Case Report
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Year 2023, Volume: 9 Issue: 5, 1163 - 1176, 17.10.2023
https://doi.org/10.18186/thermal.1370731

Abstract

References

  • REFERENCES
  • [1] Geary U, Lopez-Villalobos N, Garrick Dj, Shalloo L. An analysis of the implications of a change to the seasonal milk supply profile in the Irish dairy industry utilizing a seasonal processing sector model. J Agric Sci 2012;150:389407. [CrossRef]
  • [2] Munir M, Zhang Y, Yu W, Wilson D, Young B. Virtual milk for modelling and simulation of dairy processes. J Dairy Sci 2016;99:33803395. [CrossRef]
  • [3] Madoumier M, Azzaro-Pantel C, Tanguy G, Gésan-Guiziou G. Modelling the properties of liquid foods for use of process flow sheeting simulators: Application to milk concentration. J Food Eng 2015;164:7089. [CrossRef]
  • [4] Morales-Mendoza LF, Azzaro-Pantel C. Bridging LCA data gaps by use of process simulation for energy generation. Clean Technol Environ Policy 2017;19:15351546. [CrossRef]
  • [5] Djekic I, Miocinovic J, Tomasevic I, Smigic N, Tomic N. Environmental life-cycle assessment of various dairy products. J Clean Prod 2014;68:6472. [CrossRef]
  • [6] Dalgaard R, Schmidt J, Flysjö A. Generic model for calculating carbon footprint of milk using four different life cycle assessment modelling approaches. J Clean Prod 2014;73:146153. [CrossRef]
  • [7] Rajendran N, Han J. Techno-economic analysis and life cycle assessment of poly (butylene succinate) production using food waste. Waste Manag 2023;156:168176. [CrossRef]
  • [8] Ünal F, Akan AE, Demir B, Yaman K. 4E analysis of an underfloor heating system integrated to the geothermal heat pump for greenhouse heating. Turkish J Agric Forest 2022;46:762780. [CrossRef]
  • [9] Ünal F, Temir G, Köten H. Energy, exergy and exergoeconomic analysis of solar-assisted vertical ground source heat pump system for heating season. J Mech Sci Technol 2018;32:3929–3942. [CrossRef]
  • [10] Khanna A, Kaur S. An empirical analysis on adoption of precision agricultural techniques among farmers of Punjab for efficient land administration. Land Use Policy 2023;126:106533. [CrossRef]
  • [11] Suryanarayanan R, Sridhar VG, Natrayan L, Seeniappan K, Merneedi A, Sathish T, et al. Improvement on mechanical properties of submerged friction stir joining of dissimilar tailor welded aluminum blanks. Adv Mater Sci Eng 2021;2021:16. [CrossRef]
  • [12] Gu J, Hu M, Wang X, Ji Y, Li L, Yu J, et al. Data mining analysis reveals key acupoints and meridians for the treatment of chemotherapy-induced peripheral neuropathy. Explore (NY) 2023;19:7177. [CrossRef]
  • [13] Guna D, Vinodh D. Comparison of material removal rate of AA2014 aluminum alloy using HSS M42 and Titanium Nitride coated drill tools. Mater Today Proceed 2023;77:409413. [CrossRef]
  • [14] Kanishka D, Ramesh Kumar G. Compressive strength of novel polymer coated concrete with polypropylene fiber. Mater Today Proceed 2023;77:401404. [CrossRef]
  • [15] Sarkar D. Advanced materials management for Indian construction industry by application of statistical process control tools. Material Today: Proceed 2022;62:69346939. [CrossRef]
  • [16] Sarkar D, Bhattacharjee B. Design and application of multivariate CUSUM for quality monitoring of ready mixed concrete. Int J Quality Eng Technol 2014;4(2):161. [CrossRef]
  • [17] Xue L, Qiu P. A nonparametric CUSUM chart for monitoring multivariate serially correlated processes. Int J Quality Eng Technol 2021;53(4):396409. [CrossRef]
