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Journal articles on the topic 'Production Process'

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1

Rebenko, V. I. "Technological basis for process control of production of poultry production." Naukovij žurnal «Tehnìka ta energetika» 11, no. 1 (January 30, 2020): 61–66. http://dx.doi.org/10.31548/machenergy2020.01.061.

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2

Sahan, Melek. "Three dimensional perception and production process." New Trends and Issues Proceedings on Humanities and Social Sciences 2, no. 1 (February 19, 2016): 61–67. http://dx.doi.org/10.18844/gjhss.v2i1.278.

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3

PS, Sellero. "Quality Management, Production Process, Innovation and Productivity." Open Access Journal of Waste Management & Xenobiotics 2, no. 3 (2019): 1–3. http://dx.doi.org/10.23880/oajwx-16000124.

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This paper aims to analyse quality management systems, production process, innovation and productivity of manufacturing firms. In order to obtain that, we have taken into account aspects such as product standardization, the use of quality management systems, the complexity of the production system and some con siderations on technological innovation.
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4

Dümmler, Jörg, Sven Gehre, and Gudula Rünger. "Modeling and Verification of Production Process Chains." International Journal of Computer Theory and Engineering 6, no. 4 (2014): 346–52. http://dx.doi.org/10.7763/ijcte.2014.v6.887.

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5

Prentice, I. Colin. "Process and production." Nature 363, no. 6426 (May 1993): 209–10. http://dx.doi.org/10.1038/363209a0.

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6

OKUDA, Mitsuo, Tatsuya UEMATSU, and Akira BABA. "Studies of Potato Starch Production Process. (1). Production Process Equations." NIPPON SHOKUHIN KAGAKU KOGAKU KAISHI 45, no. 6 (1998): 375–80. http://dx.doi.org/10.3136/nskkk.45.375.

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7

SUCIU, Cristina, and Marioara TULPAN. "Production Process and Indicators of Production Systems." Annals of “Dunarea de Jos” University of Galati. Fascicle IX, Metallurgy and Materials Science 42, no. 1 (March 15, 2019): 48–51. http://dx.doi.org/10.35219/mms.2019.1.08.

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8

Pukharenko, Yu V., V. A. Norin, and M. K. Krylova. "Production of concrete products: production process modeling." Вестник гражданских инженеров 15, no. 1 (2018): 97–104. http://dx.doi.org/10.23968/1999-5571-2018-15-1-97-104.

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9

Johtela, Tommi, Jouni Smed, Mika Johnsson, Risto Lehtinen, and Olli Nevalainen. "Supporting production planning by production process simulation." Computer Integrated Manufacturing Systems 10, no. 3 (July 1997): 193–203. http://dx.doi.org/10.1016/s0951-5240(97)00008-6.

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10

Bołoz, Łukasz, Antoni Kalukiewicz, Greg Galecki, Liubomyr Romanyshyn, Taras Romanyshyn, and Rafael Barrionuevo Giménez. "Conical Pick Production Process." New Trends in Production Engineering 3, no. 1 (August 1, 2020): 231–40. http://dx.doi.org/10.2478/ntpe-2020-0019.

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AbstractOne of the basic methods of mechanical rock mining is cutting, which faces increasingly difficult working conditions. Despite the rapid development of machines used in underground and opencast mining as well as in tunnel building, construction industry and road engineering, the problem of insufficient durability of mining tools remains unsolved. In addition to drilling and, to a lesser extent, planing, cutting provides a huge market for tools. Currently, the process of cutting is mainly based on conical picks. The cutterheads of cutting machines are equipped with several dozen, and frequently – more than one hundred conical picks, which, due to their workability and abrasiveness, sometimes work only a few hours. There is a market demand for over two hundred models of conical picks. This is due to the huge variety of shapes and sizes of picks as well as the methods of their mounting in the holder. The article briefly presents various solutions of conical picks, their construction, methods of protection, dimensions and materials used. Next, based on materials produced by ZWM Carbonex, the classic method of their manufacture using the turning technology has been described. The authors have also presented briefly the use of die forging for the large-scale production of picks, applied by Górnicza Fabryka Narzędzi Sp. z o.o.
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11

Zhong, Xiuhua, Xudong Zhao, Yongkang Qian, and Yan Zou. "Polyethylene plastic production process." Insight - Material Science 1, no. 1 (August 9, 2018): 1. http://dx.doi.org/10.18282/ims.v1i1.104.

