aided concurrent design system." Thesis, University of Warwick, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263309.
Повний текст джерелаRashidy, Haitham. "Knowledge-based quality control in manufacturing processes with application to the automotive industry /." München : Herbert Utz, 2009. http://opac.nebis.ch/cgi-bin/showAbstract.pl?u20=9783831608621.
Повний текст джерелаRashidy, Haitham. "Knowledge-based quality control in manufacturing processes with application to the automotive industry." München Utz, 2008. http://d-nb.info/991264630/04.
Повний текст джерелаWang, Wei. "A knowledge based modelling system for the design and evaluation of flexible manufacturing facilities." Thesis, Loughborough University, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.328603.
Повний текст джерелаZhu, Chun Bao. "Optimisation of the grinding process using process modelling and knowledge based system approach." Thesis, University of the West of England, Bristol, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334546.
Повний текст джерелаSiddique, Mohammad. "A knowledge-based system for process planning in a seamless steel tube plant." Thesis, Aston University, 1990. http://publications.aston.ac.uk/11889/.
Повний текст джерелаLaw, Hang-Wai. "Knowledge-based computer-aided process planning system for the manufacture of bare printed circuit board." Thesis, Loughborough University, 1994. https://dspace.lboro.ac.uk/2134/27414.
Повний текст джерелаRazfar, Mohammad Reza. "Development of a knowledge based system for the selection of cutting tools and conditions for milling." Thesis, University of Sheffield, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.319419.
Повний текст джерелаValdes, Francisco Javier. "Manufacturing compliance analysis for architectural design: a knowledge-aided feature-based modeling framework." Diss., Georgia Institute of Technology, 2016. http://hdl.handle.net/1853/54973.
Повний текст джерелаKotevska, Olivera. "Learning based event model for knowledge extraction and prediction system in the context of Smart City." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAM005/document.
Повний текст джерелаBillions of “things” connected to the Internet constitute the symbiotic networks of communication devices (e.g., phones, tablets, and laptops), smart appliances (e.g., fridge, coffee maker and so forth) and networks of people (e.g., social networks). So, the concept of traditional networks (e.g., computer networks) is expanding and in future will go beyond it, including more entities and information. These networks and devices are constantly sensing, monitoring and generating a vast amount of data on all aspects of human life. One of the main challenges in this area is that the network consists of “things” which are heterogeneous in many ways, the other is that their state of the interconnected objects is changing over time, and there are so many entities in the network which is crucial to identify their interdependency in order to better monitor and predict the network behavior. In this research, we address these problems by combining the theory and algorithms of event processing with machine learning domains. Our goal is to propose a possible solution to better use the information generated by these networks. It will help to create systems that detect and respond promptly to situations occurring in urban life so that smart decision can be made for citizens, organizations, companies and city administrations. Social media is treated as a source of information about situations and facts related to the users and their social environment. At first, we tackle the problem of identifying the public opinion for a given period (year, month) to get a better understanding of city dynamics. To solve this problem, we proposed a new algorithm to analyze complex and noisy textual data such as Twitter messages-tweets. This algorithm permits an automatic categorization and similarity identification between event topics by using clustering techniques. The second challenge is combing network data with various properties and characteristics in common format that will facilitate data sharing among services. To solve it we created common event model that reduces the representation complexity while keeping the maximum amount of information. This model has two major additions: semantic and scalability. The semantic part means that our model is underlined with an upper-level ontology that adds interoperability capabilities. While the scalability part means that the structure of the proposed model is flexible in adding new entries and features. We validated this model by using complex event patterns and predictive analytics techniques. To deal with the dynamic environment and unexpected changes we created dynamic, resilient network model. It always chooses the optimal model for analytics and automatically adapts to the changes by selecting the next best model. We used qualitative and quantitative approach for scalable event stream selection, that narrows down the solution for link analysis, optimal and alternative best model. It also identifies efficient relationship analysis between data streams such as correlation, causality, similarity to identify relevant data sources that can act as an alternative data source or complement the analytics process
O'Kane, James Francis. "The use of a dynamic database within a knowledge-based system for analysing reactive scheduling issues in a FMS." Thesis, Staffordshire University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318342.
