Journal articles: 'Industrial efficiency'

1

de Ramos, Kevin Monte. "Industrial Energy Efficiency." Climate and Energy 39, no. 1 (July 5, 2022): 28–32. http://dx.doi.org/10.1002/gas.22303.

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Eichhammer, Wolfgang, and Mannsbart Wilhelm. "Industrial energy efficiency." Energy Policy 25, no. 7-9 (June 1997): 759–72. http://dx.doi.org/10.1016/s0301-4215(97)00066-9.

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Tukhtamisheva, Ainur. "Renovation of Industrial Buildings by Increasing Energy Efficiency." Journal of Advanced Research in Dynamical and Control Systems 12, SP3 (February 28, 2020): 785–91. http://dx.doi.org/10.5373/jardcs/v12sp3/20201318.

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Shcherbakov, V. N. "Industrial Сapacity Efficiency Function." Economics and Management, no. 10 (December 18, 2019): 4–15. http://dx.doi.org/10.35854/1998-1627-2019-10-4-15.

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KENNEDY, CHARLES. "INDUSTRIAL EFFICIENCY AND GROWTH." Bulletin of the Oxford University Institute of Economics & Statistics 17, no. 1 (May 1, 2009): 51–56. http://dx.doi.org/10.1111/j.1468-0084.1955.mp17001008.x.

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Xiong, Siqin, Xiaoming Ma, and Junping Ji. "The impact of industrial structure efficiency on provincial industrial energy efficiency in China." Journal of Cleaner Production 215 (April 2019): 952–62. http://dx.doi.org/10.1016/j.jclepro.2019.01.095.

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Dolge, Kristiāna, Anna Kubule, Stelios Rozakis, Inga Gulbe, Dagnija Blumberga, and Oskars Krievs. "Towards Industrial Energy Efficiency Index." Environmental and Climate Technologies 24, no. 1 (January 1, 2020): 419–30. http://dx.doi.org/10.2478/rtuect-2020-0025.

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AbstractThe study analyses factors that determine industrial energy efficiency. Composite index methodology was applied to evaluate energy utilization efficiency levels across different industrial sub-sectors. In total 12 indicators were incorporated in 3 main dimensions – economic, technical, and environmental. The first results for dimension sub-indices of the 18 main manufacturing sub-sectors in Latvia were presented and discussed. The findings of the study indicated that sector-specific disparities exist that significantly impact the energy efficiency performance of each industrial sub-sector.

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Broadberry, Stephen N., and Richard E. Caves. "Industrial Efficiency in Six Nations." Business History Review 67, no. 3 (1993): 507. http://dx.doi.org/10.2307/3117390.

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Saniuk, Anna, Sebastian Saniuk, Małgorzata Jasiulewicz-Kaczmarek, and Paweł Kużdowicz. "Efficiency Control in Industrial Enterprises." Applied Mechanics and Materials 708 (December 2014): 294–99. http://dx.doi.org/10.4028/www.scientific.net/amm.708.294.

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The global crisis has resulted in a strong need to change the enterprise philosophy. It is observed the importance of a well-thought strategy as a key prerequisite for contemporary enterprise business success. It should include a very good idea which helps to gain a competitive advantage in the market in the future, and also it has to be implemented very quickly. Therefore, efficiency control plays a significant role in industry enterprises. In this paper the new method of efficiency control dedicated for industrial enterprises which have make-to-order manufacturing (MTO) is presented. MTO companies produce bespoke and customized products to particular customer specifications but not repeated on a regular basis. The main goal of this paper is to connect the strategy implementation process with the production order acceptance process, which can increase the efficiency of strategy realization in make-to-order manufacturing.

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Geroski, Paul, and R. E. Caves. "Industrial Efficiency in Six Nations." Economica 61, no. 243 (August 1994): 403. http://dx.doi.org/10.2307/2554627.

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Pratten, Cliff, and Richard E. Caves. "Industrial Efficiency in Six Nations." Economic Journal 103, no. 421 (November 1993): 1554. http://dx.doi.org/10.2307/2234486.

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Walker, Mark D. "Industrial Groups and Investment Efficiency*." Journal of Business 78, no. 5 (September 2005): 1973–2002. http://dx.doi.org/10.1086/431449.

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Bronshteyn, Lev A., and Jesa H. Kreiner. "Energy Efficiency of Industrial Oils." Tribology Transactions 42, no. 4 (January 1999): 771–76. http://dx.doi.org/10.1080/10402009908982281.

