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نتیجه جستجو - Smart factories

تعداد مقالات یافته شده: 7
ردیف عنوان نوع
1 Ontology-augmented Prognostics and Health Management for shopfloor-synchronised joint maintenance and production management decisions
پیش آگهی و مدیریت سلامت با هستی شناسی تقویت شده برای تصمیمات مدیریت تولید و نگهداری مشترک هماهنگ شده با کف مغازه-2021
In smart factories, guaranteeing shopfloor-synchronised and real-time decision-making is essential to be responsive to the ever-changing internal environment, namely the shopfloor of the production system and assets. At operational level, decisions should balance counter acting objectives of maintenance and production; there- fore, their decision-making processes should be joint and coordinated, to fulfil production requirements considering the health state of the assets. The knowledge of the current state is promoted by the application of Prognostics and Health Management (PHM) as an aid to support informed decision-making. Nevertheless, PHM- purposed information is usually not complete in terms of production requirements. To support joint maintenance and production management decisions, an ontological approach is proposed. The ontology, called ORMA (Ontology for Reliability-centred MAintenance), has a modular structure, including formalisation of asset, pro- cess, and product knowledge. Via suitable relationships, rules, and axioms, ORMA can infer product feasibility based on the current health state of the assets and their functional units. ORMA is implemented in a Flexible Manufacturing Line at a laboratory scale. Therein, an integrated solution, involving a health state detection algorithm that interacts with the ontology, supports human decision-making via a web-based dashboard; joint maintenance and production management decisions can be then taken, relying on diversified information pro- vided by the PHM algorithm as well as the augmentation via ontology reasoning. The proposed ontology-based solution represents a step towards reconfigurability of smart factories where human and automated decision- making processes work in synergy.
keywords: هستی شناسی | استدلال | پیشگویی و مدیریت بهداشت | phm | نگهداری | تولید | Ontology | Reasoning | Prognostics and health management | PHM | maintenance | production
مقاله انگلیسی
2 چارچوب اجرا و پیاده سازی چند مرحله ای برای مدیریت زنجیره تامین هوشمند تحت صنعت 4:0
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 11 - تعداد صفحات فایل doc فارسی: 38
پتانسیل واقعی صنعت 4.0، که محصول جانبی انقلاب صنعتی چهارم است، عملاً قابل تحقق نیست. البته تا زمانی این موضوع صحت دارد که کارخانه‌های هوشمند در زنجیره‌های تامین، با سیستم‌هایشان و ماشین‌هایشان به یک سیستم شبکه مشترک متصل شوند. چند سال اخیر شاهد افزایش پذیرش و اجرای مؤلفه‌های صنعت 4.0 بوده ایم. با این حال، مرحله بعدی کارخانه‌های هوشمند که زنجیره‌های تامین هوشمند خواهند بود، هنوز در دوران ابتدایی خود است. علاوه بر این، نیاز هم‌زمانی به حفظ تمرکز بر اجرای مفهومی که صنعت 4.0 مطرح می‌کند در سطح زنجیره تامین وجود دارد. این امر به منظور به دست آوردن مزایای انتها به انتها و همچنین اجتناب از مسائل مربوط به سازگاری سازمان به سازمان که ممکن است بعداً دنبال شود، مهم است. هنگام در نظر گرفتن این مفهوم، تحقیقات محدودی در مورد مسائل مربوط به اجرای صنعت 4.0 در سطح زنجیره تامین وجود دارد. از این رو، با در نظر گرفتن کمبود ادبیات و تحقیقات موجود، در مورد پدیده ای که آینده کسب و کار و صنعت را مشخص می کند، این مطالعه از یک رویکرد اکتشافی برای به تصویر کشیدن پیاده سازی مفاهیم صنعت 4.0 در چندین لایه زنجیره تامین استفاده می کند.
واژگان کلیدی: صنعت 4.0 | کارخانه های هوشمند | مدیریت زنجیره تامین هوشمند
مقاله ترجمه شده
3 A method of NC machine tools intelligent monitoring system in smart factories
روش ابزار و ماشین آلات NC سیستم نظارت هوشمند در کارخانه های هوشمند-2020
The construction of effectual connection to bridge the gap between physical machine tools and upper software applications is one of the inherent requirements for smart factories. The difficulties in this issue lies in the lack of effective and appropriate means for real-time data acquisition, storage and processing in monitoring and the post workflows. The rapid advancements in Internet of things (IoT) and information technology have made it possible for the realization of this scheme, which have become an important module of the concepts such as “Industry 4.0”, etc. In this paper, a framework of bi-directional data and control flows between various machine tools and upper-level software system is proposed, within which several key stumbling blocks are presented, and corresponding solutions are subsequently deeply investigated and analyzed. Through monitoring manufacturing big data, potential essential information are extracted, providing useful guides for practical production and enterprise decision-making. Based on the integrated model, an NC machine tool intelligent monitoring and data processing system in smart factories is developed. Typical machine tools, such as Siemens series, are the main objects for investigation. The system validates the concept and performs well in the complex manufacturing environment, which will be a beneficial attempt and gain its value in smart factories..