Повний текст джерелаDe, Souza Antonio Artur. "Developing a knowledge-based decision support system to aid make-to-order companies in cost estimation and pricing decisions." Thesis, Lancaster University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296684.
Повний текст джерелаRamadan, Muawia [Verfasser], and Bernd [Akademischer Betreuer] Noche. "RFID-Enabled Dynamic Value Stream Mapping for Smart Real-Time Lean-Based Manufacturing System / Muawia Ramadan. Betreuer: Bernd Noche." Duisburg, 2016. http://d-nb.info/1090785445/34.
Повний текст джерелаMoud, Nawawi Mohd Kamal. "The development of a hybrid knowledge-based Collaborative Lean Manufacturing Management (CLMM) system for an automotive manufacturing environment : the development of a hybrid Knowledge-Based (KB)/ Analytic Hierarchy Process (AHP)/ Gauging Absences of Pre-Requisites (GAP) Approach to the design of a Collaborative Lean Manufacturing Management (CLMM) system for an automotive manufacturing environment." Thesis, University of Bradford, 2009. http://hdl.handle.net/10454/3353.
Повний текст джерелаMohamed, N. M. Z. Nik. "The Development of a Hybrid Knowledge-Based System for Designing a Low Volume Automotive Manufacturing Environment. The Development of A Hybrid Knowledge-Based (KB)/Gauging Absences of Pre-Requisites (GAP)/Analytic Hierarchy Process (AHP) System for the Design and Implementation of a Low Volume Automotive Manufacturing (LVAM) Environment." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/5515.
Повний текст джерелаNemrow, Andrew Craig. "Implementing an IIoT Core System for Simulated Intelligent Manufacturing in an Educational Environment." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/8822.
Повний текст джерелаPabolu, Venkata Krishna Rao. "DFM – Weldability analysis and system development." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH. Forskningsmiljö Produktutveckling - Datorstödd konstruktion, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-29316.
Повний текст джерелаAggarwal, Shubhesh, and Kjzal Kaldi. "Agile Project Management for Knowledge-Based Projects in Manufacturing Industry : Case Study: Epiroc Drilling Tools, Fagersta, Sweden." Thesis, Uppsala universitet, Industriell teknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-355239.
Повний текст джерелаAchanga, Pius Coxwell. "Development of an impact assessment framework for lean manufacturing within SMEs." Thesis, Cranfield University, 2007. http://dspace.lib.cranfield.ac.uk/handle/1826/3521.
Повний текст джерелаMilana, Milana. "The Development of a Hybrid Knowledge-Based System for Integrated Maintenance Strategy and Operations in an Automotive Industry Environment: The Development of a Hybrid Knowledge-Based (KB) System/ Gauging Absences of Pre-Requisites (GAP)/Analytic Hierarchy Process (AHP) Methodology for Integrated Maintenance Strategy and Operations in an Automotive Industry Environment." Thesis, University of Bradford, 2018. http://hdl.handle.net/10454/17446.
Повний текст джерелаWang, Zhiping. "Constructive generative design methods for qualified additive manufacturing." Thesis, Ecole centrale de Nantes, 2021. https://tel.archives-ouvertes.fr/tel-03670417.
