scholarly journals An Improved Ant Colony Optimization Approach for Optimization of Process Planning

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
JinFeng Wang ◽  
XiaoLiang Fan ◽  
Haimin Ding
Keyword(s):  
Ant Colony Optimization ◽  
Process Planning ◽  
Weighted Graph ◽  
Ant Colony ◽  
Production Costs ◽  
Planning Problem ◽  
Total Production ◽  
Simple Method ◽  
Computer Aided Process Planning ◽  
Computer Aided

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.

An Approach of Process Planning Using Ant Colony Optimization Algorithm

2014 ◽  
Vol 978 ◽  
pp. 209-212
Author(s):  
Jin Feng Wang ◽  
Kai Yu Chu ◽  
Qing Yu Wang
Keyword(s):  
Ant Colony Optimization ◽  
Directed Graph ◽  
Process Planning ◽  
Ant Colony ◽  
Production Costs ◽  
Planning Problem ◽  
Total Production ◽  
Ant Colony Optimization Algorithm ◽  
Process Plan ◽  
Weighted Directed Graph

An ant colony optimization (ACO) approach has been developed to deal with process planning problem to achieve the optimal process plan. A disjunctive weighted directed graph is conducted to describe the operations, precedence constraints between operations, and the possible visited path between operation nodes. A represent of process plan is described based on the disjunctive weighted directed graph. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing Total Production Costs (TPC). Extensive comparative experiments have been carried out to demonstrate the feasibility and efficiency of the proposed approach.

scholarly journals A Graph-Based Ant Colony Optimization Approach for Process Planning

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
JinFeng Wang ◽  
XiaoLiang Fan ◽  
Shuting Wan
Keyword(s):  
Ant Colony Optimization ◽  
Directed Graph ◽  
Process Planning ◽  
Ant Colony ◽  
Production Costs ◽  
Planning Problem ◽  
Optimization Approach ◽  
Total Production ◽  
Process Plan ◽  
Weighted Directed Graph

The complex process planning problem is modeled as a combinatorial optimization problem with constraints in this paper. An ant colony optimization (ACO) approach has been developed to deal with process planning problem by simultaneously considering activities such as sequencing operations, selecting manufacturing resources, and determining setup plans to achieve the optimal process plan. A weighted directed graph is conducted to describe the operations, precedence constraints between operations, and the possible visited path between operation nodes. A representation of process plan is described based on the weighted directed graph. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPC). Two cases have been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been conducted to demonstrate the feasibility and efficiency of the proposed approach.

An ant colony approach to operation sequencing optimization in process planning

2016 ◽  
Vol 231 (3) ◽  
pp. 470-489 ◽  
Author(s):  
Quanwei Hu ◽  
Lihong Qiao ◽  
Guanwei Peng
Keyword(s):  
Ant Colony Optimization ◽  
Process Planning ◽  
Optimization Algorithm ◽  
Ant Colony ◽  
Local Optimum ◽  
Ant Colony Optimization Algorithm ◽  
Operation Sequencing ◽  
Computer Aided Process Planning ◽  
Process Plans ◽  
Computer Aided

Computer-aided process planning is an important component for linking design and manufacturing in computer-aided design/computer-aided process planning/computer-aided manufacturing integrated manufacturing systems. Operation sequencing in computer-aided process planning is one of the most essential tasks. To solve the problem and acquire optimal process plans, operation sequencing is modeled as a combinatorial optimization problem with various constraints, and a novel modified ant colony optimization algorithm is developed to solve it. To ensure the feasibility of process plans, constrained relationships considered among operations are classified into two categories called precedence constraint relationships and clustering constraint relationships. Operation precedence graph based on constrained relationships is formed to get visual representation. To ensure good manufacturing economy, in the mathematical model for optimization, total weighted production cost or weighted resource transformation time related to machine changes, setup changes, tool changes, machines and tools is utilized as the evaluation criterion. To avoid local optimum and enhance global search ability, adaptive updating method and local search mechanism are embedded into the optimization algorithm. Case studies of three parts are carried out to demonstrate the feasibility and robustness of the modified ant colony optimization algorithm, and some comparisons between the modified ant colony optimization algorithm and previous genetic algorithm, simulated annealing algorithm, tabu search and particle swarm optimization algorithm are discussed. The results show that the modified ant colony optimization algorithm performs well in the operation sequencing problem.

scholarly journals A Genetic Crow Search Algorithm for Optimization of Operation Sequencing in Process Planning

2021 ◽  
Vol 11 (5) ◽  
pp. 1981
Author(s):  
Mica Djurdjev ◽  
Robert Cep ◽  
Dejan Lukic ◽  
Aco Antic ◽  
Branislav Popovic ◽  
...  
Keyword(s):  
Process Planning ◽  
Computer Aided Design ◽  
Search Algorithm ◽  
Combinatorial Problem ◽  
Optimization Criterion ◽  
Total Production ◽  
Operation Sequencing ◽  
Computer Aided Process Planning ◽  
Sequencing Problem ◽  
Computer Aided

Computer-aided process planning represents the main link between computer-aided design and computer-aided manufacturing. One of the crucial tasks in computer-aided process planning is an operation sequencing problem. In order to find the optimal process plan, operation sequencing problem is formulated as an NP hard combinatorial problem. To solve this problem, a novel genetic crow search approach (GCSA) is proposed in this paper. The traditional CSA is improved by employing genetic strategies such as tournament selection, three-string crossover, shift and resource mutation. Moreover, adaptive crossover and mutation probability coefficients were introduced to improve local and global search abilities of the GCSA. Operation precedence graph is adopted to represent precedence relationships among features and vector representation is used to manipulate the data in the Matlab environment. A new nearest mechanism strategy is added to ensure that elements of machines, tools and tool approach direction (TAD) vectors are integer values. Repair strategy to handle precedence constraints is adopted after initialization and shift mutation steps. Minimization of total production cost is used as the optimization criterion to evaluate process plans. To verify the performance of the GCSA, two case studies with different dimensions are carried out and comparisons with traditional and some modern algorithms from the literature are discussed. The results show that the GCSA performs well for operation sequencing problem in computer-aided process planning.

Machining Feature-Based CAD/CAPP for STEP-NC

2014 ◽  
Vol 598 ◽  
pp. 591-594 ◽  
Author(s):  
Li Yan Zhang
Keyword(s):  
Process Planning ◽  
Manufacturing Process ◽  
Data Transfer ◽  
Operation Planning ◽  
Computer Aided Process Planning ◽  
Machining Feature ◽  
Computer Aided ◽  
Cad Cam ◽  
Feature Based ◽  
Cam Systems

ISO 14649, known as STEP-NC, is new model of data transfer between CAD/CAM systems and CNC machines. In this paper, the modeling based on machining feature is proposed. The machining feature comes from the manufacturing process considering the restriction of machining technology and machining resource. Then the framework for computer aided process planning is presented, where the algorithms of operation planning is studied. The practical example has been provided and results indicate that machining feature based model can integrate with CAPP and STEP-NC seamlessly.

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