In order to reduc e the manufacturing costs for cement, it is very important to optimise the existing . Log ... HOLTEC has undertaken Performance Optimisation of the ce ment grinding circuits by …
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Since FCA has launched the world class manufacturing (WCM) model as a corporate philosophy starting ... The new method could be used as a guide for specialists to …
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This paper presents a data-driven approach to improving the productivity of manufacturing companies operating under Make-To-Order (MTO). In this study, a …
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Edge computing solutions, which process data close to the manufacturing site, can reduce latency and accelerate response times, enabling immediate action upon detection of a …
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The overall objective of this study is to investigate the patterns of typical FFF process failures, and develop a data-driven failure diagnostic method for online process …
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One reciprocating screw injection molding process from a Chinese manufacturing company motivated us to perform this study, and the screw injection molding machine is shown …
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The above techniques also exhibited good diagnosis capability. The study indicates that statistical techniques in spite of their simplicity could be as powerful as machine learning and deep ...
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In this paper, we present current research and developments of FDD approaches for process monitoring as well as a broad literature review of many useful FDD approaches. Implementation procedure...
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Integrating Machine Learning (ML) in industrial settings has become a cornerstone of Industry 4.0, aiming to enhance production system reliability and efficiency through Real-Time Fault Detection and Diagnosis (RT-FDD). This …
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The entire diagnostic process can usually be completed within the space of a few weeks. The result is an integrated implementation plan that addresses operational cost levers along with concrete organizational, IT and procedural …
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Due to the lengthy and complicated characteristics of semiconductor manufacturing process, many variables influence the model, which also may affect each other. …
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Abstract. Objective: Medical device development, from the product's conception to release to market, is very complex and relies significantly on the application of exact processes. This paper aims to provide an analysis and summary of …
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This paper explores the integration of Artificial Intelligence (AI) in process control and diagnostics in semiconductor manufacturing. It highlights current trends, including machine learning (ML) …
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Diagnostic analytics is a critical process in data analysis that focuses on uncovering the reasons behind past outcomes. While descriptive analytics explains "what …
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Manufacturing process monitoring involves collecting process data and quality character data and designing algorithms to extract statistical variables for monitoring; the state …
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The development of information technology and process technology have been enhanced the rapid changes in high-tech products and smart manufacturing, specifications …
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The case studies of Siemens, General Electric, Toyota, Boeing, and Intel illustrate AI's transformative potential across various manufacturing industry sectors. Through the integration of AI-powered technologies, these firms have achieved …
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Multivariate sensor data collected from manufacturing and process industries represents actual operational behavior and can be used for predictive maintenance of the plants.
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The main roles of fault detection and diagnosis (FDD) for industrial processes are to make an effective indicator which can identify faulty status of a process and then to take a …
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This work proposes an AM control framework that divides the related studies into three feedback loops, including the in-situ monitoring of process defects, fault diagnosis of 3-D …
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Aiming to solve the problems of the inaccurate dimension reduction of high-dimensional data and insufficient information utilization in traditional manufacturing process …
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Manufacturers need standards and guidelines to effectively enable, integrate, verify, and validate monitoring, diagnostic, and prognostic technologies to enhance factory floor-level …
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The review by Arpitha et al. offers a comprehensive exploration of Machine Learning and Deep Learning methods used in Fault Detection and Diagnosis within the metal etching process in semiconductor manufacturing. The authors …
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In five of these studies, visual object detection, surface defect detection, machine production scheduling application, fault diagnosis and prediction, and monitoring of the …
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Over the past years, the rapidly increasing global industry competition has highly raised the standards in modern manufacturing. CNC machine tools convert raw metal …
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This study concerns a case study carried out in an automotive company which aims at improving its flows within the production workshop by pulling the physical flow and minimizing the different wastes.
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Sensors enable the simple collection of data, but these devices must still provide the right information at the right time for fault detection and avoidance. In general, a fault is defined as the departure of an observed variable from an acceptable range, and the fundamental cause of this abnormality is called the basic event or the roo…See more on link.springer
This study proposed a hybrid learning-based system for on-line monitoring and diagnosis of manufacturing processes, where some key process parameters (i.e., system …
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At present production systems in car manufacturing processes are under high demand requirements and maintenance plans are of great importance in order to achieve the …
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