Повний текст джерелаAdditive manufacturing (AM) technologies give more and more design freedom to designers and engi-neers to design and define highly complex geometries and material compositions. Due to a layer-by-layer processing, the constraints, methods, tools and processes of design in AM are different from that in traditional manufacturing processes. Traditional design methods and tools cannot meet the needs of design in AM. Therefore, a new re-search field, design for AM (DfAM), has emerged to serve this need. However, existing DfAM methods are either guidelines or pure computation-based, which have limited consideration of coupled constraints along the AM digital processing chain and are difficult to ensure manufactura-bility of design in AM. To obtain qualified design in AM, this research focuses on three typical existing problems in DfAM domain: Firstly, how to ensure manufacturability in (topology optimization) TO process? Secondly, how to design support structures with lightweight, easy-to-remove for post-processing and friendly heat-diffusion properties to ensure shape accuracy and improve surface roughness of printed parts? Finally, how to avoid accuracy loss in print-ing preparation of complex lattice structures and ensure their manufacturability in design?To solve the three identified problems, this research developed a set of new constructive genera-tive design methods: 1. CSG-based generative design method to ensure manufacturability in light-weight topology optimization; 2. Pattern-based constructive generative design method to optimize support structure design and 3. Toolpath-based inversed constructive design to directly ob-tain processing models of corresponding complex lattice or porous structures with qualified print-ing toolpaths. The three proposed methods can well embed AM process constraints, realize para-metric control and save computation cost in design process to obtain a set of candidate design solutions with ensured manufacturability. A set of comparison studies with existing DfAM meth-ods and a couple of experiment case studies in medical applications demonstrated the methods’ advantages. These constructive methods may have large application potential to be adopted as design and decision making tools for other industrial applications when qualified DfAM is required
Butdee, Suthep. "Development of a hybrid intelligent process planning system for rotational parts." Thesis, Queensland University of Technology, 1997.
Знайти повний текст джерелаThorn, Jessica Paula Rose. "Ecosystem services, biodiversity and human wellbeing along climatic gradients in smallholder agro-ecosystems in the Terai Plains of Nepal and northern Ghana." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:3319dafc-5b0c-436a-b653-a623fc3e8de4.
Повний текст джерелаMadhusudanan, N. "Acquiring diagnostic knowledge from documents to predict issues in aircraft assembly." Thesis, 2018. https://etd.iisc.ac.in/handle/2005/5345.
Повний текст джерелаWang, Peng. "A smart experience-based knowledge analysis system (SEKAS)." Thesis, 2014. http://hdl.handle.net/1959.13/1054153.
Повний текст джерелаThis thesis addresses issues associated with using ever-increasing amounts of information and knowledge more effectively, and taking advantage of knowledge generated through experience. With very fast expansion of the Internet has created several problems and challenges linked to the increasing amount of information in Web content. These challenges are related mainly to the difficulty of extracting potentially useful information and knowledge from Internet pages. Data mining is a tool that enables enterprises to learn from existing experience by providing them with useful and accurate trends about their customers’ behaviour, and assists organisations in predicting which products their customers may be interested in buying. Moreover, in the real world, it is common to face optimisation problems that have two or more objectives that must be optimised at the same time, that are typically explained in different units, and are in conflict with one another. The evolutionary algorithm can use experience that is derived from a former decision event to improve the evolutionary algorithm’s ability to find optimisation solutions rapidly and efficiently. A hybrid structure, the Smart Experience-based Knowledge Analysis System (SEKAS), is put forward in this thesis to address issues of knowledge management and use. SEKAS combines a set of experience knowledge structures (SOEKS) with multiple techniques to provide a comprehensive knowledge management approach capturing, discovering, reusing and storing knowledge for the users. The SEKAS integrates a novel Decisional DNA (DDNA) knowledge structure with the traditional web crawler technologies. DDNA, as a knowledge representation platform, can help deal with noisy and incomplete data, with learning from experience, and with making precise decisions and predictions in vague and fuzzy environments. This thesis outlines the investigation of the combination of DDNA and feature selection algorithms to guarantee the future performance for prediction. The proposed approaches are general and extensible in terms of both designing novel algorithms, and in the application to other domains. The SEKAS integrates the evolutionary algorithm, Non-dominated Sorting Genetic Algorithm II (NSGA-II) (Deb et al. 2002), using experience that is derived from a former decision event, to improve the evolutionary algorithm’s ability to find optimal solutions rapidly and efficiently. The SEKAS application to solve a travelling salesman's problem shows that this new proposed hybrid model can find optimal, or close to true, Pareto-optimal solutions in a fast and efficient way. Several conceptual elements for this thesis have been implemented in the testing prototype, and the experimental results that were obtained show that the SEKAS system has great potential for managing knowledge, as well as improving the response times for providing accurate solutions. Consequently, the SEKAS can provide a universal knowledge management platform for mass autonomous mechanisms and provides many functionalities for improving the efficiency in the organisational decision-making process. A real-world implementation in clinical domain is also provided in this thesis. Clinical decisional events are acquired and formalised inside the system by using the experiential knowledge representation techniques SOEKS and Decisional DNA. Three different algorithms are then applied to the clinical experience, to provide a weighting of the different decision criteria, their fine-tuning, and the formalisation of new ones.
