A new optimization approach for nozzle selection and component allocation in multi-head beam-type SMD placement machines

S.A. Torabi, M. Hamedi, J. Ashayeri

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This paper addresses a highly challenging scheduling problem faced in multi-head beam-type surface mounting devices (SMD) machines. An integrated mathematical model is formulated aiming to balance workloads over multiple heads as well as improving the traveling speed of the robotic arm by incorporating the appropriateness factors in the model to evaluate the compatibility of component-nozzle pairs. The proposed model is a bi-objective mixed integer nonlinear programming one, which is first converted into a linearized model and then directly solved by using the augmented epsilon constraint method for small problem instances. As the model is turned out to be NP-hard, we also develop a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to solve the model for medium and large-sized problem instances. The parameters of the proposed MOPSO are tuned by using the Taguchi Method and corresponding numerical results are provided.
Original languageEnglish
Pages (from-to)700-714
JournalJournal of Manufacturing Systems
Volume32
Issue number4
DOIs
Publication statusPublished - 2013

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Mountings
Nozzles
Particle swarm optimization (PSO)
Robotic arms
Taguchi methods
Nonlinear programming
Scheduling
Mathematical models

Cite this

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title = "A new optimization approach for nozzle selection and component allocation in multi-head beam-type SMD placement machines",
abstract = "This paper addresses a highly challenging scheduling problem faced in multi-head beam-type surface mounting devices (SMD) machines. An integrated mathematical model is formulated aiming to balance workloads over multiple heads as well as improving the traveling speed of the robotic arm by incorporating the appropriateness factors in the model to evaluate the compatibility of component-nozzle pairs. The proposed model is a bi-objective mixed integer nonlinear programming one, which is first converted into a linearized model and then directly solved by using the augmented epsilon constraint method for small problem instances. As the model is turned out to be NP-hard, we also develop a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to solve the model for medium and large-sized problem instances. The parameters of the proposed MOPSO are tuned by using the Taguchi Method and corresponding numerical results are provided.",
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A new optimization approach for nozzle selection and component allocation in multi-head beam-type SMD placement machines. / Torabi, S.A.; Hamedi, M.; Ashayeri, J.

In: Journal of Manufacturing Systems, Vol. 32, No. 4, 2013, p. 700-714.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - A new optimization approach for nozzle selection and component allocation in multi-head beam-type SMD placement machines

AU - Torabi, S.A.

AU - Hamedi, M.

AU - Ashayeri, J.

PY - 2013

Y1 - 2013

N2 - This paper addresses a highly challenging scheduling problem faced in multi-head beam-type surface mounting devices (SMD) machines. An integrated mathematical model is formulated aiming to balance workloads over multiple heads as well as improving the traveling speed of the robotic arm by incorporating the appropriateness factors in the model to evaluate the compatibility of component-nozzle pairs. The proposed model is a bi-objective mixed integer nonlinear programming one, which is first converted into a linearized model and then directly solved by using the augmented epsilon constraint method for small problem instances. As the model is turned out to be NP-hard, we also develop a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to solve the model for medium and large-sized problem instances. The parameters of the proposed MOPSO are tuned by using the Taguchi Method and corresponding numerical results are provided.

AB - This paper addresses a highly challenging scheduling problem faced in multi-head beam-type surface mounting devices (SMD) machines. An integrated mathematical model is formulated aiming to balance workloads over multiple heads as well as improving the traveling speed of the robotic arm by incorporating the appropriateness factors in the model to evaluate the compatibility of component-nozzle pairs. The proposed model is a bi-objective mixed integer nonlinear programming one, which is first converted into a linearized model and then directly solved by using the augmented epsilon constraint method for small problem instances. As the model is turned out to be NP-hard, we also develop a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to solve the model for medium and large-sized problem instances. The parameters of the proposed MOPSO are tuned by using the Taguchi Method and corresponding numerical results are provided.

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