Optimization Processes and Analysis of Impact on Productivity

Hassan, Abid; Islam, Md. Shihabul

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dc.contributor.author	Hassan, Abid
dc.contributor.author	Islam, Md. Shihabul
dc.date.accessioned	2022-04-21T03:46:47Z
dc.date.available	2022-04-21T03:46:47Z
dc.date.issued	2021-03-30
dc.identifier.citation	Kano M, Nakagawa Y. Data-based process monitoring, process control, and quality improvement: Recent developments and applications in steel industry. Comput Chem Eng. 2008;32(1–2):12–24. Vincent B, Duhamel C, Ren L, Tchernev N. An industrial process optimization approach based on input and output statistical data analysis. IFAC-PapersOnLine. 2015;28(3):930–5. Bryton B. Balancing of a continuous production line. Northwestern University; 1954. Baybars I. A survey of exact algorithms for the simple assembly line balancing problem. Manage Sci. 1986;32(8):909–32. Boysen N, Fliedner M, Scholl A. A classification of assembly line balancing problems. Eur J Oper Res. 2007;183(2):674–93. Scholl A, Becker C. State-of-the-art exact and heuristic solution procedures for simple assembly line balancing. Eur J Oper Res. 2006;168(3):666–93. Elbert M. Lean production for the small company. Crc Press; 2012. Nguyen M-N, Do N-H. Re-engineering assembly line with lean techniques. Procedia CIRP. 2016;40:590–5. Indrawati S, Ridwansyah M. Manufacturing continuous improvement using lean six sigma: An iron ores industry case application. Procedia Manuf. 2015;4:528–34. Baudin M. Lean assembly: the nuts and bolts of making assembly operations flow. CRC [38] Press; 2002. Womak J, Jones DT, Roos D. The machine that changed the world. New York Rawson Assoc. 1990; Law JM. Puppets of nostalgia: The life, death, and rebirth of the Japanese Awaji ningyō tradition. Princeton University Press; 2015. Helgeson WB, Birnie DP. Assembly line balancing using the ranked positional weight technique. J Ind Eng. 1961;12(6):394–8. Kilbridge MD, Wester L. A heuristic method of assembly line balancing. J Ind Eng. 1961;12(4):292–8. Kit BW, Olugu EU, Zulkoffli Z binti. Redesigning of lamp production assembly line. Proc Int Conf Ind Eng Oper Manag. 2018;2018-March(1955):3439–57. Choon JWK, Olugu EU, binti Zulkoffli Z. Remodelling the process flow of metal division assembly line. Proc Int Conf Ind Eng Oper Manag. 2018;2018-March:3425–38. Wazed MA, Ahmed S, Nukman Y. Application of Taguchi method to analyse the impacts of common process and batch size in multistage production system under uncertain conditions. Eur J Ind Eng. 2011;5(2):215–31. Wazed MA, Ahmed S, Yusoff N. Uncertainty factors in real manufacturing environment. Aust J Basic Appl Sci. 2009;3(2):342–51. Koh SCL, Saad SM. MRP-controlled manufacturing environment disturbed by uncertainty. Robot Comput Integr Manuf. 2003;19(1–2):157–71. [39] Nazif A, Kamar N, Dahan SM. Improving productivity by simulate facility layout: a case study in a car component manufacturer. Int J Ind Manag. 2016;2(June 2016):72–80. Ahmed I, Sultana I. A literature review on inventory modeling with reliability consideration. Int J Ind Eng Comput. 2014;5(1):169–78.	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/1375
dc.description	Supervised by Dr. A. R. M. Harunur Rashid, Department of Mechanical & Production Engineering (MPE), Islamic University of Technology(IUT), Board Bazar, Gazipur, Dhaka, Bangladesh	en_US
dc.description.abstract	Optimization in industrial systems is crucial for the competitiveness of any industry in a competitive economy. A well optimized process can ensure most effective utilization of the limited resources, prove to be cost-effective and thereby increase profitability. This paper carries out literal review on several categories of optimization, such as, line optimization, production process optimization, layout optimization and inventory optimization; and tools and processes like discrete event simulation (DES), time study, root cause analysis, ANOVA, EOQ, EPQ etc. that are used to evaluate different models and scenarios for optimizing current systems. It also investigates the most effective solutions as mentioned by different researchers in their specific situations. The paper also documents the applications of such optimization porecesses in a local chemical factory and analyzes productivity improvement through these optimization processes. Finally, it is concluded that with widespread use of such optimization techniques across different industries, organizations can better enable themselves to grow and thrive	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Mechanical and Production Engineering (MPE),Islamic University of Technology(IUT), Board Bazar, Gazipur, Bangladesh	en_US
dc.title	Optimization Processes and Analysis of Impact on Productivity	en_US
dc.type	Thesis	en_US