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Lunt, Peter, Peter Ball, and Andrew Levers. "Barriers to industrial energy efficiency." International Journal of Energy Sector Management 8, no. 3 (August 26, 2014): 380–94. http://dx.doi.org/10.1108/ijesm-05-2013-0008.

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Purpose – The purpose of this research is to capture organisational barriers that can inhibit energy reduction in manufacturing. Energy consumption is a significant contributor to the economic and environmental components of industrial sustainability, and there is a significant body of knowledge emerging on the technical steps necessary to reduce that consumption. Achieving technical success requires organisational alignment, without which barriers to energy efficiency can be experienced. Design/methodology/approach – The research uses a theory building–theory testing cycle to propose and then verify existence of barriers to industrial energy efficiency. Literature review is used to build potential organisational barriers that can arise. The existence of barriers is then verified in industrial energy reduction projects using interview, observation and document analysis. Findings are validated by company staff. Findings – From the literature barriers that can be related to energy reduction, projects are uncovered. The generic and energy reduction-specific barriers are confirmed and two new barriers are identified. A cognitive map linking the relationships between all the barriers is proposed. Research limitations/implications – The research is built on detailed examination of a number of projects in a single company and work is needed to verify the findings in companies of different size and different industrial sector. Practical implications – The list of barriers created can support industry in preparing for and undertaking energy efficiency projects. The cognitive map proposed will help industry and academia understand why removing current prominent barriers can lead to surfacing of new barriers. Originality/value – The novelty of this research is in both the creation of a list of organisational barriers for energy efficiency as well as identifying the relationships between them. The work brings generic change management barriers to enhance the specific energy reduction barriers together into a broader collation of barriers as well as uncovering new barriers. The work proposes a cognitive map of industrial energy efficiency barriers to demonstrate their interrelationships.

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Hu, Jin-Li, Fang-Yu Yeh, and I.-Ting Chang. "Industrial park efficiency in Taiwan." Journal of Information and Optimization Sciences 30, no. 1 (January 2009): 63–86. http://dx.doi.org/10.1080/02522667.2009.10699866.

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Beyene, Asfaw. "Energy Efficiency and Industrial Classification." Energy Engineering 102, no. 2 (March 2005): 59–80. http://dx.doi.org/10.1080/01998590509509426.

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Tonn, Bruce, and Michaela Martin. "Industrial energy efficiency decision making." Energy Policy 28, no. 12 (October 2000): 831–43. http://dx.doi.org/10.1016/s0301-4215(00)00068-9.

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Wang, Yi, Yingxue Cao, and Xiaojing Meng. "Energy efficiency of industrial buildings." Indoor and Built Environment 28, no. 3 (January 28, 2019): 293–97. http://dx.doi.org/10.1177/1420326x19826192.

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Deineko, Liudmyla, Mykola Sychevskiy, Olena Tsyplitska, Nadiia Grebeniuk, and Oleksandr Deineko. "Increasing resource efficiency in the industrial complex ensuring environmental human rights." Environmental Economics 12, no. 1 (December 28, 2021): 124–39. http://dx.doi.org/10.21511/ee.12(1).2021.11.

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The close relationship between industrial development and environmental pollution is considered the main problem of negative climate changes and the deterioration of life quality leading to an increase in mortality. In this regard, the protection of environmental human rights is of great importance. The paper aims to assess the trends of industrial influence on the human environment and the level of protection of environmental human rights in different countries through reviewing and analysis of the set of relevant studies. The paper brings novelty exploring an array of objectives for protecting human environmental rights in the framework of the Sustainable Development Goals, implementation of a circular and resource-efficient economy, together with the Industry 4.0 technologies for industrialized countries, including Ukraine. Most studies consider contradictions between the economic and environmental goals of both businesses and the state the main obstacle for the ecologization of industrial production. The economic feasibility of introducing more resource-efficient business models has been proved. The impact of Ukrainian industrial companies on the environment and the state of human environmental rights protection is studied. The results of the study allow stating that the resource and energy inefficiency of industrial technology in the country, as well as the weakness of state institutions in the implementation of reforms for sustainable development, is a fundamental threat to human rights and a healthy life.

