A survey on assembly lines and its types

Ullah SAIF, Zailin GUAN, Baoxi WANG, Jahanzeb MIRZA, Shiyang HUANG

PDF(234 KB)
PDF(234 KB)
Front. Mech. Eng. ›› 2014, Vol. 9 ›› Issue (2) : 95-105. DOI: 10.1007/s11465-014-0302-1
REVIEW ARTICLE
REVIEW ARTICLE

A survey on assembly lines and its types

Author information +
History +

Abstract

Assembly lines are useful for mass production of standard as well as customized products. Line balancing is an important issue, in this regard an optimal or near optimal balance can provide a fruitful savings in the initial cost and also in the running cost of such production systems. A survey of different problems in different types of assembly lines and some of the critical and on going research areas are highlighted here. The provided research information is momentous for the research community in assembly line area to proceed further in the presented issues of assembly lines.

Keywords

assembly lines / line balancing / survey

Cite this article

Download citation ▾
Ullah SAIF, Zailin GUAN, Baoxi WANG, Jahanzeb MIRZA, Shiyang HUANG. A survey on assembly lines and its types. Front. Mech. Eng., 2014, 9(2): 95‒105 https://doi.org/10.1007/s11465-014-0302-1

References

[1]
ShtubA, Dar-ElE M. A methodology for the selection of assembly systems. International Journal of Production Research, 1989, 27(1): 175-186
CrossRef Google scholar
[2]
MatherH. Competitive manufacturing. Prentice Hall, Englewood Cliffs, NJ, 1989
[3]
PineB J. Mass customization: The new frontier in business competition. Harvard Business School Press, Boston, Mass, 1993
[4]
BeckerC, SchollA. A survey on problems and methods in generalized assembly line balancing. European Journal of Operational Research, 2006, 168(3): 694-715
CrossRef Google scholar
[5]
NilsBoysen, MalteFliedner, ArminScholl. A classification of assembly line balancing problems. European Journal of Operational Research, 2007, 2007: 674-693.
[6]
BaybarsI. A survey of exact algorithms for the simple assembly line balancing problem. Management Science, 1986, 32(8): 909-932
CrossRef Google scholar
[7]
GhoshS, GagnonR. A comprehensive literature review and analysis of the design, balancing and scheduling of assembly systems. International Journal of Production Research, 1989, 27(4): 637-670
CrossRef Google scholar
[8]
ErelE, SarinS. A survey of the assembly line balancing procedures. Production Planning and Control, 1998, 9(5): 414-434
CrossRef Google scholar
[9]
SchollA, BeckerC. State–of–the–art exact and heuristic solution procedures for simple assembly line balancing. European Journal of Operational Research, 2006, 168(3): 666-693
CrossRef Google scholar
[10]
BoysenN, FliednerM, SchollA. Assembly line balancing: Which model to use when? International Journal of Production Economics, 2008, 111(2): 509-528
CrossRef Google scholar
[11]
UrbanT L, ChiangW C. An optimal piecewise-linear program for the U-line balancing problem with stochastic task times. European Journal of Operational Research, 2006, 168(3): 109-120
CrossRef Google scholar
[12]
AltiparmakA, BugakA, DengizB. Optimization of buffer sizes in assembly systems using intelligent techniques. In Proceedings of Winter Simulation Conference, San Diego, USA, 2002, 1157-1162.
[13]
D’SouzaK, KhatorS. System reconfiguration to avoid deadlocks in automated manufacturing systems. Computers & Industrial Engineering, 1997, 32(2): 445-465
[14]
HamadaM, MartzH, BergE, KoehlerA. Optimizing the product-based avaibility of a buffered industrial process. Reliability Engineering & System Safety, 2006, 91(9): 1039-1048
CrossRef Google scholar
[15]
BattiniD, FaccioM, PersonaA, SgarbossaF. Design of the optimal feeding policy in an assembly system. International Journal of Production Economics, 2009, 121(1): 233-254
CrossRef Google scholar
[16]
GershwinS, SchorJ. Efficient algorithms for buffer space allocation. Annals of Operations Research, 2000, 93(1/4): 117-144
CrossRef Google scholar
[17]
ThomopoulosN T. Mixed model line balancing with smoothed station assignments. Management Science, 1970, 16(9): 593-603
CrossRef Google scholar
[18]
Dar-ElE M, NadiviA. A mixed-model sequencing application. International Journal of Production Research, 1981, 19(1): 69-84
CrossRef Google scholar
[19]