Mpofu, Khumbulani. "Knowledge-based design of reconfigurable manufacturing system advisor." 2010. http://encore.tut.ac.za/iii/cpro/DigitalItemViewPage.external?sp=1000249.
Повний текст джерелаDescribes reconfigurable manufacturing (RM) is a paradigm that promises to meet the turbulent demands in current global manufacturing. The major findings of this thesis are as follows; 1. The functional description of the machine tool provides a handy mechanism of aiding COTS machine builders come up with vary configurations of machine tools and their classification from a predefined set of COTS modules. 2. The process of linking the respective part demands to the relevant COTS RMT is a rigorous and tiresome process that demands computational power provided for by the KBS. 3. The subjective linguistic manner of linking the parts and the machine configuration can be managed by including an objective constraint for the fuzzy model. 4. Coupling the decision making using a mathematical model with the use of a KBS brings about the optimum route to arriving to the desired configuration.
Liu, Ming-Fang, and 劉明芳. "A Knowledge-based Scheduling of a Flexible Manufacturing System." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/10532120541676893728.
Повний текст джерела國立成功大學
航空太空工程學系
84
The FMS scheduling problem concerns the flow of parts and determining the sequence of operations at each machine tool. In this thesis, a heuristic scheduling method is proposed and it combines various dispatching rules in response to the dynamic status of the system. Results show that dispatching rules have a large impact on different system performance measures, such as the average machine utilization.Consequently,according to a criterion, the scheduling mechanism evaluates dispatching rules and selects the best dispatching rule for that criterion. Meanwhile, the system requires an immediate response to some external events,such as urgent parts, machine maintenance and machine breakdown, which may happen during the processing of production. To handle this situation, a new scheduling is performed with the remaining operations in the simulation mechanism to select a new rule. Object-oriented modeling and programming, which has been proposed as a solution to the reusable software development, is used to design the system modules.Finally,system integration is discussed and the role of scheduling is also described.
Xu, Chun-Lai, and 許春來. "A study for knowledge-based computer integrated manufacturing system." Thesis, 1987. http://ndltd.ncl.edu.tw/handle/96825503580027469690.
Повний текст джерелаAhmed, Muhammad Bilal. "Smart virtual product development system." Thesis, 2021. http://hdl.handle.net/1959.13/1420676.
Повний текст джерелаThe aim of this research is to address issues related to the effective use of information, knowledge and experience in industry during the process of product development. In this thesis, we propose a novel approach to the support of design, manufacturing, and inspection planning at the early stages of product development. The system we have developed is based on Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA) techniques, and will henceforth be referred to as the Smart Virtual Product Development (SVPD) system. This system comprises three primary modules, each of which has been developed to cater to a need for digital knowledge capture for smart manufacturing in the areas of product design, production planning, and inspection planning. The individual modules related to each of these areas in turn will henceforth be referred to as the design knowledge management (DKM) module, the manufacturing capability analysis and process planning (MCAPP) module, and the product inspection planning (PIP) module respectively. Together these modules are fully capable of supporting the five phases of advanced product quality planning (APQP). The SVPD system is a system that can store experiential knowledge relating to previous projects, and makes that knowledge available to a user who presents a relevant query in the future. Formal decisional events or experiences can be comprehensively represented in SOEKS using a unique combination of Variables, Functions, Constraints and Rules. A query based on objectives relevant to one of the modules mentioned above and comprised of variables and functions particular to those objectives is fed into the system, which then provides a list of potential solutions based on the experiential knowledge stored in the system. The user selects the most appropriate solution from among those provided, and that is stored in the system as an answer to similar queries. In the event that the system cannot provide a solution, an expert will then be consulted, and that expert’s decision will be manually inputted into the system and stored. The system, therefore, either updates itself or is updated manually each time a new decision is made. Our experimental results show that the SVPD system is an expert decisional support system and can play a vital role in the establishment of Industry 4.0. The system will benefit manufacturing organizations through the facilitation of product design, manufacturing, and inspection planning.
