Life Cycle Energy Assessment of a Typical Marble Processing Plant

2019 ◽  
Vol 10 (1) ◽  
pp. 31-45
Author(s):  
Bhargav Prajwal ◽  
Harlal S. Mali ◽  
Ravindra Nagar
Keyword(s):  
Co2 Emissions ◽  
Production Efficiency ◽  
Educational Software ◽  
New Technologies ◽  
Substantial Reduction ◽  
Evaluation Methodology ◽  
Processing Plant ◽  
Productivity Cost ◽  
Environmental Indices ◽  
Low Efficiency

This article describes how marble is one of the most important stone resources in terms of durability. It is aesthetically pleasing, and a decorative material used by many architects, as well as plays an important role in the economy of India. Most of the marble processing activities are performed by small and medium scale industries (SMEs) not only in India but worldwide. These industries have low efficiency and productivity due to lack of new technologies, high productivity cost and a lack of proper sustainable waste management systems, thereby increasing the waste generated during the processing stage. There is a significant need within the sector for increasing production efficiency, combined with the need of a substantial reduction in waste generated that can be achieved by endorsing technological innovations. This is in addition to following best available processing practices, incorporating energy saving technologies and modernizing the sectors management and organization structure which will substantially increase efficiency as well as production. This article provides a systematic approach for assessing the current energy and present environment status of a typical SME processing units of Rajasthan area, and proposes measures for meeting cleaner production principles. An evaluation methodology was developed considering the realistic plant operation scenarios. The total energy inputs for processing the products with their appropriate environmental indices like CO2 emissions were calculated. Alternatively, the CO2 emissions were also calculated by Gabi educational software for different industries and the best way of reducing the energy consumption is suggested by following alternate source of energy.

Life Cycle Energy Assessment of a Typical Marble Processing Plant

2021 ◽  
pp. 452-466
Author(s):  
Bhargav Prajwal ◽  
Harlal S. Mali ◽  
Ravindra Nagar
Keyword(s):  
Co2 Emissions ◽  
Production Efficiency ◽  
Educational Software ◽  
New Technologies ◽  
Substantial Reduction ◽  
Evaluation Methodology ◽  
High Productivity ◽  
Energy Assessment ◽  
Low Efficiency ◽  
Alternate Source

This article describes how marble is one of the most important stone resources in terms of durability. It is aesthetically pleasing, and a decorative material used by many architects, as well as plays an important role in the economy of India. Most of the marble processing activities are performed by small and medium scale industries (SMEs) not only in India but worldwide. These industries have low efficiency and productivity due to lack of new technologies, high productivity cost and a lack of proper sustainable waste management systems, thereby increasing the waste generated during the processing stage. There is a significant need within the sector for increasing production efficiency, combined with the need of a substantial reduction in waste generated that can be achieved by endorsing technological innovations. This is in addition to following best available processing practices, incorporating energy saving technologies and modernizing the sectors management and organization structure which will substantially increase efficiency as well as production. This article provides a systematic approach for assessing the current energy and present environment status of a typical SME processing units of Rajasthan area, and proposes measures for meeting cleaner production principles. An evaluation methodology was developed considering the realistic plant operation scenarios. The total energy inputs for processing the products with their appropriate environmental indices like CO2 emissions were calculated. Alternatively, the CO2 emissions were also calculated by Gabi educational software for different industries and the best way of reducing the energy consumption is suggested by following alternate source of energy.

Radiation Minimisation and Outcome Maximisation in Cardiac Computed Tomograpy

2010 ◽  
Vol 6 (1) ◽  
pp. 15
Author(s):  
James P Earls ◽  
Jonathon A Leipsic ◽  
◽  
Keyword(s):  
Radiation Dose ◽  
Dose Reduction ◽  
New Technologies ◽  
Cardiac Computed Tomography ◽  
Substantial Reduction ◽  
Radiation Doses ◽  
Tube Current ◽  
Prospective Triggering ◽  
Effective Radiation ◽  
Selection Of

Recent reports have raised general awareness that cardiac computed tomography (CT) has the potential for relatively high effective radiation doses. While the actual amount of risk this poses to the patient is controversial, the increasing concern has led to a great deal of research on new CT techniques capable of imaging the heart at substantially lower radiation doses than was available only a few years ago. Methods of dose reduction include optimised selection of user-defined parameters, such as tube current and voltage, as well as use of new technologies, such as prospective triggering and iterative reconstruction. These techniques have each been shown to lead to substantial reduction in radiation dose without loss of diagnostic accuracy. This article will review the most frequently used and widely available methods for radiation dose reduction in cardiac CT and give practical advice on their use and limitations.