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Klepikova, Svitlana. "Neural networks application in managing the energy efficiency of industrial enterprise." Neuro-Fuzzy Modeling Techniques in Economics 7, no. 1 (July 18, 2019): 62–73. http://dx.doi.org/10.21511/nfmte.7.2018.04.

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The article is devoted to the creation of a method for using of neural networks approach in solving problems of energy efficiency management at the industrial enterprise. The method allows to obtain an approximate expected value of the energy intensity of production, depending on the values of the main factors affecting it. The multilayer perceptron was chosen as the type of neural network, synthesis of which was carried out by using the genetic algorithm. When sampling for the synthesis of a neural network, we used the results that were obtained by means of a priori ranking, correlation and regression analysis based on the statistical data of industrial enterprises in machine-building profile. The recommendations of the use of the method and the application of its results in the practical implementation at the industrial enterprise are given. Calculations based on the aforementioned method ensured a high precision of prediction of energy intensity values for industrial enterprises that were included in the sample during the synthesis of the neural network, and an acceptable error while testing on industrial enterprises from a test sample.

21

Kiel, Edwin. "Energy efficiency in industrial drive technology." ATZproduktion worldwide 1, no. 4 (October 2008): 4–7. http://dx.doi.org/10.1007/bf03224165.

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22

Li, Peng, and Li-Li Shi. "Do Environmental Regulations Improve Industrial Efficiency?" Advances in Civil Engineering 2021 (November 13, 2021): 1–11. http://dx.doi.org/10.1155/2021/1979353.

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This study was based on research on the impact of environmental regulation on industrial efficiency in 30 provinces from 2005 to 2017 in China. For the explained variables, the industrial efficiency of the DEA-Malmquist method was utilized for the decomposition and measurement of overall factor productivity, and government environmental governance variables were added as instrumental variables for two-stage least-squares regression. In addition, environmental regulatory intensity and year were utilized as threshold variables for the threshold test. In the benchmark regression, environmental regulation harms regional industrial efficiency. However, according to the IV estimation of government environmental governance variables, environmental regulation has a positive effect on the transformation of regional industrial efficiency. The influence of environmental regulation on industrial efficiency will be first suppressed and then promoted with the gradual increase of regulatory intensity. Furthermore, there is significant spatial heterogeneity in the impact of environmental regulations.

23

Zhou, Bole, and Shouguo Zhao. "Industrial policy and corporate investment efficiency." Journal of Asian Economics 78 (February 2022): 101406. http://dx.doi.org/10.1016/j.asieco.2021.101406.

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den Boer, Emilia, Ian D. Williams, Tony Curran, and Bernd Kopacek. "Editorial: Industrial networks for resource efficiency." Proceedings of the Institution of Civil Engineers - Waste and Resource Management 167, no. 3 (August 2014): 95–96. http://dx.doi.org/10.1680/warm.2014.167.3.95.

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den Boer, Emilia, Ian Williams, Tony Curran, and Bernd Kopacek. "Editorial: Industrial networks for resource efficiency." Proceedings of the Institution of Civil Engineers - Waste and Resource Management 167, no. 4 (November 2014): 137–38. http://dx.doi.org/10.1680/warm.2014.167.4.137.

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26

Russell, Christopher. "Return on Industrial Steam Efficiency Investment." Strategic Planning for Energy and the Environment 24, no. 2 (October 2004): 43–54. http://dx.doi.org/10.1080/10485230409509660.

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27

Koehorst, Piet, and Willem Verhoeven. "Effectiveness and Efficiency in Industrial Training." Journal of European Industrial Training 10, no. 3 (March 1986): 20–22. http://dx.doi.org/10.1108/eb014234.

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28

O’Rielly, K., and J. Jeswiet. "Strategies to Improve Industrial Energy Efficiency." Procedia CIRP 15 (2014): 325–30. http://dx.doi.org/10.1016/j.procir.2014.06.074.

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Giacone, E., and S. Mancò. "Energy efficiency measurement in industrial processes." Energy 38, no. 1 (February 2012): 331–45. http://dx.doi.org/10.1016/j.energy.2011.11.054.

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30

Bose, Pinaki. "INDUSTRIAL LICENSING, BRIBERY AND ALLOCATION EFFICIENCY." Bulletin of Economic Research 47, no. 1 (January 1995): 85–88. http://dx.doi.org/10.1111/j.1467-8586.1995.tb00603.x.