  • [18] Ünal F, Bulut H, Kahraman A. Energy and cost analysis of horizontal type corn drying plant using LPG fuel. Dicle Univ J Eng 2020;11(1):161170. [CrossRef]
  • [19] Ünal F. Energy and exergy analysis of an industrial corn dryer operated by two different fuels. Int J Exergy 2021;34:475491. [CrossRef]
  • [20] Boullosa-Falces D, Gomez-Solaetxe MA, Sanchez-Varela Z, García S, Trueba A. Validation of CUSUM control chart for biofouling detection in heat exchangers. Appl Therm Eng 2019;152:2431. [CrossRef]
  • [21] Nawaz M, Maulud AS, Zabiri H, Taqvi SAA, Idris A. Improved process monitoring using the CUSUM and EWMA-based multiscale PCA fault detection framework. Chinese J Chem Eng2021;29:253265. [CrossRef]
  • [22] Bellotti M, Qian J, Reynaerts D. Self-tuning breakthrough detection for EDM drilling micro holes. J Manufactur Process 2020;57:630640. [CrossRef]
  • [23] Li Z, Paredis CJ, Augenbroe G, Huang G. A rule augmented statistical method for air-conditioning system fault detection and diagnostics. Energy Build 2012;54:154159. [CrossRef]
  • [24] Nathaphan S, Therdyothin A. Effectiveness evaluation of the energy efficiency and conservation measures for stipulation of Thailand energy management system in factory. J Clean Prod 2023;383:135442. [CrossRef]
  • [25] Benedetti M, Bonfà F, Introna V, Santolamazza A, Ubertini S. Real Time energy performance control for industrial compressed air systems: Methodology and applications. Energies 2019;12:3935. [CrossRef]
  • [26] Fichera A, Volpe R, Cutore E. Energy performance measurement, monitoring and control for buildings of public organizations: Standardized practises compliant with the ISO 50001 and ISO 50006. Dev Built Environ 2020;4:100024. [CrossRef]
  • [27] Riaz M, Abbas N, Does RJMM. Improving the performance of CUSUM charts. Qual Reliab Eng Int 2011;27:415424. [CrossRef]
  • [28] Montgomery DC. Introduction to Statistical Quality Control. 7th ed. New York: John Wiley & Sons; 2013.
  • [29] Li Y, Deng X, Liu B, Ma J, Yang F, Ouyang M. Energy management of a parallel hybrid electric vehicle based on Lyapunov algorithm. eTransport 2022;13:100184. [CrossRef]
  • [30] The Union of Chambers and Commodity Exchanges of Turkiye. Industry Directorate, Capacity Criteria 3112 Milk and products capacity calculation. https://tobb.org.tr/Sayfalar/Eng/AmaciveYapisi.php Last Accessed Date 22.09.2023.
  • [31] Prabhakar P, Srivastav P, Murari K. Energy consumption during manufacturing of different dairy products in a commercial dairy plant: A case study. Asia J Dairy Food Res 2015;34:98. [CrossRef]
  • [32] Montgomery DC, Peck EA, Vining GG, Introduction to Linear Regression Analysis. 3rd ed. New York: John Wiley & Sons; 2001.
  • [33] Li J. Nonparametric adaptive CUSUM chart for detecting arbitrary distributional changes. J Quality Technol 2021;53:154172. [CrossRef]
  • [34] Huang W, Shu L, Jiang W. A gradient approach to the optimal design of CUSUM charts under unknown mean-shift sizes. J Qual Technol 2016;48:6883. [CrossRef]
  • [35] Wen X, Cao H, Hon B, Chen E, Li H. Energy value mapping: A novel lean method to integrate energy efficiency into production management. Energy 2021;217:119353. [CrossRef]
  • [36] Siddique ARM, Bozorgi M, Venkateshwar K, Tasnim S, Mahmud S. Phase change material-enhanced solid-state thermoelectric cooling technology for food refrigeration and storage applications. J Energy Storage 2023;60:106569. [CrossRef]
  • [37] Zhang W, Huang J, Zhang T, Tan Q. A risk-based stochastic model for supporting resources allocation of agricultural water-energy-food system under uncertainty. J Hydrol 2022;610:127864. [CrossRef]
