Locator Placement Optimization for Minimum Part Positioning Error During Machining Operation Using Genetic Algorithm

Fixture design is one of the main factors which affect the final product quality. Proper design of fixture plays an important role in ensuring the required tolerance of the product. Proper placement of locators is one of the prominent factors in fixture design. Locators are elastic: they deform unde...

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Published inInternational journal of precision engineering and manufacturing Vol. 22; no. 5; pp. 813 - 829
Main Authors Butt, Sajid Ullah, Arshad, Mamoona, Baqai, Aamer Ahmed, Saeed, Hasan Aftab, Din, Naveed Akmal, Khan, Rehan Ahmed
Format Journal Article
LanguageEnglish
Published Seoul Korean Society for Precision Engineering 01.05.2021
Springer Nature B.V
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Abstract Fixture design is one of the main factors which affect the final product quality. Proper design of fixture plays an important role in ensuring the required tolerance of the product. Proper placement of locators is one of the prominent factors in fixture design. Locators are elastic: they deform under clamping and machining forces causing rigid body displacement of the workpiece which in turn affects the part quality. In this article, a 3-2-1 type of fixturing system having elastic locators around a considerably rigid rectangular workpiece is considered. A genetic algorithm is proposed, which uses a fitness function that evaluates the positioning error of the workpiece under external forces and torque. Among several variables, 12 variables, which define the placement of locators, are chosen to be optimized while minimizing the positioning error of the workpiece at the point of action of machining force. The proposed algorithm optimizes the 12 interlinked variables, within the specified region, for machining force and torque at a single point. However, when the cutting tool moves to any other point on the workpiece, it is observed that either the workpiece loses its contact with any one of the locators or the positioning error increases by a large value. To overcome this issue, the proposed algorithm is further modified for placement optimization to cater for multi-point machining, and the isostatism of the workpiece is ensured by checking the magnitude and direction of displacement (of what?) at each point of workpiece-locator contact. Finally, the original and modified GA algorithms are explained through a case study where the single point optimized placement shows loss of contact when machining force is applied at other points. The placement optimized from the modified algorithm shows that the isostatism of the workpiece remains intact while all four positioning errors are converged towards the same value. The results obtained from the proposed and modified algorithm are verified using ANSYS simulation.
AbstractList Fixture design is one of the main factors which affect the final product quality. Proper design of fixture plays an important role in ensuring the required tolerance of the product. Proper placement of locators is one of the prominent factors in fixture design. Locators are elastic: they deform under clamping and machining forces causing rigid body displacement of the workpiece which in turn affects the part quality. In this article, a 3-2-1 type of fixturing system having elastic locators around a considerably rigid rectangular workpiece is considered. A genetic algorithm is proposed, which uses a fitness function that evaluates the positioning error of the workpiece under external forces and torque. Among several variables, 12 variables, which define the placement of locators, are chosen to be optimized while minimizing the positioning error of the workpiece at the point of action of machining force. The proposed algorithm optimizes the 12 interlinked variables, within the specified region, for machining force and torque at a single point. However, when the cutting tool moves to any other point on the workpiece, it is observed that either the workpiece loses its contact with any one of the locators or the positioning error increases by a large value. To overcome this issue, the proposed algorithm is further modified for placement optimization to cater for multi-point machining, and the isostatism of the workpiece is ensured by checking the magnitude and direction of displacement (of what?) at each point of workpiece-locator contact. Finally, the original and modified GA algorithms are explained through a case study where the single point optimized placement shows loss of contact when machining force is applied at other points. The placement optimized from the modified algorithm shows that the isostatism of the workpiece remains intact while all four positioning errors are converged towards the same value. The results obtained from the proposed and modified algorithm are verified using ANSYS simulation.
Author Saeed, Hasan Aftab
Arshad, Mamoona
Butt, Sajid Ullah
Khan, Rehan Ahmed
Baqai, Aamer Ahmed
Din, Naveed Akmal
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CitedBy_id crossref_primary_10_1080_0305215X_2023_2258067
crossref_primary_10_1007_s00170_022_10061_1
crossref_primary_10_1016_j_jii_2023_100518
crossref_primary_10_3390_app13074395
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Issue 5
Keywords Locator placement
Multivariable optimization
Genetic algorithm
Fixtures
Part positioning error
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Snippet Fixture design is one of the main factors which affect the final product quality. Proper design of fixture plays an important role in ensuring the required...
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SubjectTerms CAD
Computer aided design
Cutting tools
Design factors
Elastic deformation
Engineering
Errors
Genetic algorithms
Industrial and Production Engineering
Machining
Materials Science
Optimization
Placement
Positioning devices (machinery)
Regular Paper
Rigid structures
Torque
Workpieces
Title Locator Placement Optimization for Minimum Part Positioning Error During Machining Operation Using Genetic Algorithm
URI https://link.springer.com/article/10.1007/s12541-021-00500-6
https://www.proquest.com/docview/2515145730
Volume 22
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