Operations planning for collect-and-place machines in PCB assembly

Grunow, Martin; Günther, Hans‐Otto; Schleusener, M.; Yılmaz, İhsan

doi:10.1016/j.cie.2004.09.007

Cited by 60 publications

(58 citation statements)

References 27 publications

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“…Several researchers (Altinkemer et al 2000;Grunow, Gu¨nther, Schleusener and Yilmaz 2004) viewed the problem as a vehicle-routing problem and Leipa¨la¨and Nevalainen (1989) treated it as a three-dimensional asymmetric TSP. Nevertheless, many researchers (Shih et al 1996;Yeo, Low and Yong 1996;Magyar et al 1999;Ho and Ji 2003, 2004, 2006Sun et al 2005) solved the pickand-place sequencing problem as a unique problem since the problem relies heavily on the machine characteristics.…”

Section: 3mentioning

confidence: 99%

“…They observed that empty slots between feeders help maximise simultaneous pickups; the feeders are close to each other so as to minimise the pickup travelling time; and the feeders are located close to the centre position of each feeder carrier such that the robot travelling time between the feeder carrier and the PCB point is minimised. Grunow et al (2004) arranged component feeders to slots based on the strength of the neighbourhood relations. Next, they improved the feeder setup using a random descent two-opt swapping procedure.…”

Section: Feeder Setup Optimisationmentioning

confidence: 99%

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The optimisation of the single surface mount device placement machine in printed circuit board assembly: a survey

Ayob

Kendall

2009

International Journal of Systems Science

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This article surveys research on the single surface mount device (SMD) placement machine optimisation problem. We classify the optimisation problem into five sub-problems: feeder setup, component placement sequencing, nozzle optimisation, component retrieval plan and motion control; and analyse issues relevant to each of these. One of the aims of this article is to provide guidance to other researchers and gain a deeper understanding of the various optimisation issues that arise in this domain. This could lead to the design of improved heuristics, which are more appropriate to the real-world scheduling problem of the SMD placement machine.

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Section: 3mentioning

confidence: 99%

Section: Feeder Setup Optimisationmentioning

confidence: 99%

The optimisation of the single surface mount device placement machine in printed circuit board assembly: a survey

Ayob

Kendall

2009

International Journal of Systems Science

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“…In previous researches (Ho and Ji, 2010;Chyu and Chang, 2008;Ho et al, 2007;Kulak et al, 2007;Grunow et al, 2004;Duman and Or, 2007), 2-opt local search and iterated swap procedures (ISP) have been adopted to improve a solution for feeder assignment or component sequencing problem. In our paper, several neighbourhoods are defined to develop efficient local searches.…”

Section: ) Local Search Adopted In Tsmentioning

confidence: 99%

“…The two problems are often viewed quadratic assignment problem (QAP) and travelling salesman problem (TSP) or vehicle routing problem (VRP) (Ball andMagazine 1988, McGinnis et al 1992;Or and Demirkol 1995, Jeevan et al, 2002, Grunow et al 2004. The most popular constructive heuristic for the two sub-problems is nearest neighbour heuristic (Grunow et al, 2004, Pyottiala et al, 2013.…”

Section: Introductionmentioning

confidence: 99%

An MILP model and a hybrid evolutionary algorithm for integrated operation optimisation of multi-head surface mounting machines in PCB assembly

Luo

Liu

2016

International Journal of Production Research

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Abstract:This paper focuses on an operation optimization problem for a class of multi-head surface mounting machines in printed circuit board assembly lines. The problem involves five interrelated sub-problems: assigning nozzle types as well as components to heads, assigning feeders to slots and determining component pick-up and placement sequences. According to the depth of making decisions, the sub-problems are first classified into two layers. Based on the classification, a two-stage mixed integer linear programming (MILP) is developed to describe it and a two-stage problem-solving frame with a hybrid evolutionary algorithm (HEA) is proposed. In the first stage, a constructive heuristic is developed to determine the set of nozzle types assigned to each head and the total number of assembly cycles; in the second stage, constructive heuristics, an evolutionary algorithm with two evolutionary operators and a tabu search (TS) with multiple neighbourhoods are combined to solve all the sub-problems simultaneously, where the results obtained in the first stage are taken as constraints. Computational experiments show that the HEA can obtain good near-optimal solutions for small-size instances when compared with an optimal solver, Cplex, and can provide better results when compared with a TS and an EA for actual instances.

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“…Some researchers (see, e.g., [5]) have tackled the subproblems independently but also have some researchers (see, e.g., Ho and Ji [6]) preferred to solve these subproblems in an integrated way. The literature is rich with work that has tackled this subject, especially investigating how to improve the efficiency of SMM [7,8]. The technological characteristics of the SMM can also influence the nature of some of the subproblems to be solved and the formulation of the associated models [9].…”

Section: Introductionmentioning

confidence: 99%

Optimizing the Operation Sequence of a Multihead Surface Mounting Machine Using a Discrete Particle Swarm Optimization Algorithm

Chen

Lin

2008

Journal of Artificial Evolution and Applications

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The optimization of the nozzle selection, for sequencing component pick and place operations, is very important to the efficiency of multihead surface mounting machine (SMM). The nozzle change operation, that is, choosing the best nozzle head relative pair that is most effective for picking and placing components onto the printed circuit board (PCB), significantly adds to the overall assembly time. In this paper, as a practical application, we focus on a discrete particle swarm optimization (DPSO) algorithm for multihead SMM which is used to minimize the number of nozzle change operations and pick and place operations simultaneously. To evaluate the performance of the proposed algorithm, we test it on assembly tasks of PCBs through simulations. The results of computer experiments show that this DPSO algorithm was superior to the standard PSO algorithm.

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Operations planning for collect-and-place machines in PCB assembly

Cited by 60 publications

References 27 publications

The optimisation of the single surface mount device placement machine in printed circuit board assembly: a survey

The optimisation of the single surface mount device placement machine in printed circuit board assembly: a survey

An MILP model and a hybrid evolutionary algorithm for integrated operation optimisation of multi-head surface mounting machines in PCB assembly

Optimizing the Operation Sequence of a Multihead Surface Mounting Machine Using a Discrete Particle Swarm Optimization Algorithm

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