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<p>Polyethylene has become the most important polyolefin plastic with excellent mechanical properties, processing properties and chemical stability. It is used in the production of film, packaging and pipe. However, the non-polar property and low rigidity limit its application in certain fields. The new progress of chemical and physical modification upon polyethylene are reviewed. The former includes graft modification, chlorination, copolymerization modification, crosslinking modification, chlorosulfonation modification and plasma modification. There are different methods of polyethylene production which include high-, medium- and low-pressure polyethylene. All three methods had their own benefits and shortcomings which coexist in the industry. <br /><br /></p>
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12

Hendon, Julia A. "Production as Social Process." Archeological Papers of the American Anthropological Association 17, no. 1 (June 28, 2008): 163–68. http://dx.doi.org/10.1525/ap3a.2007.17.1.163.

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13

Bertomen, Michele. "Figure/Fabric: Process/Production." Journal of Architectural Education 54, no. 4 (May 2001): 272–78. http://dx.doi.org/10.1162/10464880152474628.

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14

Kiso, Fumihiko, and Norio Arashi. "Hybrid Methanol-Production Process." Applied Energy 59, no. 2-3 (February 1998): 215–28. http://dx.doi.org/10.1016/s0306-2619(98)00010-5.

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15

Gottmann, J., M. Pfeffer, and W. Sihn. "Process Oriented Production Evaluation." Procedia CIRP 12 (2013): 336–41. http://dx.doi.org/10.1016/j.procir.2013.09.058.

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16

Oropeza-De la Rosa, E., L. G. López-Ávila, G. Luna-Solano, and D. Cantú-Lozano. "Bioethanol production process rheology." Industrial Crops and Products 106 (November 2017): 59–64. http://dx.doi.org/10.1016/j.indcrop.2016.11.051.

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17

Meloy, Roger. "Parenting the production process." Manufacturing Engineer 68, no. 9 (1989): 26. http://dx.doi.org/10.1049/me:19890149.

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18

Pitkanen, Markus, and Fredrik Lundström. "Streamlining the Production Process." Genetic Engineering & Biotechnology News 38, no. 4 (February 15, 2018): 20–21. http://dx.doi.org/10.1089/gen.38.04.09.

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19

White, Wm Claude. "Butadiene production process overview." Chemico-Biological Interactions 166, no. 1-3 (March 2007): 10–14. http://dx.doi.org/10.1016/j.cbi.2007.01.009.

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20

SAKANO, Susumu. "Optimum facilities layout of production process. Development of production process arrangement technique." Transactions of the Japan Society of Mechanical Engineers Series C 54, no. 502 (1988): 1377–81. http://dx.doi.org/10.1299/kikaic.54.1377.

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21

Dinesh, Gujuluva, Ramu Murugan, Kulanthaisamy Mohanrasu, Nagarajan Arumugam, Muthuramalingam Basu, and Alagarsamy Arun. "Anaerobic Process for Biohydrogen Production using Keratin Degraded Effluent." Journal of Pure and Applied Microbiology 13, no. 2 (June 30, 2019): 1135–43. http://dx.doi.org/10.22207/jpam.13.2.52.

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22

Mushtruk, M. M. "Investigation of process of biodiesel production from technical fats." Naukovij žurnal «Tehnìka ta energetika» 10, no. 1 (February 7, 2019): 159–64. http://dx.doi.org/10.31548/machenergy2019.01.159.

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23

Arachchige, Udara S. P. R., Dinesh Kawan, and Morten C. Melaaen. "Simulation of Carbon Dioxide Capture for Aluminium Production Process." International Journal of Modeling and Optimization 4, no. 1 (2014): 43–50. http://dx.doi.org/10.7763/ijmo.2014.v4.345.

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24

Sun, Weihong, Jingwen Ma, and Man Liang. "Research on Quality Control of Medical Device Production Process." International Journal of Materials, Mechanics and Manufacturing 7, no. 3 (June 2019): 133–37. http://dx.doi.org/10.18178/ijmmm.2019.7.3.446.

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25

Kotus, M., E. Jankajová, and M. Petrík. "Quality control of aluminium melt in production process." Research in Agricultural Engineering 61, Special Issue (June 2, 2016): S43—S47. http://dx.doi.org/10.17221/28/2015-rae.

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The quality of aluminium alloy in the production process on the chemical composition basis was evaluated. The quality of casting alloy depends on the chemical composition of melt and on the technological process of production process. The basic elements such as Si, Cu, Fe, Mg and Al in melting were evaluated. The obtained data were compared with the guide data referred to in the standard for aluminium alloy.
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26

Widayat, Widayat, and S. Suherman. "Biodiesel Production from Rubber Seed Oil via Esterification Process." International Journal of Renewable Energy Development 1, no. 2 (July 1, 2012): 57–60. http://dx.doi.org/10.14710/ijred.1.2.57-60.

