Karafan Journal

Karafan Journal

Optimization of Manpower Composition in the Production Line According to the Product Diversity with a Simulation Approach (Case Study: Chocolate Dragee Production Line in Shirin Asal Company)

Document Type : Original Article

Authors
Mehdi Mohammadi Asl 1
Mehdi Yousefi Nejad Attari 2
1 M.Sc, Department of Industrial Engineering, Bonab branch, Islamic Azad University, Bonab, Iran.
2 Assistant Professor, Department of Industrial Engineering, Bonab branch, Islamic Azad University, Bonab, Iran.
10.48301/kssa.2021.273148.1394
Abstract
Today, simulation studies have found many applications in industrial engineering and other sciences. In today's competitive market, companies and organizations are trying to increase productivity and efficiency by designing and modeling effective and efficient system operations. In this regard, to reduce evaluation time and reduce costs, use similar methods. Graphic construction in software environment and the use of statistical software are instructive and efficient. The purpose of this research was to reduce costs, increase production, reduce the unemployment time of operators and machines, as well as reduce inventories between the production processes. Simulation was used to achieve these goals. The steps of conducting the research are summarized as follows. First, the layout in the factory was identified, in the next step, timing was done for the devices and operators. Real data was transferred from the production line to the software environment and then 15 different scenarios were designed and simulated in the software environment. Then, using TOPSIS method, the best scenario was selected and using the experts and factory managers, the validity of the model was confirmed and then the model Execution and simulation results were recorded.

Highlights

[1] Rezaian, A. (2014). System analysis and design (16 ed.). Samt. https://www.gisoom.com/ book/11003471

[2] Trout, B., & Bisson, W. (2009). Continuous manufacturing of small-molecule pharamceuticals. http://www.qbd-dtc.com/wp-content/uploads/continuous-manufacturing.pdf

[3] Lee, S. L., O’Connor, T. F., Yang, X., Cruz, C. N., Chatterjee, S., Madurawe, R. D., Moore, C. M. V., Yu, L. X., & Woodcock, J. (2015). Modernizing Pharmaceutical Manufacturing: from Batch to Continuous Production. Journal of Pharmaceutical Innovation, 10(3), 191-199. https://doi.org/10.1007/s12247-015-9215-8

[4] Jacoby, R., Pernenkil, L., Harutunian, S., Heim, M., Sabad, A. (2015). Advanced Biopharmaceutical Manufacturing: An Evolution Underway. Deloitte. https://www2.deloitte.com/cont ent/dam/Deloitte/us/Documents/life-sciences-health-care/us-lshc-advanced-biopha rmaceutical-manufacturing-white-paper-051515.pdf

[5] Darabi, M., & Shah Heidari, N. (2010). Computer simulation training with Enterprise Dynamics software. Kian Rayaneh Sabz. https://www.simayedanesh.ir/book/19727

[6] Vinod, V., & Sridharan, R. (2011). Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system. International Journal of Production Economics, 129(1), 127-146. https://doi.org/10 .1016/j.ijpe.2010.08.017

[7] Asadi, F., & Bahari, A. (2017, July 3). Organizational resource planning in the emergency department using simulation model optimization. 7 th International Conference on Accounting and Management with Modern research Sciences, Tehran, Iran. https://c ivilica.com/doc/658511/

[8] Ameri, E., Mostafavi, M., Daliri Moghadam, H., & Sepehri, M. M. (2013, January 20). Optimize the use of production line resources to increase productivity with a simulation approach. 9th International Industrial Engineering Conference, Tehran, Iran. https:/ /civilica.com/doc/189228/

[9] Rasib, A. A. (2021). Production Smoothness Improvement through ARENA Application in theFood Manufacturing Industry. Turkish Journal of Computer and Mathematics Education 12(3), 3516-3526. https://doi.org/10.17762/turcomat.v12i3.1627

[10] Carata, E. (2020). Analysis of shop floor machine parts manufacturing through discrete event simulation. Gheorghe Asachi Technical University of Iasi, 66(70), 35-42. http s://www.cmmi.tuiasi.ro/wp-content/uploads/buletin/2020%20fasc%204/L4_CMM I%204_2020.pdf