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Koehorst, Piet, and Willem Verhoeven. "Effectiveness and Efficiency in Industrial Training." Journal of European Industrial Training 10, no. 4 (April 1986): 7–10. http://dx.doi.org/10.1108/eb002197.

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32

Ingason, Helgi Thor, and Thorsteinn I. Sigfusson. "Maximizing industrial infrastructure efficiency in Iceland." JOM 62, no. 8 (August 2010): 43–49. http://dx.doi.org/10.1007/s11837-010-0124-5.

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33

Winkelman, Steven R., James H. Drzemiecki, and Juanita M. Haydel. "Industrial energy efficiency and energy tracking." P2: Pollution Prevention Review 7, no. 1 (1997): 33–46. http://dx.doi.org/10.1002/(sici)1520-6815(199724)7:1<33::aid-ppr3>3.0.co;2-9.

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Xu, Kai. "Industrial Detection Efficiency Based on Automatic Industrial CT Detection System." Journal of Physics: Conference Series 1881, no. 3 (April 1, 2021): 032088. http://dx.doi.org/10.1088/1742-6596/1881/3/032088.

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Segreto, Maria-Anna, Marcello Artioli, Rovena Preka, and Mario Tarantini. "Energy Efficiency in Industrial Areas: Application of Best Practices for Energy Efficiency In Mediterranean Industrial Areas." European Journal of Sustainable Development 2, no. 4 (April 1, 2013): 61. http://dx.doi.org/10.14207/ejsd.2013.v2n4p61.

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The results presented in this paper originate from an EU research project that is near toits completion. The goal was to build a model that can be applied to all industrial sites inthe Mediterranean area. The approach followed to achieve the objectives was to study allthe new technologies and systems that, if applied globally, can make the whole areasustainable both energetically and environmentally. The application of the model allowsthe design and implementation of self-sufficient green areas in terms of energy which alsobrings to the reduction of the emissions into the atmosphere. An aim of the project wasalso to identify possible sources of funding or incentives. The main beneficiaries of theresults are SMEs that through a more responsible approach to the environment could getgreater market competitiveness and reduce energy costs of their enterprises. Otherbeneficiaries are the people who obtain advantages from a clearer and less pollutedsurrounding environment.The paper presents the results obtained from the application of the model in some pilotcases.

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Urain, Idoia, Daniel Justel, Joan Manuel F. Mendoza, and José Alberto Eguren. "Industrial eco-productivity tool: A case study of industrial SMEs." International Journal of Production Management and Engineering 11, no. 1 (January 31, 2023): 43–52. http://dx.doi.org/10.4995/ijpme.2023.18979.

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This paper presents a new, unified method to measure and increase production and environmental performance in industrial SMEs (Small and Medium Enterprises), which have very limited resources, by identifying areas to improve and forming related projects. This structured, easy-to-apply method is based on standard systems to measure waste production efficiency and eco-efficiency and unifies them in a single reference value. In addition, a case study is shown where the industrial eco-efficiency of the company is obtained with the developed tool.

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Park, Jiyong, Taeyoung Jin, Sungin Lee, and Jongroul Woo. "Industrial Electrification and Efficiency: Decomposition Evidence from the Korean Industrial Sector." Energies 14, no. 16 (August 19, 2021): 5120. http://dx.doi.org/10.3390/en14165120.

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For this study, we conducted a decomposition analysis of industrial electricity consumption based on the logarithmic mean Divisia index approach. An empirical dataset consisting of 11 industrial sectors in Korea from 2000 to 2018 was used. The three-factor decomposition equation was extended to include four factors by decomposing the energy intensity effect into electrification and electricity consumption efficiency effects. The empirical results are summarized as follows: The increase in electricity consumption in the Korean industrial sector from 2000 to 2018 is mostly caused by the production effect. While the structure effect decreases electricity consumption, the intensity effect increases it. The key findings indicate that the hidden electrification effect can be confusing to researchers with regard to the intensity effect. The empirical evidence suggests that the intensity effect has a positive effect on electricity consumption induced by the electrification effect, although the efficiency effect continuously decreased electricity consumption. The decomposition results of some sectors show that electrification, rather than the production effect, contributed the most to the increase in electricity consumption. This implies that while replacing fuel with electricity has been successfully achieved in several sectors, there are still challenges regarding increasing energy efficiency and expanding clean electricity generation.

