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Alunite processing method selection using the AHP and TOPSIS approaches under fuzzy environment 被引量:4
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作者 Alizadeh Shahab Salari Rad Mohammad Mehdi Bazzazi Abbas Aghajani 《International Journal of Mining Science and Technology》 SCIE EI CSCD 2016年第6期1017-1023,共7页
Alunite is the most important non bauxite resource for alumina. Various methods have been proposed and patented for processing alunite, but none has been performed at industrial scale and no technical,operational and ... Alunite is the most important non bauxite resource for alumina. Various methods have been proposed and patented for processing alunite, but none has been performed at industrial scale and no technical,operational and economic data is available to evaluate methods. In addition, selecting the right approach for alunite beneficiation, requires introducing a wide range of criteria and careful analysis of alternatives.In this research, after studying the existing processes, 13 methods were considered and evaluated by 14 technical, economic and environmental analyzing criteria. Due to multiplicity of processing methods and attributes, in this paper, Multi Attribute Decision Making methods were employed to examine the appropriateness of choices. The Delphi Analytical Hierarchy Process(DAHP) was used for weighting selection criteria and Fuzzy TOPSIS approach was used to determine the most profitable candidates. Among 13 studied methods, Spanish, Svoronos and Hazan methods were respectively recognized to be the best choices. 展开更多
关键词 Alunite Mineral processing methods Multi Attribute decision Making Delphi Analytical Hierarchy Process (DAHP)Fuzzy TOPSIS
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Developing a mathematical assessment model for blasting patterns management: Sungun copper mine 被引量:9
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作者 M.Yari M.Monjezi +1 位作者 R.Bagherpour S.Jamali 《Journal of Central South University》 SCIE EI CAS 2014年第11期4344-4351,共8页
Blasting is one of the most important operations in the mining projects that has effective role in the whole operation physically and economically. Unsuitable blasting pattern may lead to unwanted events such as poor ... Blasting is one of the most important operations in the mining projects that has effective role in the whole operation physically and economically. Unsuitable blasting pattern may lead to unwanted events such as poor fragmentation, back break and fly rock. Multi attribute decision making(MADM) can be useful method for selecting the most appropriate blasting pattern among previously performed patterns. In this work, initially, from various already performed patterns, efficient and inefficient patterns are determined using data envelopment analysis(DEA). In the second step, after weighting impressive attributes using experts' opinion, elimination Et choice translating reality(ELECTRE) was used for ranking the efficient patterns and recognizing the most appropriate pattern in the Sungun Copper Mine, Iran. According to the obtained results, blasting pattern with the hole diameter of 15.24 cm, burden of 3 m, spacing of 4 m and stemming of 3.2 m has selected as the best pattern and has selected for future operation. 展开更多
关键词 expert system analytic hierarchy process(AHP) multi-attribute decision making(MADM) elimination Et choice translating reality(ELECTRE) data envelopment analysis(DEA) blasting pattern
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THE NEXT INDUSTRIAL REVOLUTION:INTEGRATED SERVICES AND GOODS 被引量:16
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作者 James M.TIEN 《Journal of Systems Science and Systems Engineering》 SCIE EI CSCD 2012年第3期257-296,共40页
The outputs or products of an economy can be divided into services products ana gooas products (due to manufacturing, construction, agriculture and mining). To date, the services and goods products have, for the mos... The outputs or products of an economy can be divided into services products ana gooas products (due to manufacturing, construction, agriculture and mining). To date, the services and goods products have, for the most part, been separately mass produced. However, in contrast to the first and second industrial revolutions which respectively focused on the development and the mass production of goods, the next - or third - industrial revolution is focused on the integration of services and/or goods; it is beginning in this second decade of the 21st Century. The Third Industrial Revolution (TIR) is based on the confluence of three major technological enablers (i.e., big data analytics, adaptive services and digital manufacturing); they underpin the integration or mass customization of services and/or goods. As detailed in an earlier paper, we regard mass customization as the simultaneous and real-time management of supply and demand chains, based on a taxonomy that can be defined in terms of its underpinning component and management foci. The benefits of real-time mass customization cannot be over-stated as goods and services become indistinguishable and are co-produced - as "servgoods" - in real-time, resulting in an overwhelming economic advantage to the industrialized countries where the consuming customers are at the same time the co-producing producers. 展开更多
关键词 Big data decision analytics GOODS adaptive services digital manufacturing value chain supply chain demand chain mass production mass customization industrial revolution
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INTERNET OF CONNECTED SERVGOODS:CONSIDERATIONS,CONSEQUENCES AND CONCERNS 被引量:5
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作者 James M.Tien 《Journal of Systems Science and Systems Engineering》 SCIE EI CSCD 2015年第2期130-167,共38页
In an earlier paper (Tien 2012), the author augurs that, in contrast to the first and second industrial revolutions which respectively focused on the development and the mass production of goods, the next - or third... In an earlier paper (Tien 2012), the author augurs that, in contrast to the first and second industrial revolutions which respectively focused on the development and the mass production of goods, the next - or third - industrial revolution is focused on the integration of services and/or goods; it began in this second decade of the 21st Century. The Third Industrial Revolution (TIR) is underpinned by the integration or mass customization of services and/or goods. The benefits of real-time mass customization cannot be over-stated as goods and services become indistinguishable and are co-produced as "ServGoods", resulting in an overwhelming economic advantage to the industrialized countries where the consuming customers are at the same time the co-producing producers. Adding sensors to these ServGoods and letting them connect or communicate among themselves or with other ServGoods can result in an Intemet of Things (i.e., connected ServGoods). A number of considerations, consequences and concerns relating to such an Intemet of Connected ServGoods are discussed herein. 展开更多
关键词 GOODS services ServGoods sensors Big Data decision analytics adaptive services digital manufacturing value chain supply chain demand chain mass production mass customization industrial revolution Intemet of Things
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A literature review of perishable medical resource management
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作者 Chao Zhang Peifeng Li +1 位作者 Qiao-chu He Fan Wang 《Frontiers of Engineering Management》 CSCD 2023年第4期710-726,共17页
In recent decades,healthcare providers have faced mounting pressure to effectively manage highly perishable and limited medical resources.This article offers a comprehensive review of supply chain management pertainin... In recent decades,healthcare providers have faced mounting pressure to effectively manage highly perishable and limited medical resources.This article offers a comprehensive review of supply chain management pertaining to such resources,which include transplantable organs and healthcare products.The review encompasses 93 publications from 1990 to 2022,illustrating a discernible upward trajectory in annual publications.The surveyed literature is categorized into three levels:Strategic,tactical,and operational.Key problem attributes and methodologies are analyzed through the assessment of pertinent publications for each problem level.Furthermore,research on service innovation,decision analytics,and supply chain resilience elucidates potential areas for future research. 展开更多
关键词 perishable medical resources organ transplant healthcare products decision analytics operations management
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