با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
Non-destructive and contactless estimation of chlorophyll and ammonia contents in packaged fresh-cut rocket leaves by a Computer Vision System
تخمین غیر مخرب و بدون تماس محتویات کلروفیل و آمونیاک در برگ های موشک تازه برش خورده بسته بندی شده توسط یک سیستم کامپیوتر ویژن-2022
Computer Vision Systems (CVS) offer a non-destructive and contactless tool to assign visual quality level to fruit and vegetables and to estimate some of their internal characteristics. The innovative CVS described in this paper exploits the combination of image processing techniques and machine learning models (Random Forests) to assess the visual quality and predict the internal traits on unpackaged and packaged rocket leaves. Its perfor- mance did not depend on the cultivation system (traditional soil or soilless). The same CVS, exploiting its ma- chine learning components, was able to build effective models for either the classification problem (visual quality level assignment) and the regression problems (estimation of senescence indicators such as chlorophyll and ammonia contents) just by changing the training data. The experiments showed a negligible performance loss on packaged products (Pearson’s linear correlation coefficient of 0.84 for chlorophyll and 0.91 for ammonia) with respect to unpackaged ones (0.86 for chlorophyll and 0.92 for ammonia). Thus, the non-destructive and con- tactless CVS represents a valid alternative to destructive, expensive and time-consuming analyses in the lab and can be effectively and extensively used along the whole supply chain, even on packaged products that cannot be analyzed using traditional tools.
keywords: Contactless quality level assessment | Diplotaxis tenuifolia L | Image analysis | Packaged vegetables | Senescence indicators prediction
یک مدل ریاضی چند منظوره برای زنجیره تامین داروسازی با توجه به تراکم دارو در کارخانهها
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 15 - تعداد صفحات فایل doc فارسی: 47
مدیریت زنجیره تامین ( SCM ) , به روش یکی از مسائل مهم در جنبه مدیریتی , نقش مهمی در مقابله با مسایل انسانی و مشکلات ایفا میکند . به دلیل برخی محدودیتها ( به عنوان مثال , ظرفیت تولید و ظرفیت ذخیرهسازی ) و خواسته ها( به عنوان مثال , کاهش هزینه و افزایش درآمد ) , مدیران زنجیره تامین همیشه به دنبال بهترین پاسخ به مقدار و نوع ارتباط بین سطوح مختلف SCM هستند . در تحقیقات آتی , یک زنجیره تامین دارو ( PSC ) با سه تابع هدف توسعهیافته , با هدف به حداقل رساندن هزینههای کلی , خواستههای برآورده نشده , و کاهش زمان انتظار در ورودی کارخانه . در تحقیقات آتی , موضوع کلی و تحقیقات در مدلسازی PSC و حل مساله مورد بحث قرار گرفتهاند . سپس یک مدل برنامهریزی غیرخطی با تحقیقات قبلی برای حل کاستیهای موجود پیشنهاد شدهاست.
همچنین روشهای تصمیمگیری چند هدفه برای انطباق با اهداف متناقض مدل به طور همزمان استفاده میشوند . سپس نرمافزار تجاری GAMS برای حل مشکل اندازههای مختلف به کار میرود . در نهایت ، تحلیل حساسیت گسترده و ارزیابی نتایج مورد بحث قرار میگیرد و پیشنهادهای توسعه آتی ارایه میشوند.
واژه های کاربردی : زنجیره تامین دارو | فسادپذیری | زمانبندی | فهرست | نظریه کیوینگ
|مقاله ترجمه شده
MagLoc : A magnetic induction based localization scheme for fresh food logistics
MagLoc: یک طرح محلی سازی مبتنی بر القای مغناطیسی برای تدارکات مواد غذایی تازه-2022
An IoT infrastructure to continuously monitor the fresh food supply chain can quickly detect food quality and contamination issues and thereby reduce costs and food wastage. This, in turn, involves several challenges including the development of inexpensive quality/contamination sensors to be deployed in a fine grain manner in the food boxes, technologies for sensor level communications, online data management and analytics, and logistics driven by such analytics. In this paper, we study the issues related to the communication among sensing modules deployed in the fresh food boxes and thereby an automated localization of the boxes that may have quality/contamination issues. In this context we study the near-field magnetic induction (NFMI) based communication and localization, as the ubiquitous RF communications suffer high attenuation through the water/mineral rich tissue media. An accurate localization of the sensors inside boxes within the food pallets is very challenging in this environment. In this paper we propose a novel magnetic induction based localization scheme, and show that with a small number of anchor nodes, the localization can be done without any errors for boxes as small as 0.5 meter on the side, and with small errors even for boxes half as big.
