Optimization of process plans using a constraint-based tabu search approach

Abstract

A computer-aided process planning system should ideally generate and optimize process plans to ensure the application of good manufacturing practices and maintain the consistency of the desired functional specifications of a part during its production processes. Crucial processes, such as selecting machining resources, determining set-up plans and sequencing operations of a part should be considered simultaneously to achieve global optimal solutions. In this paper, these processes are integrated and modelled as a constraint-based optimization problem, and a tabu search-based approach is proposed to solve it effectively. In the optimization model, costs of the utilized machines and cutting tools, machine changes, tool changes, set-ups and departure from good manufacturing practices (penalty function) are the optimization evaluation criteria. Precedence constraints from the geometric and manufacturing interactions between features and their related operations in a part are defined and classified according to their effects on the plan feasibility and processing quality. A hybrid constraint-handling method is developed and embedded in the optimization algorithm to conduct the search efficiently in a large-size constraint-based space. Case studies, which are used for comparing this approach with the genetic algorithm and simulated annealing approaches, and the proposed constraint-handling method and other constraint methods, are discussed to highlight the performance of this approach in terms of the solution quality and computational efficiency of the algorithm.

A genetic algorithm for operation sequencing in CAPP using edge selection based encoding strategy

“…However, T 6 is unavailable for operation 6, whose candidate cutting tools are T 7 and T 8 . The features, operations, and manufacturing resources information could be found in Table 5 of this paper, Table 4 of Li et al (2002a), Table 11 of Li et al (2004) and Table 5 of Huang et al (2012). Actually, the reported best result under condition 1 is 2535 according to the benchmarks.…”

“…Under condition 1, the best result of benchmarks [2527 by hybrid GA and SA in Li et al (2002a), 2527 by TS algorithm, 2535 by SA and 2667 by standard GA in Li et al (2004), 2527 by hybrid GA in Huang et al (2012), 2540 by Liu et al (2013)] is 2527. The best benchmark result was generated when operation 6 used cutting tool T 6 .…”

A hybrid optimization approach for sustainable process planning and scheduling

“…It should be pointed out that some assumptions [29,30] that are commonly used in most of the previous research works regarding scheduling were still taken for this study. The assumptions include:…”

Optimization of Operation Sequencing in CAPP for Cylindrical Part Using Super Hybrid Genetic Algorithm-Expert System (S-Genex) Approach

“…The various output parameters and optimal solutions obtained by S 1 100 100 100 100 2 11 -0 100 1 100 100 100 3 11 100 -100 1 100 1 1 4 100 100 100 -100 100 100 100 5 11 1 100 100 -0 100 100 6 11 1 100 100 100 -100 100 7 11 100 100 100 100 100 -100 8 11 1 100 100 100 100 1 -Bhaskara Reddy [6] generated sequences in the initial population which violates the precedence relations even though the final reported optimal solution is a feasible one for the same case study. As the total number of 10, even a search technique is not essential to find the optimal solution.…”

“…Li et al [11] researched the utilization of compelled based tabu scan approach for streamlining of process plans. Advance it was examined by Krishna and Rao [12] utilizing Ant colony algorithm (ACA) and found that the computational time has significantly decreased.…”