Po-ShengTseng and 曾柏盛. "Development of a Knowledge-based System for Materials Additive Manufacturing." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/15959099279624200602.
Повний текст джерела國立成功大學
材料科學及工程學系
103
There are new knowledges generated in the field of additive manufacturing (AM) technologies. To extract knowledge effectively, we need a knowledge-based system with a clear structure. There are three aspects of AM technologies, including classification of processings, materials and application of products. A knowledge-based system has been established from the standpoint of knowledge management and demonstrated in the form of websites. The knowledge-based system is separated to three divisions, which are classification of processings, materials and application of products. In the first division, processings are classified into seven categories based on phases of starting materials. Phases of starting materials involve liquid phase, semi-liquid phase and solid phase. AM technologies based on liquid phase include vat photo-polymerization, material jetting and binder jetting . AM technology based on semi-liquid phase is termed as fused deposition modeling . AM technologies based on solid powders include powder bed fusion and direct energy deposition. AM technologies based on solid sheets is known as sheet lamination . In the second division, the materials are divide into three categories, which are polymers, metals and ceramics. In the third division, applications of products are illustrated by case studies. Three divisions are presented in the form of a clear-structured website . The knowledge-based system for additive manufacturing is valuable for knowledge management. Comparing with other methods of knowledge acquisition, the knowledge-based system is easier to be updated , therefore it is an excellent medium for popularisation the information related to AM technologies.
Wu, Zheng-Nan, and 吳政南. "Prototype System for Smart Manufacturing Factory Based on Cloud and IoT Technologies." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/jm9xub.
Повний текст джерела國立高雄科技大學
資訊工程系
107
With the rapid development of science and technology and the progress of the times, the technology of the Internet of Things has become more and more mature. In the past few years, a new wave of scientific and technological revolutions and industrial changes has emerged in the world. Developed countries have followed the trend and have thrown out the stimulus for real economic growth. The national strategy and plan hopes to regain the competitive advantage in manufacturing through technological advancement and industrial policy adjustment. Among them, Germany, one of the major industrial countries, proposed the “Industry 4.0” reform method, which was designed in accordance with the industrial characteristics of its own country. The main core is intelligent manufacturing, through embedded processors, memories, sensors and communications. Modules, which connect equipment, products, raw materials, and software, so that products and different production equipment can be interconnected and exchange information. In other words, Germany's Industry 4.0 can correct errors, optimize and control and adjust production lines in the future. Because of its industrial type, Taiwan's small and medium-sized enterprises are not able to have sufficient funds, product information and customer information, just like Germany or international companies, to make the factory complete and systematically intelligent to enhance competition. We need to design different smart factory solutions for different types and conditions of different factories. This paper will use a certain enzyme factory in Taiwan as a case to design a prototype of a smart factory plan to solve the current problems of the plant. To increase productivity has brought more benefits.
CHEN, WEI-CHUNG, and 陳為仲. "Implementation of an Intelligent Production System based on the Smart Manufacturing Technologies." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/89sj6s.