Taxation, Innovation or Both? Market-Based Measures and the Adoption of New Technologies to Mitigate Airline CO2 Emissions in Brazil

2018 ◽  
Author(s):  
Carolina Resende ◽  
Gustavo Santos ◽  
Mayara Murça ◽  
Thiago Caliari ◽  
Alessandro Vinícius Marques de Oliveira
Keyword(s):  
Co2 Emissions ◽  
New Technologies

Cost management for concrete batch plant using stochastic mathematical models

2006 ◽  
Vol 33 (8) ◽  
pp. 1065-1074 ◽  
Author(s):  
Tarek M Zayed ◽  
Ibrahim A Nosair
Keyword(s):  
Mathematical Models ◽  
Production Efficiency ◽  
Cost Management ◽  
Unit Cost ◽  
Expected Value ◽  
Cost Models ◽  
Productivity Cost ◽  
Batch Plant ◽  
Factor Share ◽  
Construction Operation

Assessing productivity, cost, and delays are essential to manage any construction operation, particularly the concrete batch plant (CBP) operation. This paper focuses on assessing the above-mentioned items for the CBP using stochastic mathematical models. It aims at (i) identifying the potential sources of delay in the CBP operation; (ii) assessing their influence on production, efficiency, time, and cost; and (iii) determining each factor share in inflating the CBP concrete unit expense. Stochastic mathematical models were designed to accomplish the aforementioned objectives. Data were collected from five CBP sites in Indiana, USA, to implement and verify the designed models. Results show that delays due to management conditions have the highest probability of occurrence (0.43), expected value of delay percent (62.54% out of total delays), and relative delay percent. The expected value of efficiency for all plants is 86.53%; however, the average total expense is US$15.56/m3 (all currency are in US$). In addition, the expected value of effective expenses (EE) is $18.03/m3, resulting in extra expenses (XE) of $2.47/m3. This research is relevant to both industry practitioners and researchers. It develops models to determine the effect of delays on concrete unit cost. They are also beneficial to the CBP management.Key words: concrete batch plant, delays, management conditions, cost models, cost management, stochastic mathematical models.

Research on Intelligent Optimization Algorithm for Multi-Objective Disassembly Line Balancing Problem

2020 ◽  
Author(s):  
Yunli Xu ◽  
Bitao Yao ◽  
Duc Truong Pham
Keyword(s):  
Manufacturing Industry ◽  
Production Efficiency ◽  
Line Balancing ◽  
Product Complexity ◽  
Intelligent Optimization ◽  
Combination Scheme ◽  
Objective Space ◽  
Disassembly Line Balancing ◽  
Low Efficiency ◽  
Disassembly Line

Abstract For resource reutilization and environmental protection, remanufacturing gets more and more attention in many countries. Disassembly is a critical part of traditional manufacturing industry, but the traditional disassembly operation is mainly done by workers, which is low-efficiency. Now the use of robots can improve production efficiency a lot, which involves the problem of disassembly line balancing. Due to the constraints such as product complexity and precedence relationship between tasks, when the number of tasks increases, the combination scheme between tasks increases geometrically, and conventional algorithms are difficult to solve the problems, the Disassembly Line Balancing Problem (DLBP) is generally necessary to optimize multiple objectives. In this research, the author selects a variety of intelligent optimization algorithms to resolve the complex disassembly line balancing problem in different dimensional objective space. Four representative algorithms are selected from three angles to be compared through three performance indicators. It is concluded that these algorithms have different search capabilities for different specifications and objective space. Researchers should carefully select the algorithm according to the specific disassembly problem. The appropriate algorithm should be selected according to the scale of the disassembly line problem and the number of optimization objectives in actual production practice.

Educational Software Evaluation

2011 ◽  
pp. 699-711 ◽  
Author(s):  
Michael Shaughnessy
Keyword(s):  
Educational Software ◽  
Evaluation Methodology ◽  
Evaluation Methodologies ◽  
Initial Investigation ◽  
History Of ◽  
The Subject ◽  
Software Methodologies ◽  
The Individual ◽  
Evaluation Techniques ◽  
Complete History

From 1980 to 2000, there were many articles written on the subject of software review and evaluation. Upon initial investigation of educational software methodologies, it appears that there are as many evaluation methodologies as there are authors presenting them. Several articles (methodology analyses) have been written describing these evaluation techniques (Bryson & Cullen, 1984; Eraut, 1989; Holznagel, 1983; Jones et al., 1999; McDougall & Squires, 1995; Reiser & Kegelmann, 1994, 1996; Russell & Blake, 1988). Each of these articles describes various methodologies and presents the most current evaluation methodology available, but fails to provide a complete history of the types of evaluation methodologies. These analyses of evaluation methodologies focus on the individual methodology, but refrain from putting individual methodologies into a greater systematic context.

