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An improved ant colony optimization approach for optimization of process planning.

Wang J, Fan X, Ding H - ScientificWorldJournal (2014)

Bottom Line: In this paper, process planning problem is described based on a weighted graph, and an ant colony optimization (ACO) approach is improved to deal with it effectively.A case has been carried out to study the influence of various parameters of ACO on the system performance.Extensive comparative experiments have been carried out to validate the feasibility and efficiency of the proposed approach.

View Article: PubMed Central - PubMed

Affiliation: School of Energy, Power and Mechanical Engineering, North China Electric Power University, Baoding 071003, China.

ABSTRACT
Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environments (CIMs). In this paper, process planning problem is described based on a weighted graph, and an ant colony optimization (ACO) approach is improved to deal with it effectively. The weighted graph consists of nodes, directed arcs, and undirected arcs, which denote operations, precedence constraints among operation, and the possible visited path among operations, respectively. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPCs). A pheromone updating strategy proposed in this paper is incorporated in the standard ACO, which includes Global Update Rule and Local Update Rule. A simple method by controlling the repeated number of the same process plans is designed to avoid the local convergence. A case has been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been carried out to validate the feasibility and efficiency of the proposed approach.

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Related in: MedlinePlus

A sample part with 14 features and 20 operations: Part 2.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig4: A sample part with 14 features and 20 operations: Part 2.

Mentions: Two prismatic parts are used for the case experiments. The first prismatic part (Part 1) used by Zhang et al. [5] is illustrated in Figure 3. It consists of 14 STEP-defined manufacturing features and 14 machining operations. The machining information and precedence constraints are given in Tables 3 and 4. The second prismatic part (Part 2) used by Li et al. [13] is illustrated in Figure 4. The machining information and precedence constraints are given in Tables 5 and 6.


An improved ant colony optimization approach for optimization of process planning.

Wang J, Fan X, Ding H - ScientificWorldJournal (2014)

A sample part with 14 features and 20 operations: Part 2.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4109124&req=5

fig4: A sample part with 14 features and 20 operations: Part 2.
Mentions: Two prismatic parts are used for the case experiments. The first prismatic part (Part 1) used by Zhang et al. [5] is illustrated in Figure 3. It consists of 14 STEP-defined manufacturing features and 14 machining operations. The machining information and precedence constraints are given in Tables 3 and 4. The second prismatic part (Part 2) used by Li et al. [13] is illustrated in Figure 4. The machining information and precedence constraints are given in Tables 5 and 6.

Bottom Line: In this paper, process planning problem is described based on a weighted graph, and an ant colony optimization (ACO) approach is improved to deal with it effectively.A case has been carried out to study the influence of various parameters of ACO on the system performance.Extensive comparative experiments have been carried out to validate the feasibility and efficiency of the proposed approach.

View Article: PubMed Central - PubMed

Affiliation: School of Energy, Power and Mechanical Engineering, North China Electric Power University, Baoding 071003, China.

ABSTRACT
Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environments (CIMs). In this paper, process planning problem is described based on a weighted graph, and an ant colony optimization (ACO) approach is improved to deal with it effectively. The weighted graph consists of nodes, directed arcs, and undirected arcs, which denote operations, precedence constraints among operation, and the possible visited path among operations, respectively. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPCs). A pheromone updating strategy proposed in this paper is incorporated in the standard ACO, which includes Global Update Rule and Local Update Rule. A simple method by controlling the repeated number of the same process plans is designed to avoid the local convergence. A case has been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been carried out to validate the feasibility and efficiency of the proposed approach.

Show MeSH
Related in: MedlinePlus