[11] Company, M. S., & Azimi, P. (2017). Developing and Solving a New Bi-Objective Model to Assign Human Resource And Equipment to Parallel Workstations in a Product ion Line Using Optimization Via Simulation Technique. Industrial Management Studies, 15(46), 57-71. https://doi.org/10.22054/jims.2017.7988

[12] Yaghoubi, N., Dehghani, M., & Omidvar, M. (2017). A model for the establishment of meta-synthesis technique based entrepreneurial university and TOPSIS. Karafan Quarterly Scientific Journal, 14(1), 51-65. https://karafan.tvu.ac.ir/article_100500. html?lang=en

Keywords
Continuous Production System
Simulation Production
Factory Packing System
Topsis
Shannon Entropy
Subjects
[1] Rezaian, A. (2014). System analysis and design (16 ed.). Samt. https://www.gisoom.com/ book/11003471
[2] Trout, B., & Bisson, W. (2009). Continuous manufacturing of small-molecule pharamceuticals. http://www.qbd-dtc.com/wp-content/uploads/continuous-manufacturing.pdf
[3] Lee, S. L., O’Connor, T. F., Yang, X., Cruz, C. N., Chatterjee, S., Madurawe, R. D., Moore, C. M. V., Yu, L. X., & Woodcock, J. (2015). Modernizing Pharmaceutical Manufacturing: from Batch to Continuous Production. Journal of Pharmaceutical Innovation, 10(3), 191-199. https://doi.org/10.1007/s12247-015-9215-8
[4] Jacoby, R., Pernenkil, L., Harutunian, S., Heim, M., Sabad, A. (2015). Advanced Biopharmaceutical Manufacturing: An Evolution Underway. Deloitte. https://www2.deloitte.com/cont ent/dam/Deloitte/us/Documents/life-sciences-health-care/us-lshc-advanced-biopha rmaceutical-manufacturing-white-paper-051515.pdf
[5] Darabi, M., & Shah Heidari, N. (2010). Computer simulation training with Enterprise Dynamics software. Kian Rayaneh Sabz. https://www.simayedanesh.ir/book/19727
[6] Vinod, V., & Sridharan, R. (2011). Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system. International Journal of Production Economics, 129(1), 127-146. https://doi.org/10 .1016/j.ijpe.2010.08.017
[7] Asadi, F., & Bahari, A. (2017, July 3). Organizational resource planning in the emergency department using simulation model optimization. 7 th International Conference on Accounting and Management with Modern research Sciences, Tehran, Iran. https://c ivilica.com/doc/658511/
[8] Ameri, E., Mostafavi, M., Daliri Moghadam, H., & Sepehri, M. M. (2013, January 20). Optimize the use of production line resources to increase productivity with a simulation approach. 9th International Industrial Engineering Conference, Tehran, Iran. https:/ /civilica.com/doc/189228/
[9] Rasib, A. A. (2021). Production Smoothness Improvement through ARENA Application in theFood Manufacturing Industry. Turkish Journal of Computer and Mathematics Education 12(3), 3516-3526. https://doi.org/10.17762/turcomat.v12i3.1627
[10] Carata, E. (2020). Analysis of shop floor machine parts manufacturing through discrete event simulation. Gheorghe Asachi Technical University of Iasi, 66(70), 35-42. http s://www.cmmi.tuiasi.ro/wp-content/uploads/buletin/2020%20fasc%204/L4_CMM I%204_2020.pdf
[11] Company, M. S., & Azimi, P. (2017). Developing and Solving a New Bi-Objective Model to Assign Human Resource And Equipment to Parallel Workstations in a Product ion Line Using Optimization Via Simulation Technique. Industrial Management Studies, 15(46), 57-71. https://doi.org/10.22054/jims.2017.7988
[12] Yaghoubi, N., Dehghani, M., & Omidvar, M. (2017). A model for the establishment of meta-synthesis technique based entrepreneurial university and TOPSIS. Karafan Quarterly Scientific Journal, 14(1), 51-65. https://karafan.tvu.ac.ir/article_100500. html?lang=en
Karafan Journal
Volume 20, Issue 1 - Serial Number 61
Technical & Engineering
Spring 2023
Pages 433-451

  • Receive Date 23 May 2021
  • Revise Date 26 September 2021
  • Accept Date 11 October 2021