Keywords: Smart sensing | Industrial sensors | Food supply chain | Physical Internet | Magnetic communication | Localization
Integrating blockchain into supply chain safeguarded by PUF-enabled RFID
ادغام بلاک چین در زنجیره تامین که توسط RFID دارای PUF محافظت می شود-2022
Due to globalization, supply chain networks are moving towards higher complexity and becoming vulnerable to various kinds of attacks such as counterfeiting, information tampering, and so on. Appropriate approaches are necessary to tackle different types of attacks and to ensure the required supply chain security. In this paper, we have addressed the product counterfeiting issue using Physical Unclonable Function (PUF) enabled Radio Frequency Identification (RFID) tag. In this research, as a preferred alternative to the traditional centralized databases, blockchain technology has been leveraged to support anti-counterfeiting. Applying blockchain technology to supply chains can add many useful features such as decentralization, immutability, transparency, traceability, non-repudiation, complicated record-keeping, and so on. We have also used a reputation-based consensus algorithm for the blockchain which is less resource-intensive and thus will not indirectly impose additional cost on supply chain products. In the same research direction, we have devised our system architecture that is suitable for lightweight supply chain devices. The proposed three protocols namely: registration protocol, verification protocol, and transaction protocol along with the blockchain technology help to transfer the ownership of the authentic product and keep the sensitive supply chain information safe. An encryption-based secret sharing technique has also been introduced to assist data protection.
keywords: Blockchain | PUF | RFID | Secret sharing | Supply chain security
Introducing an application of an industry 4:0 solution for circular supply chain management
معرفی کاربرد راه حل صنعت 4:0 برای مدیریت حلقه تأمین دایره ای-2021
In recent years, sustainable supply chain management practices have been adopted by companies that desire to reduce the negative environmental and social impacts within their supply chains. Within this perspective, a circular approach has been developed in the supply chain literature. Circular economy models and solutions assisted by industry 4.0 technologies have been developed to transform products in the end of their life cycle into new products with different use. In this paper an industry 4.0 waste-to- energy solution is developed and applied in a pilot case study comprised by a real-world supply chain to evaluate the sustainability performance of circular supply chain management (CSCM). The ﬁndings show that redesigning supply chains for circular economy with the use of Industry 4.0 technologies, can enable circular supply chain management. Clear beneﬁts are provided linking the proposed solution to the six circular economy dimensions of the ReSOLVE model i.e. regenerate, share, optimize, loop, virtualise, and exchange. Improved availability of personnel (5% and 15%) and ﬂeet resources (15%) are identiﬁed as some of the key quantitative beneﬁts, while supply chain traceability through the full visibility and automation offered by the proposed solution, are some of the key non-quantiﬁable out- comes. The present work seeks to contribute to the existing literature by providing empirical evidence of how industry 4.0 and circular economy are applied in practice. Implications for managers and policy makers, along with the study limitations and further research paths are also presented.© 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-NDlicense (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Circular economy | Circular supply chain management (CSCM) | Industry 4.0 | Waste-to-energy | ReSOLVE model
Environmental hotspots analysis: A systematic framework for food supply chains and implementation case in the UK poultry industry
تجزیه و تحلیل کانون های محیطی: چارچوبی سیستماتیک برای زنجیره های تأمین مواد غذایی و موارد پیاده سازی در صنعت طیور انگلیس-2021
Environmental sustainability analyses of end-to-end food supply chain (SC) operations need to be per- formed regularly to accommodate reconﬁguration opportunities arising in the global business landscape. This research scrutinises the pertinent literature and identiﬁes the challenges of data availability, data obsolescence, computational complexity, and data speciﬁcity that associate to well-established environmental assessment methodologies, and proposes a stepwise approach that considers key players and processes for generating “close to real-time snapshots” of the main environmental hotspots for the focus ﬁrm. The applicability of the proposed systematic approach is demonstrated via an implementation at a resource-intensive sector of signiﬁcant scale, i.e., the UK poultry industry. Overall, this research con- tributes to the SC environmental sustainability management domain by guiding the mapping and identiﬁcation of environmental hotspots across end-to-end networks of operations in the form of a stepwise framework, and through articulating several research propositions.© 2021 Elsevier Ltd. All rights reserved.
Keywords: Environmental sustainability | Hotspots analysis | Food supply networks | Supply chain management | Systematic approach
Developing and solving an integrated model for production routing in sustainable closed-loop supply chain
توسعه و حل یک مدل یکپارچه برای مسیر یابی تولید در زنجیره تأمین حلقه بسته پایدار-2021
Social and environmental sustainability has gained increasing importance in today’s complex supply chains. Accordingly, an integrated model for production routing in the sustainable closed-loop supply chain is presented in the current study. A three-objective mathematical model is also proposed to minimize supply chain costs, maximize social responsibility or social beneﬁts, and ﬁnally, minimize environmental emissions. Sample trial problems are solved in three groups of the small, medium, and large size using the BCO algorithm. To prove the efﬁciency of this algorithm, its results are compared with the results using the NSGA-II algorithm in terms of comparative metrics such as quality, diversity, and spacing, as well as the runtime to the solution. According to the results, in all cases, the BCO algorithm outperformed the NSGA-II algorithm as it achieved more qualitative and near-optimal solutions. Also, the diversity metric values showed that the BCO algorithm is stronger in the exploration and extraction of the solution feasible region. The results of the metric of spacing and runtime to solution also showed that the NSGA-II algorithm achieves the solution in lower runtime than the BCO algorithm and searches solutions space in a more uniform manner.© 2021 Elsevier Ltd. All rights reserved.