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One promise source of alternative energy is biodiesel from rubber seed oil, because the raw materials available in plentiful quantities and can be renewed. In addition, the rubber seed is still lack of utilization, and Indonesia is one of the largest rubbers producing country in the world. The objective of this research is to studied on biodiesel production by esterification process. Parameters used in this study are the ratio of catalyst and temperature and its influence on the characteristics of the resulting biodiesel product. Characterization of rubber seed include acid content number analysis, saponification numbers, density, viscosity, iodine number, type of free fatty acids and triglyceride oils. The results of analysis showed that rubber seed oil content obtained is 50.5%. The results of the GCMS analysis showed that a free fatty acid level in rubber seed is very high. Conversion into bio-diesel oil is obtained by at most 59.91% and lowest 48.24%.
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27

R. K, Gundampati, and Debnath M. "Extracellular Ribonuclease from Aspergillus niger: process optimization for production." International Journal of Engineering and Technology 1, no. 4 (2009): 317–20. http://dx.doi.org/10.7763/ijet.2009.v1.63.

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28

Nayak, Dr Satya Ranjan. "Innovation in Production Process and Labour Productivity in Industries." Indian Journal of Applied Research 3, no. 10 (October 1, 2011): 1–2. http://dx.doi.org/10.15373/2249555x/oct2013/24.

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29

Abood, Adnan Naama, and Tahar Salah Habeb. "Production of ZA-27 Alloy by New Rheocasting Process." Journal of Zankoy Sulaimani - Part A 11, no. 1 (March 20, 2008): 89–99. http://dx.doi.org/10.17656/jzs.10184.

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30

SAMCHUK, Ludmila, Yulia POVSTIANA, Nataliia LISHCHYNA, and Artem KLYMENKO. "USING UML DIAGRAMS FOR THE TECHNOLOGICAL PROCESS IN PRODUCTION." Herald of Khmelnytskyi National University. Technical sciences 319, no. 2 (April 27, 2023): 268–75. http://dx.doi.org/10.31891/2307-5732-2023-319-1-268-275.

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The article uses the unified UML modeling language to visualize production elements. To show some of the advantages of the proposed approach, the main components of the production system are defined: technological machines, operators, materials, products and the production process. A class diagram is used to represent the components. Defined attributes and methods of each class: attributes and methods to each class that define its properties and behavior. The Machine class can have attributes such as machine ID and Destination, and methods such as start() and stop(). Relationships between classes are established: association, aggregation, and composition to represent relationships between classes. The Production Process class can have an aggregation relationship with the Machine class, indicating that the production process consists of multiple machines. This work contains UML diagrams and description tables that make it possible to structure the activity of the technological process in production. The technological process of manufacturing products is shown, which is presented in detail on the state diagram.
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31

Weichhart, Georg, Jürgen Mangler, Christoph Mayr-Dorn, Alexander Egyed, and Alexander Hämmerle. "Production Process Interoperability for Cyber-Physical Production Systems." IFAC-PapersOnLine 54, no. 1 (2021): 906–11. http://dx.doi.org/10.1016/j.ifacol.2021.08.188.

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32

Chuan-Kai Wu, Chuan-Kai Wu, Xiang-Yun Yi Chuan-Kai Wu, Zhi-Fei Guo Xiang-Yun Yi, Guang-Yu Chu Zhi-Fei Guo, and Ya-Min Wang Guang-Yu Chu. "Application of Deep Learning in Parameter Optimization of Automatic Production Process in Hot Rolling Production Line." 電腦學刊 35, no. 6 (December 2024): 123–36. https://doi.org/10.53106/199115992024123506010.

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<p>China is a major producer of steel and a pillar industry of the national economy, with huge coal consumption. With the increasingly prominent problem of energy shortage, traditional industrial models are constantly being transformed and upgraded using information technology, and a comprehensive energy information management system is being constructed. This article focuses on the production scheduling optimization problem of steel hot rolling production process. Firstly, based on the hot rolling process flow, the operation and maintenance time consumption of hot rolling equipment and the conversion time between hot rolling equipment are fully considered. The mathematical model of production scheduling for the hot rolling production process is established with the goals of minimizing work order completion time and balancing equipment working hours. Then, the classic NSGA-II algorithm is used as the basis for multi-objective solving. To solve the problems of the algorithm being prone to falling into local optima, insufficient distribution, and long solving time, the algorithm is improved by combining deep reinforcement learning ideas. Finally, through simulation experiments, the superiority of the improved algorithm in the convergence process is verified. At the same time, real hot rolling cases are used as scheduling objects to complete scheduling optimization and provide scheduling solutions.</p> <p>&nbsp;</p>
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33

Kutschenreiter-Praszkiewicz, Izabela. "Production process planning of innovative product." Pomiary Automatyka Robotyka 215, no. 1 (March 5, 2015): 57–64. http://dx.doi.org/10.14313/par_215/57.