Keywords: CNC | Monitoring system | Data analysis | Machine tool | Smart factory
مقاله انگلیسی
4 Improved behavior model based on sequential rule mining
مدل رفتار بهبود یافته براساس کاوش قوانین پیوسته-2018
The fourth industrial revolution leads the manufacturing companies to develop future and smart factories by merging automation and digitalization to result a more efficient production method. An evolutionary and competitive experimental approach is necessary to foster the innovation and the rapid change of the automation and digitalization. Consequently, software becomes an important component of industrial automation. One of the major challenge in Industry 4.0 is to industrialize the production of software. Software factory, as one industry with a virtual production line to produce software for manufacturing companies, offers a form of flexible employment, called as telecommuting work. Although this form brings many benefits for both employee and employers, some risks associated with telecommuting work exist. Monitoring the employee behavior is one of the employer way to see the accountability of the employee. Hence, understanding the human behavior during the production process would be an important issue for fulfilling overall operational excellence in software factory. Among approaches proposed to discover the human behavior based on the sequence activities, process mining is one of which has received attentions lately. While most recent process mining approaches in the domain of human behavior address process discovery and post-analysis, few of them have paid attentions on pre-analysis. The pre-analysis is one of the ways to produce a reliable and high-quality of event log which purposely impacts on discovering a daily common behavior and disregarding irregular sequential behavior. This study aims to propose a new way of pre-analysis using sequential rule mining. The key contributions of this research first, is to determine the potential local behaviors using sequential rule mining considering time constraint. Second, the local behaviors are used to enhance event log for discovering relevant behavior model. Third, the mined model is verified by performing conformance checking approach to check the conformity between the behavior model and the real logs based on three measurements: f-measure, ABA, and DMF. The resulting local behaviors, called as rules, can be used for guiding stakeholders to pinpoint the relevant behavior for human capital and productivity enhancement.
Keywords: Relevant behavior model ، Log filtering ، Process mining ، Sequential rule mining
مقاله انگلیسی
5 Industrial Internet of Things Monitoring Solution for Advanced Predictive Maintenance Applications
راه حل نظارتی اینترنت اشیاء صنعتی برای برنامه های نگهداری پیشگیرانه پیشرفته -2017
Internet of Things (IoT) solutions in industrial environments can lead nowadays to the development of innovative and efficient systems aiming at increasing op erational efficiency in a new generation of smart factories. In this direction the article presents in detail an advanced Industrial IoT (IIoT) solution, the NGS-PlantOne system, specially designed to enable a pervasive monitoring of industrial machinery through battery-powered IoT sensing devices, thus allow ing the development of advanced predictive maintenance applications in the considered scenario. To the end of evaluating the performance of the devel oped IIoT system in a real environment, the NGS-PlantOne solution has been first installed and then set in operation in a real electricity power plant. The deployed testbed, based on 33 IoT sensing devices performing advanced tem perature and vibration monitoring tasks, has been kept in operation for two months while evaluating transmission delays and system operating life through power consumption measures. Performance results show as the developed IIoT solution benefits from all the advantages provided by the adopted IoT protocols, guaranteeing that each node is reachable through simple IP-based techniques with an acceptable delay, and showing an estimated average life of 1 year in case of each IoT smart device is configured to send collected and elaborated data every 30 minutes.
Keywords: Industrial Internet-of-Things | Smart Plants |Industrial monitoring
مقاله انگلیسی
6 Internet of Things and Big Data - The Disruption of the Value Chain and the Rise of New Software Ecosystems
اینترنت اشیا و داده های بزرگ - اختلال زنجیره ارزش و ظهور اکوسیستم های نرم افزاری جدید-2016
IoT connects devices, humans, places, and even abstract items like events. Driven by smart sensors, powerful embedded microelectronics, high-speed connectivity and the standards of the internet, IoT is on the brink of disrupting todays value chains. Big Data, characterized by high volume, high velocity and a high variety of formats, is a result of and also a driving force for IoT. The datafication of business presents completely new opportunities and risks. To hedge the technical risks posed by the interaction between “everything”, IoT requires comprehensive modelling tools. Furthermore, new IT platforms and architectures are necessary to process and store the unprecedented flow of structured and unstructured, repetitive and non-repetitive data in real-time. In the end, only powerful analytics tools are able to extract “sense” from the exponentially growing amount of data and, as a consequence, data science becomes a strategic asset.
The era of IoT relies heavily on standards for technologies which guarantee the interoperability of everything. This paper outlines some fundamental standardization activities. Big Data approaches for real-time processing are outlined and tools for analytics are addressed. As consequence, IoT is a (fast) evolutionary process whose success in penetrating all dimensions of life heavily depends on close cooperation between standardization organizations, open source communities and IT experts.
Keywords: Internet of Things | Smart Factories | Big Data | Software Platforms | Data Science
مقاله انگلیسی
7 نقش اینترنت اشیا در منابع انرژی تجدید پذیر
سال انتشار: 2016 - تعداد صفحات فایل pdf انگلیسی: 5 - تعداد صفحات فایل doc فارسی: 8
مفهوم شهرهای هوشمند با تکامل از مدل های مفهومی به مراحل توسعه، در حال تبدیل شدن به یک واقعیت است. انرژی و پخش بار انعطاف پذیر، قابل اطمینان، کارآمد و یکپارچه، بخش های ضروری برای انرژی دار کردن و توان رسانی به خدمات شهرهای هوشمند مانند بیمارستان های هوشمند، ساختمان های هوشمند، کارخانه های هوشمند و ترافیک و حمل و نقل هوشمند هستند. انتظار می رود که تمام این خدمات هوشمند با استفاده از شبکه های هوشمند انرژی و برق که از مهم ترین ارکان این شهرها به شمار می روند، بدون وقفه کار کنند. برای متصل و هماهنگ نگه داشتن خدمات شهرهای هوشمند، اینترنت اشیا (IoT) و محاسبات ابری، در این انتقال بسیار مهم هستند. این مقاله، نقش IoT در الحاق منابع انرژی تجدید پذیر در شبکه قدرت را ارائه می کند.
کلمات کلیدی: انرژی هوشمند | شبکه هوشمند | شهرهای هوشمند | اینترنت اشیا | 6LoWPAN
مقاله ترجمه شده
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