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An optimization approach for setup planning and operation sequencing with tolerance constraints

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Abstract

Setup planning and operation sequencing are two interrelated problems in computer-aided process planning. However, they are addressed by most traditional methods separately, in which setup planning focuses on precision assurance, while operation sequencing is devoted to cost reduction. One drawback of these methods is that they cannot balance the requirements between precision and cost. In this paper, a constrained optimization approach is proposed to address the setup planning and operation sequencing problems in a combined way. With an objective to minimize the manufacturing cost, the optimization model includes various constraints, especially the precision constraints on setup error, tool error, and stacking error. A modified particle swarm optimization algorithm is developed to search for the optimal solution. The case study shows that the proposed method has relatively more flexibility in guaranteeing the precision and decreasing the cost.

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Abbreviations

f i :

The i-th operation of a process

TAD i :

Tool approaching direction of the i-th operation

MT i :

Machining tool of the i-th operation

CT i :

Cutting tool of the i-th operation

DF i :

Datum face operation of the i-th operation

CF i :

Clamping face operation of the i-th operation

PS :

Process solution matrix

n :

Number of the operations in a process

m :

Number of the setups in a process

S t :

The t-th setup of a process

s :

Total setup solution of a process

ΔE s :

Setup error of an operation

ΔE D :

Stacking error of an operation

ΔE T :

Tool error of an operation

T :

Tolerance matrix between the operations in a process

P :

Precedence matrix for the operations in a process

A :

TAD matrix for the operations in a process

D k :

Vector of selected datum face operation for the k-th setup

C k :

Vector of selected clamping face operation for the k-th setup

N :

Number of the particles in the optimization algorithm

N i :

Iteration numbers of the Particle Swarm Optimization algorithm

M :

Number of the particles that are selected as global optima in the update step

P e :

Probability in which the exchange operator is executed in the new particle generation

P m :

Probability in which the mutation operator is executed in the new particle generation

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Funding

This project is supported by National Natural Science Foundation of China (Grant Nos. 51475186 and 51775202).

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Authors and Affiliations

  1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, People’s Republic of China

    Wenbo Wu, Zhengdong Huang, Kangxiang Wu & Yongfu Chen

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  1. Wenbo Wu
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  2. Zhengdong Huang
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  3. Kangxiang Wu
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  4. Yongfu Chen
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Correspondence to Yongfu Chen.

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Wu, W., Huang, Z., Wu, K. et al. An optimization approach for setup planning and operation sequencing with tolerance constraints. Int J Adv Manuf Technol 106, 4965–4985 (2020). https://doi.org/10.1007/s00170-019-04791-y

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