KimY K, KimY J, KimY, 0, 0. Genetic algorithms for assembly line balancing with various objectives. Computers & Industrial Engineering, 1996, 30(3): 397-409
CrossRef Google scholar
[20]
SimariaA S, VilarinhoP M. A genetic algorithm based approach to the mixed model assembly line balancing problem of type II. Computers & Industrial Engineering, 2004, 47(4): 391-407
CrossRef Google scholar
[21]
MansouriS A. A multi-objective genetic algorithm for mixed-model sequencing on JIT assembly lines. European Journal of Operational Research, 2005, 167(3): 696-716
CrossRef Google scholar
[22]
KarabatiS, SayinS. Assembly line balancing in a mixed-model sequencing environment with synchronous transfers. European Journal of Operational Research, 2003, 149(2): 417-429
CrossRef Google scholar
[23]
KimY K, KimJ Y, KimY. A coevolutionary algorithm for balancing and sequencing in mixed model assembly lines. Applied Intelligence, 2000a, 13(3): 247-258
CrossRef Google scholar
[24]
KimY K, KimJ Y, KimY A. An endosymbiotic evolutionary algorithm for the integration of balancing and sequencing in mixed-model U-lines. European Journal of Operational Research, 2006, 168(3): 838-852
CrossRef Google scholar
[25]
MerengoC, NavaF, PozzettiA. Balancing and sequencing manual mixed-model assembly lines. International Journal of Production Research, 1999, 37(12): 2835-2860
CrossRef Google scholar
[26]
OzcanU, CerciogluH, GokcenH, TokluB. Balancing and sequencing of parallel mixed-model assembly lines. International Journal of Production Research, 2010, 48(17): 5089-5113
CrossRef Google scholar
[27]
HwangR, KatayamaH. Integrated procedure of balancing and sequencing for mixed-model assembly lines: a multi-objective evolutionary approach. International Journal of Production Research, 2010, 48(21): 6417-6441
CrossRef Google scholar
[28]
MosadeghH, ZandiehM, Fatemi GhomiS M T. Simultaneous solving of balancing and sequencing problems with station-dependent assembly times for mixed-model assembly lines. Applied Soft Computing, 2012, 12(4): 1359-1370
CrossRef Google scholar
[29]
BoysenN. VariantenflieXfertigung, Gabler, Wiesbaden, 2005.
[30]
PintoP A, DannenbringD G, KhumawalaB M. A branch and bound algorithm for assembly line balancing with paralleling. International Journal of Production Research, 1975, 13(2): 183-196
CrossRef Google scholar
[31]
MiltenburgJ, WijngaardJ. U-line Line Balancing Problem. Management Science, 1994, 40(10): 1378-1388
CrossRef Google scholar
[32]
MiltenburgJ. The effect of breakdowns on U-shaped production lines. International Journal of Production Research, 2000, 38(2): 353-364
CrossRef Google scholar
[33]
HiranoH. JIT Factory Revolution. Productivity Press, Cambridge, MA, 1988.
[34]
SekineK. One-Piece Flow. Productivity Press, Portland, OR, 1992.
[35]
MiltenburgJ, SparlingD. Optimal solution algorithms for the U-line balancing problem. Working Paper. McMaster University, Hamilton, 1995.
[36]
SparlingD, MiltenburgJ. The mixed-model U-line balancing problem. International Journal of Production Research, 1998, 36(2): 485-501
CrossRef Google scholar
[37]
ChandS, ZengT. A comparison of U-line and straightline performances under stochastic task times. Manufacturing and Service Operations Management, 2001, 3(2): 138-150
CrossRef Google scholar
[38]
GuerrieroF, MiltenburgJ. The stochastic U-line balancing problem. Naval Research Logistics, 2003, 50(1): 31-57
CrossRef Google scholar
[39]
BartholdiJ J. Balancing two-sided assembly lines: A case study. International Journal of Production Research, 1993, 31(10): 2447-2461
CrossRef Google scholar
[40]
LeeT O, KimY, KimY K. Two-sided assembly line balancing to maximize work relatedness and slackness. Computers & Industrial Engineering, 2001, 40(3): 273-292
CrossRef Google scholar
[41]
AgnetisA, CianciminoA, LucertiniM, PizzichellaM. Balancing flexible lines for car components assembly. International Journal of Production Research, 1995, 33(2): 333-350
CrossRef Google scholar
[42]
ChicaM, CordónÓ, DamasS. An advanced multiobjective genetic algorithm design for the time and space assembly line balancing problem. Computers & Industrial Engineering, 2011, 61(1): 103-117
CrossRef Google scholar
[43]