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34

Feng, Ming Zhi, Rui Long Zhao, Na Lv, and Shuang Bao Zhang. "Constructional Bamboo Plywood Process Control and Production Process." Applied Mechanics and Materials 184-185 (June 2012): 728–31. http://dx.doi.org/10.4028/www.scientific.net/amm.184-185.728.

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Focusing on the problems of the bamboo plywood existing in the construction field, we have proposed an optimal process for the building bamboo plywood through controlling the preparation process of the bamboo plywood. In our work, moso bamboo was selected as the objective and then a variety of performances of the bamboo plywood were tested with the heat-up-heat-down process. Experiments show that in the same conditions of MC 10%, RC 7%-8%, the best optimum processes of 12mm thick constructional bamboo plywood is 15min pressing time, the pressing temperature between 155°C to 160°C and the sheet density of 0.85 g/cm3. The optimal process to make the performance of bamboo plywood substantially exceeded the European standard the OSB/4 levels. It can provide practical application of engineering and production design with reference value and theoretical basis for the bamboo plywood.
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35

Shyian, Dmytro, and Mykola Bozhko. "Expenditure structure formation in the process of crop production intensification." Economics of Development 17, no. 4 (February 8, 2019): 30–38. http://dx.doi.org/10.21511/ed.17(4).2018.04.

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Methodological and practical aspects of expenditure division into permanent and variable in crop production have been considered in the paper. A graphical method was used to determine the value of constant expenditure in the production of wheat and maize for grain on the example of agricultural enterprises of Kharkiv region. This analysis was carried out as a whole for all costs, as well as for individual articles. It has been found that the value of constant expenditure varies depending on the level of production intensity. Changes in the proportion of constant expenditure in their general value were nonlinear, characterized by a decrease in the relative magnitude of constant expenditure of enterprises with the most intensive level of production. This allows the given group of companies to have a higher level of competitiveness and a lower level of production risk. The author’s approach to determination of constant expenditure proportion has been proposed by calculation of the constant expenditure structure coefficient. This coefficient allows you to determine the proportion of constant expenditure more precisely by taking into account its value by individual articles. On the example of enterprises engaged in the production of wheat and corn for grain we have calculated coefficients of the constant expenditure structure. The obtained results have confirmed nonlinear dependence of changes in the value of constant expenditure, depending on the level of production intensity.
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36

Elaiyaraju, P., and N. Partha. "Studies on biogas production by anaerobic process using agroindustrial wastes." Research in Agricultural Engineering 62, No. 2 (June 30, 2016): 73–82. http://dx.doi.org/10.17221/65/2013-rae.

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This study investigated the effect of factors namely temperature, pH, substrate concentration on sago and tannery effluents by the anaerobic digestion process for biogas production. Response surface methodology with the Central Composite Design (CCD) experiments verified that the biogas production rates were mainly affected by operating temperature, pH, and substrate concentration. The experiments were carried out by two distinct effluents at different organic loading rate under mesophilic range of temperature 31–33°C. Co-digestion was carried out for a period of 21 days. The gas produced was measured by the liquid displacement system. Meanwhile, the highest biogas yields – 80% of CH<sub>4</sub> and 20% of CO<sub>2</sub> –produced in the combined effluent were confirmed by the Gas Chromatography (GC) analysis.
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37

Dębowski, Marcin, Roman Szewczyk, and Alicja Gudanowska. "The Model of Development of Production Process in Biomedical Production Plant." Pomiary Automatyka Robotyka 23, no. 1 (March 30, 2019): 43–46. http://dx.doi.org/10.14313/par_231/43.

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38

Al-Sultan, K. S., and M. A. Al-Fawzan. "Determination of the optimal process means and production production cycles for multistage production systems subject to process deterioration." Production Planning & Control 9, no. 1 (January 1998): 66–73. http://dx.doi.org/10.1080/095372898234532.

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39

Shehab, Shaza, Dhabia M. Al-Mohannadi, and Patrick Linke. "Chemical production process portfolio optimization." Chemical Engineering Research and Design 167 (March 2021): 207–17. http://dx.doi.org/10.1016/j.cherd.2021.01.013.