Keywords: Closed-loop supply chain | Sustainability | Production routing
Developing a two-stage model for a sustainable closed-loop supply chain with pricing and advertising decisions
در حال توسعه یک مدل دو مرحله ای برای یک زنجیره تامین حلقه بسته پایدار با تصمیمات قیمت گذاری و تبلیغات-2021
Closed-Loop Supply Chain (CLSC) has become a critical problem due to its effects on various factors including economic motivations, environmental concerns, and social impacts. Moreover, there are coordination tools, such as pricing and advertising, which impact its performance. In this paper, we offer a two-stage approach to model and solve a sustainable CLSC, taking into account pricing, green quality, and advertising. In the first stage, optimal decisions on pricing, greening, and advertising are made, while in the second stage, a fuzzy multi- objective Mixed Integer Linear Programming (MILP) model is used to maximize the total profit, reduce CO2 emissions, and improve social impacts. Suitable solution methods are introduced according to the scale of the problem. For small-scale instances, an augmented ϵ-constraint method is used to solve the problem. For large-scale instances, approximations are required, and a Lagrangian relaxation algorithm solves the problem in polynomial time. The performance of the proposed model is evaluated through various numerical examples. The results illustrate the applicability and efficiency of the model, while confirming significant improvements in sustainable objectives under optimal pricing, green quality, and advertising. Besides, the proposed Lagrangian relaxation method significantly reduces the computational time for large-scale instances, with only a 2.308% deviation from the optimal results.
Keywords: Sustainable closed-loop supply chain | Multi-objective programming | Supply chain pricing | Augmented ϵ-constraint | Lagrangian relaxation | CO2 emissions
Towards resilient and sustainable supply of critical elements from the copper supply chain: A review
به سمت تأمین انعطاف پذیر و پایدار عناصر حیاتی از زنجیره تامین مس: یک مرور-2021
The highly specialized materials needed for the de-carbonization of energy, smart devices and the internet of things have created supply concerns of critical elements used in these applications. Several critical elements are produced as by-products from base metal mining and processing. Increasing the capture of critical elements from existing operations should lead to a more resilient and sustainable supply of these elements. Towards this goal, this paper presents a review of the distribution behavior of five critical elements (selenium, tellurium, arsenic, antimony and bismuth) through the primary copper pyrometallurgical supply chain. This review identifies gaps in the distribution/concentration data of these elements in deposits and during mineral processing. Smelter dusts, refinery slimes and electrolyte are points of enrichment that can be targeted for additional recovery of these elements. Using published data, copper smelter dusts appear to contain enough arsenic and bismuth to meet the world’s supply needs. Industrial data collected from 29 refineries and represents ~46% of the worlds electrorefining production was extrapolated to examine the contained annual content of these five elements. Copper anodes contain 7900 tones/yr of selenium, 2300 tonnes/yr of tellurium, 24,000 tones/yr arsenic, 7100tonnes/yr of antimony and 5100 tones/yr of bismuth. The selenium and tellurium contents are 2–3 times and 4–5 times more than the current world’s annual production of these elements, respectively. While technology development in the processing of smelter dusts and refinery slimes could provide important breakthroughs, government and corporate collaboration are likely needed to encourage increased recovery of selenium, tellurium, arsenic, antimony and bismuth from the primary copper pyrometallurgical supply chain.
Keywords: Critical elements | Copper | Ore | Flotation | Smelting | Refining
Efficient and sustainable closed-loop supply chain network design: A two-stage stochastic formulation with a hybrid solution methodology
طراحی شبکه زنجیره تامین حلقه بسته کارآمد و پایدار: یک فرمول تصادفی دو مرحله ای با روش راه حل ترکیبی-2021
In recent years, consumers and legislators have pushed companies to design their supply chain networks to consider environmental and social impacts as an important performance outcome. Due to the role of resource utilization as a key component of logistics network design, another primary goal of design is ensuring available scarce resources are used as efficiently as possible across all facilities. To address efficiency issues in a sustainable closed-loop supply chain network, a stochastic integrated multi-objective mixed integer nonlinear programming model is developed in this paper, in which sustainability outcomes as well as efficiency of facility resource utilization are considered in the design of a sustainable supply chain network. In doing so, efficiency is assessed using a bi-objective output-oriented data envelopment analysis model. A hybrid three-step solution methodology is presented that creates a linear form of the original mixed integer nonlinear programming problem using piecewise McCormick envelopes approach. In the second step, an aggregated single objective programming model is derived by exploiting the multi-choice goal programming. Finally, a Lagrangian relaxation algorithm is developed to effectively solve the latter stochastic single objective mixed integer linear programming problem. The application of the proposed approach is investigated with data drawn from a case study in the electronics industry. This case study illustrates how firms may balance sustainability and efficiency in the supply chain network design problem. Further, it demonstrates the integration of efficiency results in improving economic aspects of sustainability as well as social responsibility outcomes, but also highlights the trade-offs that exist between efficiency and environmental impacts.
Keywords: Closed-loop supply chain network | Sustainability | Data envelopment analysis | Stochastic programming | Multi-choice goal programming | Lagrangian relaxation