  • [38] Tan Q, Zhang T. Robust fractional programming approach for improving agricultural water-use efficiency under uncertainty. J Hydrolog 2018;564:11101119. [CrossRef]
  • [39] Li M, Fu Q, Singh VP, Ji Y, Liu D, Zhang C, Li T. An optimal modelling approach for managing agricultural water-energy-food nexus under uncertainty. Sci Total Environ 2019;651(Pt 1):14161434. [CrossRef]
  • [40] Jing R, He Y, He J, Liu Y, Yang S. Global sensitivity based prioritizing the parametric uncertainties in economic analysis when co-locating photovoltaic with agriculture and aquaculture in China. Renew Energy 2022;194:10481059. [CrossRef]
  • [41] Zheng Z, Ji L, Xie Y, Huang G, Pan J. Synergic management of crop planting structure and biomass utilization pathways under a food-energy-water nexus perspective. J Clean Prod 2022;335:130314. [CrossRef]
  • [42] Beck MB, Chen C, Walker RV, Wen Z, Han J. Multi-sectoral analysis of smarter urban nitrogen metabolism: A case study of Suzhou, China. Ecol Model 2023;478:110286. [CrossRef]
  • [43] Esen H, Inalli M, Esen M. Technoeconomic appraisal of a ground source heat pump system for a heating season in eastern Turkey. Energy Convers Manag 2006;47:12811297. [CrossRef]
  • [44] Holman JP. Experimental methods for engineers. 7th ed. New York: McGraw Hill; 2001.
  • [45] Esen M, Yuksel T. Experimental evaluation of using various renewable energy sources for heating a greenhouse. Energy Build 2013;65:340351.
  • [46] Erbay Z, Koca N. Energetic, Exergetic, and Exergoeconomic Analyses of Spray-Drying Process during White Cheese Powder Production. Dry Technol 2012;30:435444. [CrossRef]
  • [47] Figliola RS, Beasley D. Theory and Design for Mechanical Measurements. 6th ed. New Jersey: John Wiley & Sons Inc; 2015.
  • [48] Bobovnik G, Kutin J. Uncertainty analysis of the air velocity standard based on LDA and wind tunnel. Measure 2023;206:112228. [CrossRef]
  • [49] Cengel YA, Boles MA, Kanoglu M. Thermodynamics: An Engineering Approach. New York: Mcgraw-Hill Education; 2019.
  • [50] Başaran A, Yılmaz T, Azgın Şükrü T, Çivi C. Comparison of drinking milk production with conventional and novel inductive heating in pasteurization in terms of energetic, exergetic, economic and environmental aspects. J Clean Product 2021;317:128280. [CrossRef]
  • [51] Solanki A, Pal Y. A comprehensive review to study and implement solar energy in dairy industries. J Therm Eng 2021;7(5):1216–1238. [CrossRef]
  • [52] Heydari A, Forati M, Khatam SM. Thermal performance investigation of a hybrid solar air heater applied in a solar dryer using thermodynamic modeling. J Therm Eng 2021;7:715–730. [CrossRef]
  • [53] Margolies B, Adams MC, Pranata J, Gondoutomo K, Barbano DM. Effect of uncertainty in composition and weight measures in control of cheese yield and fat loss in large cheese factories. J Dairy Sci 2017;100:68226852. [CrossRef]
  • [54] Lincoln BJ, Kong L, Pineda AM, Walmsley TG. Process integration and electrification for efficient milk evaporation systems. Energy 2022;258:124885. [CrossRef]
  • [55] Bühler F, Nguyen T-V, Jensen JK, Holm FM, Elmegaard B. Energy, exergy and advanced exergy analysis of a milk processing factory. Energy 2018;162:576592. [CrossRef]
  • [56] Bühler F, Zühlsdorf B, Nguyen T-V, Elmegaard B. A comparative assessment of electrification strategies for industrial sites: Case of milk powder production. Appl Energy 2019;250:13831401. [CrossRef]

