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A particle swarm optimization algorithm for multi-row facility layout problem in semiconductor fabrication

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Abstract

Semiconductor chips are the most basic components of smart wearable device and other AI devices. The problem of facility layout in semiconductor fabrication is considered very important, for it will affect the cost saving and performance improvement of the key chips implanted in artificial intelligence production such as intelligent wearable devices. Facility layout problem in semiconductor fabrication is to determine the optimal placement of facilities in a multi-row particular area. In this study, we propose a mathematical model to solve multi-row facility layout problem regarded as a predefined system of discrete points to place the processing modules at different locations in semiconductor fabrication plants (i.e., semiconductor fabrication). Considering the large amounts of computation required we use particle swarm optimization (PSO) algorithm to solve the multi-row facility layout problem by minimizing the total transportation distance between the modules. The results confirm that the PSO algorithm is an effective and practical approach for solving the multi-row facility layout problem within a shorter period. The effect of the number of particles on the efficiency of the PSO algorithm is also discussed in this paper.

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References

  • Afentakis PA (1989) Loop layout design problem for flexible manufacturing systems. Int J Flex Manuf Syst 1:143–175

    Article  Google Scholar 

  • Ahmadi A, Pishvaee MS, Jokar MRA (2017) A survey on multi-floor facility layout problems. Comput Ind Eng 107:158–170

    Article  Google Scholar 

  • Aiello G, Enea M, Galante G (2006) A multi-objective approach to facility layout problem by genetic search algorithm and Electre method. Robot Cim Int Manuf 22:447–455

    Article  Google Scholar 

  • Alves DTS, de Medeiros JL, Araujo ODF (2016) Optimal determination of chemical plant layout via minimization of risk to general public using Monte Carlo and simulated annealing techniques. J Loss Prevent Proc 41:202–214

    Article  Google Scholar 

  • Azadeh A, Haghighi SM, Asadzadeh SM, Saedi H (2013) A new approach for layout optimization in maintenance workshops with safety factors: the case of a gas transmission unit. J Loss Prevent Proc 26:1457–1465

    Article  Google Scholar 

  • Azadeh A, Haghighi SM, Asadzadeh SM (2014) A novel algorithm for layout optimization of injection process with random demands and sequence dependent setup times. J Manuf Syst 33:287–302

    Article  Google Scholar 

  • Azevedo MM, Crispim JA, de Sousa JP (2017) A dynamic multi-objective approach for the reconfigurable multi-facility layout problem. J Manuf Syst 42:140–152

    Article  Google Scholar 

  • Balakrishnan J, Cheng CH, Conway DG, Lau CM (2003b) A hybrid genetic algorithm for the dynamic plant layout problem. Int J Prod Econ 86:107–120

    Article  Google Scholar 

  • Benabes J, Poirson E, Bennis F (2013) Integrated and interactive method for solving layout optimization problems. Expert Syst Appl 40:5796–5803

    Article  Google Scholar 

  • Benvenuto G, Campora U, Trucco A (2014) Comparison of ship plant layouts for power and propulsion systems with energy recovery. J Mar Eng Technol 13:3–15

    Article  Google Scholar 

  • Bozer YA, Meller RD, Erlebacher SJ (1994) An improvement-type layout algorithm for single and multiple floor facilities. Manag Sci 40:918–932

    Article  MATH  Google Scholar 

  • Camacho C, Novais P (2017) Innovations and practical applications of intelligent systems in ambient intelligence and humanized computing. J Amb Intel Hum Comp 8:155–156

    Article  Google Scholar 

  • Caputo AC, Pelagagge PM, Palumbo M, Salini P (2015) Safety-based process plant layout using genetic algorithm. J Loss Prevent Proc 34:139–150

    Article  Google Scholar 

  • Chen GYH (2013) A new data structure of solution representation in hybrid ant colony optimization for large dynamic facility layout problems. Int J Prod Econ 142:362–371

    Article  Google Scholar 

  • Chen T (2018) An innovative fuzzy and artificial neural network approach for forecasting yield under an uncertain learning environment. J Amb Intel Hum Comp 9:1013–1025

    Article  Google Scholar 

  • Chen T, Tsai HR (2018) Application of industrial engineering concepts and techniques to ambient intelligence: a case study. J Amb Intel Hum Comp 9:215–223

    Article  Google Scholar 

  • Chen DS, Wang Q, Chen HC (2001) Linear sequencing for machine layouts by a modified simulated annealing. Int J Prod Res 39:1721–1732

    Article  MATH  Google Scholar 

  • Cheng R, Gen M, Tosawa T (1996) Genetic algorithms for designing loop layout manufacturing systems. Comput Ind Eng 31:587–591

    Article  Google Scholar 

  • Djellab H, Gourgand A (2001) A new heuristic procedure for the single-row facility layout problem. Int J Comput Integ M 14:270–280

    Article  Google Scholar 

  • Garey MR, Johnson DS (1979) Computers and intractability: a guide to the theory of NP-completeness. WH Freeman, New York

    MATH  Google Scholar 

  • Gebraad P, Thomas JJ, Ning A, Fleming P, Dykes K (2017) Maximization of the annual energy production of wind power plants by optimization of layout and yaw-based wake control. Wind Energy 20:97–107

    Article  Google Scholar 

  • Hassan MMD (1994) Machine layout problem in modern manufacturing facilities. Int J Prod Res 32:2559–2584