Повний текст джерела國立臺北科技大學
機械工程系機電整合碩士班
107
This research aims to build a small scale autonomous factory based on the Cyber Physical System (CPS) and Internet of Things (IoT).This factory has 3 CNC laser engraving machines as the core platform and smart manufacturing technologies. The developed system uses communication network to integrate the physical manufacturing machines and information of customized orders by various software processing, data management, and automation techniques to realize a cyber-physic system as well as a flexible manufacturing system. The system is designed academic research on the Industry 4.0 and related technologies. Besides the abovementioned automation, production data collection via web-link devices are also implemented to provide real-time facility monitoring and big data analysis for quality assurance, production management and other purposes. This thesis consists of two parts, system implementation and data analysis. The system implementation is based on the smart manufacturing and focused on the flexibility production, cyber-physic system and IoT. The implemented system has 3 CNC laser engraving machines with different laser power generators to mimic the variance of machines in the real world. Furthermore, flexible and customized designed tags are chosen to be the products so that the system has to face the challenges of flexibility. An internet-based order-making interface program will also be integrated. For the data analysis, a user interface is created to collect data from CNC machines and save it in the cloud server for analysis. Based on the collected data, machine efficiency and health can be predicted and feed-backed immediately to adjust the production settings for quality improvement and the prepare for preventive maintenance and monitoring of machines.
ZHENG, LI-SHENG, and 鄭禮聖. "Design and Implementation of a Cloud-based Prototype System for Smart Manufacturing Execution." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/hmgcpj.
Повний текст джерела國立高雄科技大學
資訊工程系
108
Smart manufacturing is a popular issue in recent years, it had been three revolution of industrial during the past. Start from the first revolution of industrial, called industrial 1.0 ,it's a machined age cause by the introduction of steam engine, then the second revolution of industrial, called industrial 2.0, use electric power to make a great amount of product, and the third revolution of industrial, called industrial 3.0, use PLC/CNC controller and robotic arm to improve the Automated control system, and now is the fourth revolution of industrial, Combine network and hardware called industrial 4.0, it's the background concept of the Smart manufacturing. There is lot of activity to research and improve the development of smart manufacturing, but stand in those industry's shoes, there is no established concept on smart manufacturing, it's said to solved the different demand of industry. But there is a common point that's to break the old view of industry, and developing a humanity way of manufacturing. The pourpose of this research is to design and implement a cloud-based prototype system for smart manufacturing execution. combind the concept of smart manufacturing, useing HMVC construst to build a management system of business. Useing cloud technology to transferthe firsthand information and analysis the data, to find the potential sales approach of salesperson,it's can also improve the industrial value of the related products.
KUO, CHIEN-TING, and 郭建廷. "Implementation of Smart Manufacturing Information Management System based on Cloud Edge Computing Technology." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/628jav.
Повний текст джерела國立高雄科技大學
資訊工程系
107
Nowadays, we live in a period that people highly seek digitalization and artificial intelligence. The Industrial structure and consumption patterns in the world is hugely changing because of various new technologies developing. The industries, products, and services applied new skills widely appear in a short time. The new skills are continuously innovating, developing, and expanding their application area, making the existing industry business models constantly transforming. Every industry expects that artificial intelligence would optimize the supply chain and big data analysis would make enterprises able to forecasting and quickly grasping the clients’ demands. Then the enterprise could affiliate smart manufacturing to offer faster service and better products when trading in a more efficient way. Therefore, they can provide great trading experience for clients, and obtain great profit. The purpose of this thesis is to study how to Cloudization and Systematization the data of a traditional transaction, applying machine learning and big data technology, combined with the website front-end technology and the database management system to design and to implement a smart business system, and under such a framework how to implement business expects like reducing time cost, increasing work efficiency and turnover rate, and analyzing visiting modes smartly, and then affiliate smart manufacturing to apply artificial intelligence to all the parts of supply chain. When trading with various group of clients, the process of getting the client’s demand until producing products must be smarter in order to make the enterprise quickly set the business strategy and goal for every client group. This Research explores how to introduce machine learning and big data technologies into a business system, and further integrates the data from clients and analyze the data to promote the decision-making wisdom of the enterprise.
Mohamed, N. M. Z. Nik, and M. Khurshid Khan. "The development of a hybrid knowledge-based system for the design of a Low Volume Automotive Manufacturing (LVAM) system." 2012. http://hdl.handle.net/10454/9524.