Energy and production analysis of a dairy milk factory: A case of study

Year 2023, Volume: 9 Issue: 5, 1163 - 1176, 17.10.2023
https://doi.org/10.18186/thermal.1370731

Abstract

This study illustrates a factory’s production efficiency by demonstrating its energy efficiency in the dairy milk industry. Determining the thermal energy to save energy enhances the prof-itability of the factory. The aim of this study is to conduct a thermal energy and production analysis of a dairy milk factory based on annual production. This study intends to make the conclusions more realistic by using production and energy data dependability analysis. The overall power consumption for the thermal and electric energy processes was found to be as 180,520 [W]. The target-specific energy consumption value was computed for Case 1 as 6,352.14 [MJ/t], for Case 2 as 5,898.67 [MJ/t], and for Case 3 as 5,445.21 [MJ/t]. The annual thermal (steam boiler) and electrical energy expenditures were obtained, with 315.87 [kW] of thermal (steam) energy and 80.98 [kW] of electrical energy. The total thermal and electri-cal energy reached 396.85 [kW]. Despite the factory’s expenditure on thermal and electrical energy, the energy efficiency was determined to be as 45.5%. The input energy was obtained to be 374.24 [kW] in Case 1, 356.33 [kW] in Case 2, and 342.08 [kW] in Case 3. The energy efficiency was calculated as 48.2 [%] for Case 1, 50.7 [%] for Case 2, and 52.8 [%] for Case 3. This study, which is expected to inspire future research, is also likely to assist livestock and agriculture in the energy field. The novelty of this study is that optimizing product efficiency and energy consumption in the production of milk and dairy products positively increases the energy efficiency of factories.