    Article  MATH  Google Scholar 

  • Hosseini S, Al Khaled A, Vadlamani S (2014) Hybrid imperialist competitive algorithm, variable neighborhood search, and simulated annealing for dynamic facility layout problem. Neural Comput Appl 25:1871–1885

    Article  Google Scholar 

  • Izadinia N, Eshghi K, Salmani MH (2014) A robust model for multi-floor layout problem. Comput Ind Eng 78:127–134

    Article  Google Scholar 

  • Kennedy J, Eberhart R (1995) Particle swarm optimization. Proc IEEE Int Conf Neural Netw 4:1942–1948

    Article  Google Scholar 

  • Kim JG, Kim YD (2000) Layout planning for facilities with fixed shapes and input and output points. Int J Prod Res 38:4635–4653

    Article  MATH  Google Scholar 

  • Koopmans TC, Beckmann M (1957) Assignment problems and the location of economic activities. Econometrica 25:53–76

    Article  MathSciNet  MATH  Google Scholar 

  • Kouvelis P, Kurawarwala AA, Gutierrez GJ (1992) Algorithms for robust single and multiple period layout planning for manufacturing systems. Eur J Oper Res 63:287–303

    Article  MATH  Google Scholar 

  • Kulturel-Konak S, Konak A (2015) A large-scale hybrid simulated annealing algorithm for cyclic facility layout problems. Eng Optimiz 47:963–978

    Article  MathSciNet  MATH  Google Scholar 

  • Kumar KR, Hadjinicola GC, Lin TL (1995) A heuristic procedure for the single-row facility layout problem. Eur J Oper Res 87:65–73

    Article  MATH  Google Scholar 

  • Lee CJ (2015) Optimal multi-floor plant layout based on the mathematical programming and particle swarm optimization. Ind Health 53:491–497

    Article  Google Scholar 

  • Lee GC, Kim YD (2000) Algorithms for adjusting shapes of departments in block layouts on the gird-based plane. Omega 28:111–122

    Article  Google Scholar 

  • Lee DH, Lee CJ (2017) The plant layout optimization considering the operating conditions. J Chem Eng Jpn 50:568–576

    Article  Google Scholar 

  • Li BT, Yan SN, Lin QY (2016) Automated layout design of stiffened container structures based on the morphology of plant ramifications. J Bionic Eng 13:344–354

    Article  Google Scholar 

  • Liu JF, Wang DW, He K, Xue Y (2017) Combining Wang–Landau sampling algorithm and heuristics for solving the unequal-area dynamic facility layout problem. Eur J Oper Res 262:1052–1063

    Article  MathSciNet  MATH  Google Scholar 

  • Mazinani M, Abedzadeh M, Mohebali N (2013) Dynamic facility layout problem based on flexible bay structure and solving by genetic algorithm. Int J Adv Manuf Tech 65:929–943

    Article  Google Scholar 

  • Medina-Herrera N, Jimenez-Gutierrez A, Grossmann IE (2014) A mathematical programming model for optimal layout considering quantitative risk analysis. Comput Chem Eng 68:165–181

    Article  Google Scholar 

  • Modi A, Haglind F (2015) Thermo dynamic optimisation and analysis of four Kalina cycle layouts for high temperature applications. Appl Therm Eng 76:196–205

    Article  Google Scholar 

  • Mohamadghasemi A, Hadi-Vencheh A (2012) An integrated synthetic value of fuzzy judgments and nonlinear programming methodology for ranking the facility layout patterns. Comput Ind Eng 62:342–348

    Article  Google Scholar 

  • Tompkins JA, White JA, Bozer YA, Frazelle EH, Tanchoco JM, Trevino J (1996) Facilities planning. Wiley, New York

    Google Scholar 

  • Ulutas BH, Islier AA (2009) A clonal selection algorithm for dynamic facility layout problems. J Manuf Syst 28:123–131

    Article  Google Scholar 

  • Ulutas B, Islier AA (2015) Dynamic facility layout problem in footwear industry. J Manuf Syst 36:55–61

    Article  Google Scholar 

  • Wu Y, Wang YF, Feng X (2016) A heuristic approach for petrochemical plant layout considering steam pipeline length. Chin J Chem Eng 24:1032–1037

    Article  Google Scholar 

  • Yang T, Peters BA, Tu M (2005) Layout design for flexible manufacturing systems considering single-loop directional flow patterns. Eur J Oper Res 164:440–455

    Article  MATH  Google Scholar 

  • Zhang CJ, Yang YJ, Du ZW, Ma C (2016) Particle swarm optimization algorithm based on ontology model to support cloud computing applications. J Amb Intel Hum Comp 7:633–638

    Article  Google Scholar 

  • Zhang MG, Dou Z, Liu LF, Jiang JC, Mebarki A, Ni L (2017) Study of optimal layout based on integrated probabilistic framework (IPF): case of a crude oil tank farm. J Loss Prevent Proc 48:305–311

    Article  Google Scholar 

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Authors and Affiliations

  1. Logistics Engineering and Management, Shanghai Maritime University, Shanghai, China

    Biqin Hu & Bin Yang

  2. Logistics Management, Zhejiang Textile and Fashion College, Ningbo, China

    Biqin Hu

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  1. Biqin Hu
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  2. Bin Yang
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Correspondence to Biqin Hu.

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Hu, B., Yang, B. A particle swarm optimization algorithm for multi-row facility layout problem in semiconductor fabrication. J Ambient Intell Human Comput 10, 3201–3210 (2019). https://doi.org/10.1007/s12652-018-1037-3

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  • DOI: https://doi.org/10.1007/s12652-018-1037-3

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