HamtaN, FatemiG S M T, JolaiF. Akbarpour ShiraziM. A hybrid PSO algorithm for a multi-objective assembly line balancing problem with flexible operation times, sequence-dependent setup times and learning effect. International Journal of Production Economics, 2013, 141(1): 99-111
CrossRef Google scholar
[44]
PonnambalamS G, AravindanP, Mogileeswar NaiduG. A multi-objective genetic algorithm for solving assembly line balancing problem. International Journal of Advanced Manufacturing Technology, 2000, 16(5): 341-352
CrossRef Google scholar
[45]
WeiN C, ChaoI M, 0. A solution procedure for type E-simple assembly line balancing problem. Computers & Industrial Engineering, 2011, 61(3): 824-830
CrossRef Google scholar
[46]
NourmohammadiA, ZandiehM. Assembly line balancing by a new multi-objective differential evolution algorithm based on TOPSIS. International Journal of Production Research, 2011, 49(10): 2833-2855
CrossRef Google scholar
[47]
CakirB, AltiparmakF, DengizB. Multi-objective optimization of a stochastic assembly line balancing: a hybrid simulated annealing algorithm. Computers & Industrial Engineering, 2011, 60(3): 376-384
CrossRef Google scholar
[48]
McmullenP R, TarasewichP. Multi-objective assembly line balancing via a modified ant colony optimization technique. International Journal of Production Research, 2006, 44(1): 27-42
CrossRef Google scholar
[49]
MalakootiB, KumarA. A knowledge-based system for solving multi-objective assembly line balancing problems. International Journal of Production Research, 1996, 34(9): 2533-2552
CrossRef Google scholar
[50]
AskinR G, ZhouM. A parallel station heuristic for the mixed-model production line balancing problem. International Journal of Production Research, 1997, 35(11): 3095-3105
CrossRef Google scholar
[51]
GokcenH, ErelE. A goal programming approach to mixed-model assembly line balancing problem. International Journal of Production Economics, 1997, 48(2): 177-185
CrossRef Google scholar
[52]
ChenR S, LuK Y, YuS C. A hybrid genetic algorithm approach on multi-objective of assembly planning problem. Engineering Applications of Artificial Intelligence, 2002, 15(5): 447-457
CrossRef Google scholar
[53]
VilarinhoP M, SimariaA S. A two-stage heuristic method for balancing mixed-model assembly lines with parallel workstations. International Journal of Production Research, 2002, 40(6): 1405-1420
CrossRef Google scholar
[54]
BukchinJ, RubinovitzJ. A weighted approach for assembly line design with station paralleling and equipment selection. IIE Transactions, 2003, 35(1): 73-85
CrossRef Google scholar
[55]
GamberiniR, GrassiA, RiminiB. A new multi-objective heuristic algorithm for solving the stochastic assembly line re-balancing problem. International Journal of Production Economics, 2006, 102(2): 226-243
CrossRef Google scholar
[56]
BaykasogluA. Multi-rule multi-objective simulated annealing algorithm for straight and U type assembly line balancing problems. Journal of Intelligent Manufacturing, 2006, 17(2): 217-232
CrossRef Google scholar
[57]
NearchouA C. Multi-objective balancing of assembly lines by population heuristics. International Journal of Production Research, 2008, 46(8): 2275-2297
CrossRef Google scholar
[58]
HwangR K, KatayamaH, GenM. U-shaped assembly line balancing problem with genetic algorithm. International Journal of Production Research, 2008, 46(16): 4637-4649
CrossRef Google scholar
[59]
DebK, PratapA, AgarwalS, MeyarivanT. A fast and elitist multi objective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197
CrossRef Google scholar
[60]
CarlosA. Coello Coello and Nareli Cruz Cortes. Solving Multi objective Optimization Problems using an Artificial Immune System. Genetic Programming and Evolvable Machines, 2005, 6: 163-190
CrossRef Google scholar
[61]
AgrawalS, DashoraY, TiwariM K, SonY J. Interactive particle swarm: a Pareto-adaptive metaheuristic to multiobjective optimization. IEEE Transactions on Systems, Man, and Cybernetics. Part A, Systems and Humans, 2008, 38(2): 258-277
CrossRef Google scholar
[62]
YenG G, LeongW F, 0. Dynamic multiple swarms in multiobjective particle swarm optimization. IEEE Transactions on Systems, Man, and Cybernetics. Part A, Systems and Humans, 2009, 39(4): 1013-1027
CrossRef Google scholar
[63]
WangY, DangC, LiH, HanL, WeiJ. A clustering multi-objective evolutionary algorithm based on orthogonal and uniform design, in: Proceeding of Congress on Evolutionary Computation. CEC’09, 2009, 2927-2933.