References

  • REFERENCES
  • [1] Geary U, Lopez-Villalobos N, Garrick Dj, Shalloo L. An analysis of the implications of a change to the seasonal milk supply profile in the Irish dairy industry utilizing a seasonal processing sector model. J Agric Sci 2012;150:389407. [CrossRef]
  • [2] Munir M, Zhang Y, Yu W, Wilson D, Young B. Virtual milk for modelling and simulation of dairy processes. J Dairy Sci 2016;99:33803395. [CrossRef]
  • [3] Madoumier M, Azzaro-Pantel C, Tanguy G, Gésan-Guiziou G. Modelling the properties of liquid foods for use of process flow sheeting simulators: Application to milk concentration. J Food Eng 2015;164:7089. [CrossRef]
  • [4] Morales-Mendoza LF, Azzaro-Pantel C. Bridging LCA data gaps by use of process simulation for energy generation. Clean Technol Environ Policy 2017;19:15351546. [CrossRef]
  • [5] Djekic I, Miocinovic J, Tomasevic I, Smigic N, Tomic N. Environmental life-cycle assessment of various dairy products. J Clean Prod 2014;68:6472. [CrossRef]
  • [6] Dalgaard R, Schmidt J, Flysjö A. Generic model for calculating carbon footprint of milk using four different life cycle assessment modelling approaches. J Clean Prod 2014;73:146153. [CrossRef]
  • [7] Rajendran N, Han J. Techno-economic analysis and life cycle assessment of poly (butylene succinate) production using food waste. Waste Manag 2023;156:168176. [CrossRef]
  • [8] Ünal F, Akan AE, Demir B, Yaman K. 4E analysis of an underfloor heating system integrated to the geothermal heat pump for greenhouse heating. Turkish J Agric Forest 2022;46:762780. [CrossRef]
  • [9] Ünal F, Temir G, Köten H. Energy, exergy and exergoeconomic analysis of solar-assisted vertical ground source heat pump system for heating season. J Mech Sci Technol 2018;32:3929–3942. [CrossRef]
  • [10] Khanna A, Kaur S. An empirical analysis on adoption of precision agricultural techniques among farmers of Punjab for efficient land administration. Land Use Policy 2023;126:106533. [CrossRef]
  • [11] Suryanarayanan R, Sridhar VG, Natrayan L, Seeniappan K, Merneedi A, Sathish T, et al. Improvement on mechanical properties of submerged friction stir joining of dissimilar tailor welded aluminum blanks. Adv Mater Sci Eng 2021;2021:16. [CrossRef]
  • [12] Gu J, Hu M, Wang X, Ji Y, Li L, Yu J, et al. Data mining analysis reveals key acupoints and meridians for the treatment of chemotherapy-induced peripheral neuropathy. Explore (NY) 2023;19:7177. [CrossRef]
  • [13] Guna D, Vinodh D. Comparison of material removal rate of AA2014 aluminum alloy using HSS M42 and Titanium Nitride coated drill tools. Mater Today Proceed 2023;77:409413. [CrossRef]
  • [14] Kanishka D, Ramesh Kumar G. Compressive strength of novel polymer coated concrete with polypropylene fiber. Mater Today Proceed 2023;77:401404. [CrossRef]
  • [15] Sarkar D. Advanced materials management for Indian construction industry by application of statistical process control tools. Material Today: Proceed 2022;62:69346939. [CrossRef]
  • [16] Sarkar D, Bhattacharjee B. Design and application of multivariate CUSUM for quality monitoring of ready mixed concrete. Int J Quality Eng Technol 2014;4(2):161. [CrossRef]
  • [17] Xue L, Qiu P. A nonparametric CUSUM chart for monitoring multivariate serially correlated processes. Int J Quality Eng Technol 2021;53(4):396409. [CrossRef]
  • [18] Ünal F, Bulut H, Kahraman A. Energy and cost analysis of horizontal type corn drying plant using LPG fuel. Dicle Univ J Eng 2020;11(1):161170. [CrossRef]
  • [19] Ünal F. Energy and exergy analysis of an industrial corn dryer operated by two different fuels. Int J Exergy 2021;34:475491. [CrossRef]
  • [20] Boullosa-Falces D, Gomez-Solaetxe MA, Sanchez-Varela Z, García S, Trueba A. Validation of CUSUM control chart for biofouling detection in heat exchangers. Appl Therm Eng 2019;152:2431. [CrossRef]
  • [21] Nawaz M, Maulud AS, Zabiri H, Taqvi SAA, Idris A. Improved process monitoring using the CUSUM and EWMA-based multiscale PCA fault detection framework. Chinese J Chem Eng2021;29:253265. [CrossRef]
  • [22] Bellotti M, Qian J, Reynaerts D. Self-tuning breakthrough detection for EDM drilling micro holes. J Manufactur Process 2020;57:630640. [CrossRef]
  • [23] Li Z, Paredis CJ, Augenbroe G, Huang G. A rule augmented statistical method for air-conditioning system fault detection and diagnostics. Energy Build 2012;54:154159. [CrossRef]
  • [24] Nathaphan S, Therdyothin A. Effectiveness evaluation of the energy efficiency and conservation measures for stipulation of Thailand energy management system in factory. J Clean Prod 2023;383:135442. [CrossRef]
  • [25] Benedetti M, Bonfà F, Introna V, Santolamazza A, Ubertini S. Real Time energy performance control for industrial compressed air systems: Methodology and applications. Energies 2019;12:3935. [CrossRef]
  • [26] Fichera A, Volpe R, Cutore E. Energy performance measurement, monitoring and control for buildings of public organizations: Standardized practises compliant with the ISO 50001 and ISO 50006. Dev Built Environ 2020;4:100024. [CrossRef]
  • [27] Riaz M, Abbas N, Does RJMM. Improving the performance of CUSUM charts. Qual Reliab Eng Int 2011;27:415424. [CrossRef]