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Rietbergen, Martijn G., and Kornelis Blok. "Setting SMART targets for industrial energy use and industrial energy efficiency." Energy Policy 38, no. 8 (August 2010): 4339–54. http://dx.doi.org/10.1016/j.enpol.2010.03.062.

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Guerrero-García-Rojas, Hilda R., Diego García-Vega, and Luis Seguí-Amórtegui. "Productividad industrial del agua en México: análisis de eficiencia para ocho sectores." Tecnología y ciencias del agua 12, no. 1 (January 1, 2021): 313–57. http://dx.doi.org/10.24850/j-tyca-2021-01-08.

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Se presenta un análisis de eficiencia sobre el uso y aprovechamiento de los recursos hídricos por parte de los principales sectores industriales, que mayor volumen consumen en México en sus procesos de producción. Dicho análisis fue elaborado a nivel nacional para cada uno de los ocho sectores industriales seleccionados. Previo al análisis de eficiencia hídrica, se contextualizan y se describen algunas características y particularidades sobre los recursos hídricos, así como los principales rasgos de la industria. El procedimiento metodológico de la investigación fue de tipo descriptivo y deductivo, basado en fuentes oficiales de México. Entre algunas de las conclusiones se pueden mencionar: i) el acceso limitado y disperso a las fuentes oficiales de información en materia de uso y aprovechamiento del agua en la industria, ii) las estimaciones de eficiencia hídrica muestran cierta heterogeneidad y mayor dominio de los volúmenes de agua por parte de algunos sectores industriales, sobre otros de menor relevancia, iii) la eficiencia hídrica estuvo basada en la relación costo-producción, iv) el aprovechamiento hídrico industrial es geográficamente heterogéneo y disperso, ya que la mayoría de las industrias se localizan en las zonas del centro y norte del país, donde paradójicamente existen menores niveles de disponibilidad hídrica, contrario a las zonas del sur y sureste del territorio mexicano, donde la disponibilidad hídrica es abundante y, paradójicamente, existe menor dinamismo económico y, v) los resultados de eficiencia hídrica son estimaciones aproximadas, debido a la complejidad de los datos y los filtros que se tuvieron que realizar durante la investigación.

40

Truba, A. S., E. E. Mozhaev, and A. K. Markov. "IMPROVING ENERGY EFFICIENCY IN AGRO-INDUSTRIAL COMPLEX." Экономика сельского хозяйства России, no. 8 (August 2020): 45–49. http://dx.doi.org/10.32651/208-45.

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41

Metyakubov, A., and D. Matrizayeva. "Economic Analysis of Industrial Investment Management Efficiency." Bulletin of Science and Practice 6, no. 7 (July 15, 2020): 251–56. http://dx.doi.org/10.33619/2414-2948/56/27.

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The paper analyses the issues related to main areas of efficacy of managing investment projects at enterprises of the construction materials industry in the conditions of diversification and increasing its investment attraction. The research team proposed recommendations on improving diversification of the structure of construction materials industry, wide attracting of foreign investments for modernization, technological and technical reequipping of enterprises of the branch and its export potential.

42

Stepanko, N. G. "Ecological efficiency of the industrial-natural relations." Science Almanac, no. 1 (2014): 234–38. http://dx.doi.org/10.17117/na.2014.01.234.

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43

Golov, R. S., V. G. Smirnov, V. Yu Teplyshev, D. A. Prokof’ev, A. G. Palamarchuk, K. V. Anisimov, and A. M. Andrianov. "Energy Efficiency Requirements at Russian Industrial Enterprises." Russian Engineering Research 42, no. 4 (April 2022): 398–400. http://dx.doi.org/10.3103/s1068798x22040104.

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Alimkhanova, Aliya Nurzhanovna, and Artur Alexandrovich Mizel. "Evaluation of the efficiency of industrial enterprises." Professor’s Journal. Series: Technical science 1 (February 25, 2021): 20–30. http://dx.doi.org/10.18572/2686-8598-2021-4-1-20-30.