Повний текст джерелаA conceptual design approach is an important stage for the development of a hybrid Knowledge-Based System (KBS) for Low Volume Automotive Manufacturing (LVAM). The development of a hybrid KBS, which is a blend of KBS and Gauging Absences of Pre-requisites (GAP), is proposed for LVAM research. The hybrid KB/GAP system identifies all potential elements of LVAM issues throughout the development of this system. The KBS used in the system design stage of the LVAM system analyses the gap between the existing and the benchmark organisations for an effective implementation through the GAP analysis technique. The proposed KBLVAM model at the design stage explores three major components, namely LVAM car body parts manufacturing perspective, LVAM competitive priorities perspective and LVAM lean environment perspective. Initial results reveal that the KBLVAM system has identified, for each perspective modules and sub-modules, the Problem Categories (PC) in a prioritised manner.
The financial support by the Malaysian Government, Universiti Malaysia Pahang and University of Bradford for this research is grateful acknowledged.
Lee, Yuan-Chen, and 李元鎮. "Design and Verification of Intelligent Mold-manufacturing Navigating System with Knowledge-based Management." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/41592466775695265669.
Повний текст джерела中原大學
機械工程研究所
96
With the flourishing development of 3C industry, the products get more diversified and the life cycle keeps reducing. Therefore, the mold development and the manufacturing time should be reduced as requested. Due to the shortage of professional engineers, the overall mold industry is unable to achieve the product specifications only by the accumulated experiences and knowledge. Nowadays, in order to maintain and enhance the competitiveness, the important goal of enterprise is to shorten the time of mold design and manufacturing, train new engineers in the shortest time, and upgrade the quality of products. The first part of this study is to develop a mold-manufacturing navigating system with knowledge management on the CAD/CAM software Pro/ENGINEER 3.0 Browser. The CAM engineers use the mold-manufacturing navigating system with process-planning navigating system to produce the machine codes of processing machine. The historical database and technological database of the system are used to prevent the unnecessary mistakes caused by the lack of experience. Since Pro/ENGINEER and UG are the most commonly used CAD/CAM software, the second part of this study is to migrate the mold-manufacturing navigating system with knowledge management to the CAD/CAM software UG NX5 Browser, and compare the capability and practicality. This study used cell-phone core and cavity as examples. The time and benefits of using and without-using mold-manufacturing navigating system is compared. The results show that using the mold-manufacturing navigating system can shorten the time of NC programming from 60~120 minutes to 30~60 minutes, and it can also save time at wire-cutting programming and electrode designing. The assistance of historical database and technological database can not only reduce the mistakes of machine-path planning, but also increase the rate of tool usage.
Mohamed, N. M. Z. Nik, and M. Khurshid Khan. "Knowledge based system implementation for lean process in low volume automotive manufacturing (LVAM) with reference to process manufacturing." 2011. http://hdl.handle.net/10454/9541.
Повний текст джерелаGlobal manufacturing industry mostly depends on new product development and processes to become competitive. The product development process for automotive industry is normally complicated, lengthy, expensive, and risky. Hence, a study of lean manufacturing processes for low volume manufacturing in automotive industry is proposed to overcome this issue by eliminating all wastes in the lengthy process. This paper presents a conceptual design approach to the development of a hybrid Knowledge Based (KB) system for lean process in Low Volume Automotive Manufacturing (LVAM). The research concentrates on the low volume processes by using a hybrid KB system, which is a blend of KB system and Gauging Absences of Pre-requisites (GAP). The hybrid KB/GAP system identifies all potential waste elements of low volume process manufacturing. The KB system analyses the difference between the existing and the benchmark standards for lean process for an effective implementation through the GAP analysis technique. The proposed model explores three major lean process components, namely Employee Involvement, Waste Elimination, and Kaizen (continuous improvement). These three components provide valuable information in order for decision makers to design and implement an optimised low volume manufacturing process, but which can be applied in all process manufacturing, including chemical processing.
Khan, M. Khurshid, I. Hussain, and S. Noor. "A knowledge based methodology for planning and designing of a flexible manufacturing system (FMS)." 2011. http://hdl.handle.net/10454/9521.