  • [28] Montgomery DC. Introduction to Statistical Quality Control. 7th ed. New York: John Wiley & Sons; 2013.
  • [29] Li Y, Deng X, Liu B, Ma J, Yang F, Ouyang M. Energy management of a parallel hybrid electric vehicle based on Lyapunov algorithm. eTransport 2022;13:100184. [CrossRef]
  • [30] The Union of Chambers and Commodity Exchanges of Turkiye. Industry Directorate, Capacity Criteria 3112 Milk and products capacity calculation. https://tobb.org.tr/Sayfalar/Eng/AmaciveYapisi.php Last Accessed Date 22.09.2023.
  • [31] Prabhakar P, Srivastav P, Murari K. Energy consumption during manufacturing of different dairy products in a commercial dairy plant: A case study. Asia J Dairy Food Res 2015;34:98. [CrossRef]
  • [32] Montgomery DC, Peck EA, Vining GG, Introduction to Linear Regression Analysis. 3rd ed. New York: John Wiley & Sons; 2001.
  • [33] Li J. Nonparametric adaptive CUSUM chart for detecting arbitrary distributional changes. J Quality Technol 2021;53:154172. [CrossRef]
  • [34] Huang W, Shu L, Jiang W. A gradient approach to the optimal design of CUSUM charts under unknown mean-shift sizes. J Qual Technol 2016;48:6883. [CrossRef]
  • [35] Wen X, Cao H, Hon B, Chen E, Li H. Energy value mapping: A novel lean method to integrate energy efficiency into production management. Energy 2021;217:119353. [CrossRef]
  • [36] Siddique ARM, Bozorgi M, Venkateshwar K, Tasnim S, Mahmud S. Phase change material-enhanced solid-state thermoelectric cooling technology for food refrigeration and storage applications. J Energy Storage 2023;60:106569. [CrossRef]
  • [37] Zhang W, Huang J, Zhang T, Tan Q. A risk-based stochastic model for supporting resources allocation of agricultural water-energy-food system under uncertainty. J Hydrol 2022;610:127864. [CrossRef]
  • [38] Tan Q, Zhang T. Robust fractional programming approach for improving agricultural water-use efficiency under uncertainty. J Hydrolog 2018;564:11101119. [CrossRef]
  • [39] Li M, Fu Q, Singh VP, Ji Y, Liu D, Zhang C, Li T. An optimal modelling approach for managing agricultural water-energy-food nexus under uncertainty. Sci Total Environ 2019;651(Pt 1):14161434. [CrossRef]
  • [40] Jing R, He Y, He J, Liu Y, Yang S. Global sensitivity based prioritizing the parametric uncertainties in economic analysis when co-locating photovoltaic with agriculture and aquaculture in China. Renew Energy 2022;194:10481059. [CrossRef]
  • [41] Zheng Z, Ji L, Xie Y, Huang G, Pan J. Synergic management of crop planting structure and biomass utilization pathways under a food-energy-water nexus perspective. J Clean Prod 2022;335:130314. [CrossRef]
  • [42] Beck MB, Chen C, Walker RV, Wen Z, Han J. Multi-sectoral analysis of smarter urban nitrogen metabolism: A case study of Suzhou, China. Ecol Model 2023;478:110286. [CrossRef]
  • [43] Esen H, Inalli M, Esen M. Technoeconomic appraisal of a ground source heat pump system for a heating season in eastern Turkey. Energy Convers Manag 2006;47:12811297. [CrossRef]
  • [44] Holman JP. Experimental methods for engineers. 7th ed. New York: McGraw Hill; 2001.
  • [45] Esen M, Yuksel T. Experimental evaluation of using various renewable energy sources for heating a greenhouse. Energy Build 2013;65:340351.
  • [46] Erbay Z, Koca N. Energetic, Exergetic, and Exergoeconomic Analyses of Spray-Drying Process during White Cheese Powder Production. Dry Technol 2012;30:435444. [CrossRef]
  • [47] Figliola RS, Beasley D. Theory and Design for Mechanical Measurements. 6th ed. New Jersey: John Wiley & Sons Inc; 2015.
  • [48] Bobovnik G, Kutin J. Uncertainty analysis of the air velocity standard based on LDA and wind tunnel. Measure 2023;206:112228. [CrossRef]
  • [49] Cengel YA, Boles MA, Kanoglu M. Thermodynamics: An Engineering Approach. New York: Mcgraw-Hill Education; 2019.
  • [50] Başaran A, Yılmaz T, Azgın Şükrü T, Çivi C. Comparison of drinking milk production with conventional and novel inductive heating in pasteurization in terms of energetic, exergetic, economic and environmental aspects. J Clean Product 2021;317:128280. [CrossRef]
  • [51] Solanki A, Pal Y. A comprehensive review to study and implement solar energy in dairy industries. J Therm Eng 2021;7(5):1216–1238. [CrossRef]
  • [52] Heydari A, Forati M, Khatam SM. Thermal performance investigation of a hybrid solar air heater applied in a solar dryer using thermodynamic modeling. J Therm Eng 2021;7:715–730. [CrossRef]
  • [53] Margolies B, Adams MC, Pranata J, Gondoutomo K, Barbano DM. Effect of uncertainty in composition and weight measures in control of cheese yield and fat loss in large cheese factories. J Dairy Sci 2017;100:68226852. [CrossRef]
  • [54] Lincoln BJ, Kong L, Pineda AM, Walmsley TG. Process integration and electrification for efficient milk evaporation systems. Energy 2022;258:124885. [CrossRef]
  • [55] Bühler F, Nguyen T-V, Jensen JK, Holm FM, Elmegaard B. Energy, exergy and advanced exergy analysis of a milk processing factory. Energy 2018;162:576592. [CrossRef]
  • [56] Bühler F, Zühlsdorf B, Nguyen T-V, Elmegaard B. A comparative assessment of electrification strategies for industrial sites: Case of milk powder production. Appl Energy 2019;250:13831401. [CrossRef]
There are 57 citations in total.