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Objective: To evaluate the efficiency of Russian industrial enterprises based on the stochastic method using financial indicators for 2017-2018. Method: the parametric SFA (Stochastic Frontier Analysis) method based on a stochastic model of the production function is used to assess the efficiency of enterprises. In order to achieve more accurate results, a modification of this method was performed. And also with the help of the developed modified SFA method, the bankruptcy of industrial enterprises of the Russian Federation was predicted on the basis of selected significant financial indicators. 35 bankrupt enterprises and 35 operating enterprises of the same industry were analyzed. Results: As a result of the work done using open sources, you can see how the efficiency of different enterprises in the same industry changes over several years. Conclusion: This study suggests the ability to use the Stochastic Frontier Analysis method and its modification on the studied data in the process of monitoring the dynamics of the efficiency of enterprises both bankrupt and operating. Such an assessment of efficiency can be recommended to other sectors of the economy.

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Zhang, Ren-Long, and Xiao-Hong Liu. "Evaluating ecological efficiency of Chinese industrial enterprise." Renewable Energy 178 (November 2021): 679–91. http://dx.doi.org/10.1016/j.renene.2021.06.119.

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46

Atteberry, William, and Ronald Rutherford. "Industrial Real Estate Prices and Market Efficiency." Journal of Real Estate Research 8, no. 3 (January 1, 1993): 377–85. http://dx.doi.org/10.1080/10835547.1993.12090715.

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47

Galvao, J., A. Nabais, M. Galvao, J. Candeias, T. Pereira, and J. Ramos. "Efficiency in an Intensive Energy Industrial Consumer." Renewable Energy and Power Quality Journal 18 (June 2020): 599–602. http://dx.doi.org/10.24084/repqj18.443.

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48

Pimenta, J., L. C. De Lima, J. B. F. Duarte, and R. M. Macedo. "INDUSTRIAL BURNERS TESTING AND COMBUSTION EFFICIENCY ANALYSIS." Revista de Engenharia Térmica 1, no. 2 (December 31, 2002): 03. http://dx.doi.org/10.5380/reterm.v1i2.3503.

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This paper describes experimental procedures and techniques adopted for combustion analysis during the testing of burners for industrial applications. The tests were carried out in the Combustion Technology Laboratory (NTC) of the University of Fortaleza. The NTC facilities are composed basically of experimental testing hall, a monitoring room, a chromatography laboratory and a modeling and simulation studies room. In the lab testing hall, is installed a test bench composed basically of the following parts : a combustion chamber with nominal thermal capacity of 1.000.000 kcal/h, two fully instrumented gas and air supply sections, a gas analyzer for emissions measurement, a panel for monitoring of water supply to combustion chamber coil, a cooling tower for heat delivery of combustion chamber. A data acquisition and control system is available with all the hardware tools for monitoring of the combustion process. With all the acquired measurements of temperature, flow rate, pressures, emissions, etc., the First Law energy balance approach was used in order to evaluate the combustion efficiency of two different burners with 378.000 and 403.200 kcal/h nominal heat power. Analysis of preliminary results allows representing the burners efficiency according to different air and fuel operating conditions. The experimental data obtained are also compared with simulation results from the modeling of the combustion process, presented in another article linked with this work, where a discussion of such comparison is made. Future studies will be dedicated to the development of improved efficiency combustion systems for industrial and commercial applications.

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Wu, Jie, Chu Wang, and Zhixiang Zhou. "Industrial pollutant treatment efficiency considering environmental factors." Journal of Modelling in Management 14, no. 3 (August 2, 2019): 773–91. http://dx.doi.org/10.1108/jm2-01-2019-0005.

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Purpose The purpose of this paper is to improve the accuracy of evaluation efficiency by constructing parallel structures considering the main components of industrial pollutants, and then to consider some external influence factors to eliminate random errors. Design/methodology/approach In this paper, data transformation has been used to deal with undesirable output, and a model with a parallel structure based on the three-stage data envelopment analysis model to calculate the efficiency scores of different division in pollution treatment has been composed. Findings The analysis shows that the external environmental factors and random factors of the economy and society greatly affect the efficiency of industrial pollutant treatment; moreover, there is an imbalance between regions in China in the treatment of industrial pollutants. Originality/value Optimal improvement requires each province to take targeted measures to improve its efficiency of pollutant treatment measures, which are tailored to specific situations and determined by efficiency analysis in this paper.

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Sahudin, Zahariah, Hasni Abdullah, and Faridah Pardi. "Technical Efficiency of Shariah-Compliant Industrial Firms." Advanced Science Letters 23, no. 8 (August 1, 2017): 7754–57. http://dx.doi.org/10.1166/asl.2017.9569.

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Journal articles on the topic 'Industrial efficiency'

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