[64]
ZamudaA, BrestJ, BoskovicB, ZumerV. Differential evolution with self adaptation and local search for constrained multiobjective optimization, in: Proceeding of Congress on Evolutionary Computation. CEC’09, 2009, 192-202.
[65]
KukkonenS, LampinenJ. Performance assessment of generalized differential evolution with a given set of constrained multi-objective test problems, in: Proceeding of Congress on Evolutionary Computation. CEC’09, 2009, 1943-1950.
[66]
YangC, GaoJ, SunL. A multi-objective genetic algorithm for mixed-model assembly line rebalancing. Computers & Industrial Engineering, 2013, 65(1): 109-116
CrossRef Google scholar
[67]
JohnsonR V. A branch and bound algorithm for assembly line balancing problems with formulation irregularities. Management Science, 1983, 29(11): 1309-1324
CrossRef Google scholar
[68]
BoucherT O. Choice of assembly line design under task learning. International Journal of Production Research, 1978, 25(4): 513-524
CrossRef Google scholar
[69]
ChakravartyA K. Line balancing with task learning effects. IIE Transactions, 1988, 20(2): 186-193
CrossRef Google scholar
[70]
ShinD. An efficient heuristic for solving stochastic assembly line balancing problems. Computers & Industrial Engineering, 1990, 18(3): 285-295
CrossRef Google scholar
[71]
BuzacottJ A. Abandoning the moving assembly line: Models of human operators and job sequencing. International Journal of Production Research, 1990, 28(5): 821-839
CrossRef Google scholar
[72]
RobinsonL W, McClainJ O, ThomasL J. The good, the bad and the ugly: Quality on an assembly line. International Journal of Production Research, 1990, 28(5): 963-980
CrossRef Google scholar
[73]
HillierF S, SoK C. The effect of machine breakdowns and interstage storage on the performance of production line systems. International Journal of Production Research, 1991, 29(10): 2043-2055
CrossRef Google scholar
[74]
PikeR, MartinG E. The bowl phenomenon in unpaced lines. International Journal of Production Research, 1994, 32(3): 483-499
CrossRef Google scholar
[75]
McMullenP R, TarasewichP. Using ant techniques to solve the assembly line balancing problem. IIE Transactions, 2003, 35(7): 605-607
CrossRef Google scholar
[76]
ZhaoX, LiuJ, OhnK, . Modeling and analysis of a mixed-model assembly line with stochastic operation times. Naval Research Logistics, 2007, 54(6): 681-691
CrossRef Google scholar
[77]
HopN V. A heuristic solution for fuzzy mixed-model line balancing problem. European Journal of Operational Research, 2006, 168(3): 798-810
CrossRef Google scholar
[78]
XuW, XiaoT. Mixed model assembly line balancing problem with fuzzy operation times and drifting operations. In: Proceeding of Winter Simulation Conference (WSC 2008). Miami, FL, USA, 2008: 1752-1760.
[79]
MoodieC L, YoungH H. A heuristic method of assembly line balancing for assumptions of constant or variable work element times. Journal of Industrial Engineering, 1965, 16: 23-29
[80]
KaoE P C. Computational experience with a stochastic assembly line balancing algorithm. Computers & Operations Research, 1979, 6(2): 79-86
CrossRef Google scholar
[81]
SniedovichM. Analysis of a preference order assembly line problem. Management Science, 1981, 27(9): 1067-1080
CrossRef Google scholar
[82]
NkasuM M, LeungK H. A stochastic approach to assembly line balancing. International Journal of Production Research, 1995, 33(4): 975-991
CrossRef Google scholar
[83]
KouvelisP, YuG. Robust Discrete Optimization and Its Applications. Boston, MA, USA: Kluwer Academic Publishers, 1997.
[84]
XuW, XiaoT. Strategic Robust Mixed model assembly line balancing based on scenario planning. Tsinghua Science and Technology, 2011, 16(3): 308-314
CrossRef Google scholar
[85]
SalvesonM E. The assembly line balancing problem. Journal of Industrial Engineering, 1955, 6(3): 18-25

Acknowledgments

This work has been supported by MOST (the Ministry of Science & Technology of China) under the grants No.2012AA040909, 2012BAH08F04, and 2013AA040206, and by the National Natural Science Foundation of China (Grants No.51035001 and 71271156).

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg
AI Summary AI Mindmap
PDF(234 KB)

Accesses

Citations

Detail

Sections
Recommended

/