Details

Primary Language English
Subjects Thermodynamics and Statistical Physics
Journal Section Articles
Authors

Öznur Öztuna Taner This is me 0000-0001-7867-5540

Publication Date October 17, 2023
Submission Date May 15, 2023
Published in Issue Year 2023 Volume: 9 Issue: 5

Cite

APA Öztuna Taner, Ö. (2023). Energy and production analysis of a dairy milk factory: A case of study. Journal of Thermal Engineering, 9(5), 1163-1176. https://doi.org/10.18186/thermal.1370731
AMA Öztuna Taner Ö. Energy and production analysis of a dairy milk factory: A case of study. Journal of Thermal Engineering. October 2023;9(5):1163-1176. doi:10.18186/thermal.1370731
Chicago Öztuna Taner, Öznur. “Energy and Production Analysis of a Dairy Milk Factory: A Case of Study”. Journal of Thermal Engineering 9, no. 5 (October 2023): 1163-76. https://doi.org/10.18186/thermal.1370731.
EndNote Öztuna Taner Ö (October 1, 2023) Energy and production analysis of a dairy milk factory: A case of study. Journal of Thermal Engineering 9 5 1163–1176.
IEEE Ö. Öztuna Taner, “Energy and production analysis of a dairy milk factory: A case of study”, Journal of Thermal Engineering, vol. 9, no. 5, pp. 1163–1176, 2023, doi: 10.18186/thermal.1370731.
ISNAD Öztuna Taner, Öznur. “Energy and Production Analysis of a Dairy Milk Factory: A Case of Study”. Journal of Thermal Engineering 9/5 (October 2023), 1163-1176. https://doi.org/10.18186/thermal.1370731.
JAMA Öztuna Taner Ö. Energy and production analysis of a dairy milk factory: A case of study. Journal of Thermal Engineering. 2023;9:1163–1176.
MLA Öztuna Taner, Öznur. “Energy and Production Analysis of a Dairy Milk Factory: A Case of Study”. Journal of Thermal Engineering, vol. 9, no. 5, 2023, pp. 1163-76, doi:10.18186/thermal.1370731.
Vancouver Öztuna Taner Ö. Energy and production analysis of a dairy milk factory: A case of study. Journal of Thermal Engineering. 2023;9(5):1163-76.

IMPORTANT NOTE: JOURNAL SUBMISSION LINK http://eds.yildiz.edu.tr/journal-of-thermal-engineering