Повний текст джерелаThis paper presents a Knowledge-Based (KB) integrated approach for planning and designing of number of machining centres, selection of material handling system, layout and networking architecture and cost analysis for a Flexible Manufacturing Systems (FMS). The KB model can be applied for integrating the decision issues at both the planning and designing stages of an FMS for three types of layouts (single row, double row, and loop) and three MHS types (robot-conveyor, AGV-conveyor and a hybrid AGV-robot-conveyor). The KB methodology starts from a suitable information input, which includes demand per year of part types, part type’s information, machining centre’s calculation, Material Handling System (MHS) selection, machining centre’s layout selection, networking selection and financial analysis. The KB methodology is developed by using AM, an expert system shell, and contains over 1500 KB rules. The performance of the system has been verified and validated through four published and four industrial case studies, respectively. The validation results from industry show that the KB methodology is capable of considering detailed design inputs and is able to assist in designing and selecting a practical FMS. It is concluded that a KB system for the present FMS application is a viable and efficient methodology.
Milana, M., M. Khurshid Khan, and J. Eduardo Munive-Hernandez. "A framework of Knowledge Based System for Integrated Maintenance Strategy and Operation." 2014. http://hdl.handle.net/10454/8767.
Повний текст джерелаThe dependency of maintenance as a manufacturing logistic function has made the considerations and constrains of maintenance decisions complex in nature. The rapid growth of automation in manufacturing process has also increased the role of maintenance as an inseparable business partner. As consequence, maintenance strategy and operations should always be aligned with business and manufacturing perspectives within a holistic and integrated manner to achieve competitive advantage. This paper presents a framework of Knowledge Based System for Integrated Maintenance Strategy and Operation (KBIMSO) linked to business and manufacturing perspectives. The KBIMSO framework has novelty of simultaneously highlighting the elements of business, manufacturing and maintenance perspectives which contribute to direct maintenance performance and can be used by the companies to evaluate their existing maintenance system in relation to business competitive priorities and manufacturing process requirements in order to gain optimal maintenance performance as the competitive driver.
Support for this study is provided by the Directorate of Higher Education, Ministry of National Education, Republic of Indonesia and the University of Bradford, the United Kingdom.
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Milana, M., M. Khurshid Khan, and J. Eduardo Munive-Hernandez. "Design and development of Knowledge Based System for Integrated Maintenance Strategy and Operations." 2016. http://hdl.handle.net/10454/16898.
Повний текст джерелаThe importance of maintenance has escalated significantly by the increase in automation in manufacturing processes. This condition changed the perspective of maintenance from being considered as an inevitable cost to being seen as a key business function to drive competitiveness. Consequently, maintenance decisions need to be aligned with the business competitive strategy as well as the requirements of manufacturing/quality functions in order to support manufacturing equipment performance. Therefore, it is required to synchronise the maintenance strategy and operations with business and manufacturing/quality aspects. This article presents the design and development of a Knowledge Based System for Integrated Maintenance Strategy and Operations. The developed framework of the Knowledge Based System for Integrated Maintenance Strategy and Operations is elaborated to show how the Knowledge Based System for Integrated Maintenance Strategy and Operations can be applied to support maintenance decisions. The knowledge-based system integrates the Gauging Absences of Prerequisites methodology in order to deal with different decision-making priorities and to facilitate benchmarking with a target performance state. This is a new contribution to this area. The Knowledge Based System for Integrated Maintenance Strategy and Operations is useful in reviewing the existing maintenance system and provides reasonable recommendations for maintenance decisions with respect to business and manufacturing perspectives. In addition, it indicates the roadmap from the current state to the benchmark goals for the maintenance system.
Ministry of Research, Technology and Higher Education of the Republic of Indonesia and the University of Bradford, UK.
Peres, Ricardo Alexandre Fernandes da Silva. "An agent based architecture to support monitoring in plug and produce manufacturing systems using knowledge extraction." Master's thesis, 2015. http://hdl.handle.net/10362/16562.
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