Machine configuration and workload balancing of modular placement machines in multi-product PCB assembly

ABSTRACT A popular gantry-type placement machine includes several interconnected, autonomously operating component placement modules and the machine was designed so as to able to use different kinds of placement heads and vacuum nozzles in the modules, which can be easily changed. Although this increases the flexibility of the production line, the reconfiguration phases of the modules may be unproductive and one should keep them to a minimum. In addition, the production times can be shortened by balancing the workloads of the machine modules. Here, a two-step optimisation method for the machine reconfiguration and workload balancing in the case of multiple Printed Circuit Borad (PCB) batches of different sizes and PCB types is presented. The objective is to minimise the total production time, and keep the machine configuration the same for all batches. The proposed algorithm is iterative and it applies integer programming for the workload balancing along with an evolutionary algorithm that searches for the best machine configuration. In experiments, for single PCB types the proposed algorithm obtained optimal or near optimal solutions. For multiple PCB types the solutions favour the PCB types that have a bigger production time due to greater batch sizes, but the total production time is still close to optimal.

[1]  Mika Johnsson,et al.  Estimating the operation time of flexible surface mount placement machines , 2012, Prod. Eng..

[2]  Katsuhiko Takahashi,et al.  An integrated allocation method for the PCB assembly line balancing problem with nozzle changes , 2012 .

[3]  Nick T. Thomopoulos,et al.  Mixed Model Line Balancing with Smoothed Station Assignments , 1970 .

[4]  Zbigniew Michalewicz,et al.  Genetic algorithms + data structures = evolution programs (3rd ed.) , 1996 .

[5]  Timo Knuutila,et al.  Reconfiguring flexible machine modules of a PCB assembly line , 2010, Prod. Eng..

[6]  Alexandre Dolgui,et al.  A taxonomy of line balancing problems and their solutionapproaches , 2013 .

[7]  Frits C. R. Spieksma,et al.  Production planning problems in printed circuit board assembly , 2002, Discret. Appl. Math..

[8]  Tapio Pahikkala,et al.  Estimating the production time of a PCB assembly job without solving the optimised machine control , 2015, Int. J. Comput. Integr. Manuf..

[9]  R. W. Sierenberg An Algorithm for the Line Balancing Problem , 1972 .

[10]  Zbigniew Michalewicz,et al.  Parameter Control in Evolutionary Algorithms , 2007, Parameter Setting in Evolutionary Algorithms.

[11]  Timo Knuutila,et al.  Modeling the machine configuration and line-balancing problem of a PCB assembly line with modular placement machines , 2011 .

[12]  Nick T. Thomopoulos,et al.  Line Balancing-Sequencing for Mixed-Model Assembly , 1967 .

[13]  Mika Johnsson,et al.  Grouping and sequencing PCB assembly jobs with minimum feeder setups , 2006 .

[14]  Yueming Hu,et al.  An MILP model and a hybrid evolutionary algorithm for integrated operation optimisation of multi-head surface mounting machines in PCB assembly , 2017, Int. J. Prod. Res..

[15]  Armin Scholl,et al.  State-of-the-art exact and heuristic solution procedures for simple assembly line balancing , 2006, Eur. J. Oper. Res..

[16]  François Soumis,et al.  Balancing printed circuit board assembly line systems , 1998 .

[17]  Graham Kendall,et al.  A survey of surface mount device placement machine optimisation: Machine classification , 2008, Eur. J. Oper. Res..

[18]  Armin Scholl,et al.  A survey on problems and methods in generalized assembly line balancing , 2006, Eur. J. Oper. Res..

[19]  Nils Boysen,et al.  Assembly line balancing: Which model to use when? , 2006 .

[20]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[21]  George L. Nemhauser,et al.  An Algorithm for the Line Balancing Problem , 1964 .

[22]  X. L. Travassos,et al.  Mixed assembly line rebalancing: A binary integer approach applied to real world problems in the automotive industry , 2012 .

[23]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

[24]  Ana S. Simaria,et al.  A genetic algorithm based approach to the mixed-model assembly line balancing problem of type II , 2004, Comput. Ind. Eng..

[25]  Ping Ji,et al.  Optimization of PCB component placements for the collect-and-place machines , 2008 .

[26]  Ilker Baybars,et al.  A survey of exact algorithms for the simple assembly line balancing , 1986 .

[27]  Cheng-Jian Lin,et al.  Optimization of printed circuit board component placement using an efficient hybrid genetic algorithm , 2016, Applied Intelligence.

[28]  Mika Johnsson,et al.  Scheduling algorithms for computer-aided line balancing in printed circuit board assembly , 1998 .

[29]  Mika Johnsson,et al.  Job Grouping in Surface Mounted Component Printing , 1999 .

[30]  O. E. Flippo,et al.  The assembly of printed circuit boards : a case with multiple machines and multiple board types , 1995 .

[31]  Yossi Bukchin,et al.  A branch-and-bound based solution approach for the mixed-model assembly line-balancing problem for minimizing stations and task duplication costs , 2006, Eur. J. Oper. Res..

[32]  Adil Baykasoglu,et al.  Hybridizing ant colony optimization via genetic algorithm for mixed-model assembly line balancing problem with sequence dependent setup times between tasks , 2013, Appl. Soft Comput..

[33]  Alexandre Dolgui,et al.  A bibliographic review of production line design and balancing under uncertainty , 2015 .