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40

Gushchina, N. V., and V. V. Kulikov. "Digitalization of the production process." Trends in the development of science and education 60, no. 2 (April 30, 2020): 48–51. http://dx.doi.org/10.18411/lj-04-2020-27.

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41

Kliopova, Irina, and Jurgis Staniskis. "PROCESS CONTROL IN CLEANER PRODUCTION." Environmental Engineering and Management Journal 3, no. 3 (2004): 517–26. http://dx.doi.org/10.30638/eemj.2004.049.

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42

TANI, Y. "Microbial Process of Menaquinone Production." Journal of Nutritional Science and Vitaminology 38, Special (1992): 251–54. http://dx.doi.org/10.3177/jnsv.38.special_251.

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43

Fujiki, Daisuke, and Mayu Yamakawa. "Sentence Production Process in Writing." Proceedings of the Annual Convention of the Japanese Psychological Association 81 (September 20, 2017): 2D—056–2D—056. http://dx.doi.org/10.4992/pacjpa.81.0_2d-056.

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44

Pustějovská, Pavlína, and Simona Jursová. "Process Engineering in Iron Production." Chemical and Process Engineering 34, no. 1 (March 1, 2013): 63–76. http://dx.doi.org/10.2478/cpe-2013-0006.

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Abstract Balance, thermodynamic and mainly kinetic approaches using methods of process engineering enable to determine conditions under which iron technology can actually work in limiting technological states, at the lowest reachable fuel consumption (reducing factor) and the highest reachable productivity accordingly. Kinetic simulation can be also used for variant prognostic calculations. The paper deals with thermodynamics and kinetics of iron making process. It presents a kinetic model of iron oxide reduction in a low temperature area. In the experimental part it deals with testing of iron ore feedstock properties. The theoretical and practical limits determined by heat conditions, feedstock reducibility and kinetics of processes are calculated.
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45

Kozień, Ewa. "Quality Improvement in Production Process." Quality Production Improvement - QPI 1, no. 1 (July 1, 2019): 596–601. http://dx.doi.org/10.2478/cqpi-2019-0080.

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Abstract Quality is a certain degree of excellence and is one of the important factor in realization of the production process. Evaluation of the quality excellence in production project management is connected with a process of making changes in particular phases of project realization. The thesis proposed in the article is: the effective quality improvement based on implementation of the quality management method contributes to achieve the planned quality in the production project.
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46

Saadé, Raafat George, and Ali Ahmed. "Process Analysis of Knowledge Production." International Journal of Applied Logistics 2, no. 3 (July 2011): 49–66. http://dx.doi.org/10.4018/jal.2011070104.

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This paper presents an optimized supply chain for ‘knowledge products’. Based on the traditional logistics model for academic knowledge, knowledge creation and delivery are discussed. A new framework of an optimized supply chain for ‘knowledge products’ is developed. A semi-structured interview was undertaken to capture and analyze the knowledge logistics in a traditional publishing setup. Findings include the illustration of a new optimized supply chain for the manufacturing and distribution of ‘knowledge products’. Realised benefits are discussed showing a significant reduction in total supply chain processing. Research in this domain involves the actual knowledge creators (publishing companies). Connecting knowledge delivery systems to the supplier presents challenges including information sharing and openness to accessing their systems. More challenges are discussed with implications, primarily related to commitment, partnership and re-engineering of present systems. Publishing companies still follow the same traditional supply chain for knowledge creation. They have moved towards custom publishing, but their processes remain practically the same. Publishing companies have to change their mindsets and re-engineer their processes.
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47

Singh, Veena, Kusum Solanki, and Munishwar Gupta. "Process Optimization for Biodiesel Production." Recent Patents on Biotechnology 2, no. 2 (June 1, 2008): 130–43. http://dx.doi.org/10.2174/187220808784619748.

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48

Armstrong, Alan, and Mario Morroni. "Production Process and Technical Change." Economic Journal 103, no. 421 (November 1993): 1556. http://dx.doi.org/10.2307/2234487.

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49

Khadzhiev, S. N., I. M. Gerzeliev, O. S. Vedernikov, A. V. Kleymenov, D. O. Kondrashev, N. V. Oknina, S. E. Kuznetsov, Z. A. Saitov, and M. N. Baskhanova. "A new alkylate production process." Catalysis in Industry 9, no. 3 (July 2017): 198–203. http://dx.doi.org/10.1134/s2070050417030059.

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50

Dolinsek, Slavko, and Janez Kopac. "Process planning in mass production." International Journal of Manufacturing Technology and Management 2, no. 1/2/3/4/5/6/7 (2000): 891. http://dx.doi.org/10.1504/ijmtm.2000.001382.

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