The Optimization of Precision Milling Parameters for Titanium Based on Genetic Algorithm

2012 ◽  
Vol 472-475 ◽  
pp. 1078-1081
Author(s):  
Wen Sheng Zhang ◽  
Hong Xiang Wang ◽  
Hong Du ◽  
Tao Xu
Keyword(s):  
Genetic Algorithm ◽  
Production Efficiency ◽  
Optimal Solution ◽  
Minimum Cost ◽  
Cutting Parameters ◽  
Function Optimization ◽  
Cnc Machining ◽  
Production Costs ◽  
Milling Parameters ◽  
Low Efficiency

The genetic algorithm converges faster compared with the traditional optimization algorithm, the global optimal solution can be quickly obtained and it is very effective for multi-peak function optimization. A milling process parameter optimization model is established for titanium based on genetic algorithm in this paper, the relevant constraints is considered and the optional titanium milling parameters is achieved based on the targets of maximum production efficiency and minimum cost, utilizing MATLAB optimization software to program, the best combination of cutting parameters is got finally. Experimental results show that the cutting efficiency and production costs are significantly improved with the optimized cutting parameters, so that the defects of low efficiency in CNC machining resulting in relying on experienced cutting parameters is overcome.

scholarly journals An Artificial Neural Network Approach to Forecast the Environmental Impact of Data Centers

Information ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 113 ◽  
Author(s):  
Joao Ferreira ◽  
Gustavo Callou ◽  
Albert Josua ◽  
Dietmar Tutsch ◽  
Paulo Maciel
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Data Center ◽  
Data Centers ◽  
New Technologies ◽  
Operational Costs ◽  
The Us ◽  
Artificial Neural

Due to the high demands of new technologies such as social networks, e-commerce and cloud computing, more energy is being consumed in order to store all the data produced and provide the high availability required. Over the years, this increase in energy consumption has brought about a rise in both the environmental impacts and operational costs. Some companies have adopted the concept of a green data center, which is related to electricity consumption and CO2 emissions, according to the utility power source adopted. In Brazil, almost 70% of electrical power is derived from clean electricity generation, whereas in China 65% of generated electricity comes from coal. In addition, the value per kWh in the US is much lower than in other countries surveyed. In the present work, we conducted an integrated evaluation of costs and CO2 emissions of the electrical infrastructure in data centers, considering the different energy sources adopted by each country. We used a multi-layered artificial neural network, which could forecast consumption over the following months, based on the energy consumption history of the data center. All these features were supported by a tool, the applicability of which was demonstrated through a case study that computed the CO2 emissions and operational costs of a data center using the energy mix adopted in Brazil, China, Germany and the US. China presented the highest CO2 emissions, with 41,445 tons per year in 2014, followed by the US and Germany, with 37,177 and 35,883, respectively. Brazil, with 8459 tons, proved to be the cleanest. Additionally, this study also estimated the operational costs assuming that the same data center consumes energy as if it were in China, Germany and Brazil. China presented the highest kWh/year. Therefore, the best choice according to operational costs, considering the price of energy per kWh, is the US and the worst is China. Considering both operational costs and CO2 emissions, Brazil would be the best option.

scholarly journals At the Epicenter of COVID-19–the Tragic Failure of the Global Supply Chain for Medical Supplies

2020 ◽  
Vol 8 ◽  
Author(s):  
Sonu Bhaskar ◽  
Jeremy Tan ◽  
Marcel L. A. M. Bogers ◽  
Timo Minssen ◽  
Hishamuddin Badaruddin ◽  
...  
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Production Efficiency ◽  
New Technologies ◽  
Health Workers ◽  
Global Supply Chain ◽  
Governance System ◽  
Current Crisis ◽  
The Face ◽  
The Impact

The tragic failure of the global supply chain in the face of the current coronavirus outbreak has caused acute shortages of essential frontline medical devices and personal protective equipment, crushing fear among frontline health workers and causing fundamental concerns about the sustainability of the health system. Much more coordination, integration, and management of global supply chains will be needed to mitigate the impact of the pandemics. This article describes the pressing need to revisit the governance and resilience of the supply chains that amplified the crisis at pandemic scale. We propose a model that profiles critical stockpiles and improves production efficiency through new technologies such as advanced analytics and blockchain. A new governance system that supports intervention by public-health authorities during critical emergencies is central to our recommendation, both in the face of the current crisis and to be better prepared for potential future crises. These reinforcements offer the potential to minimize the compromise of our healthcare workers and health systems due to infection exposure and build capacity toward preparedness and action for a future outbreak.

Sign in / Sign up

Export Citation Format

Share Document