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Maroua Ghali, Sami Elghali and Nizar Aifaoui
The purpose of this paper is to establish a tolerance optimization method based on manufacturing difficulty computation using the genetic algorithm (GA) method. This…
The purpose of this paper is to establish a tolerance optimization method based on manufacturing difficulty computation using the genetic algorithm (GA) method. This proposal is among the authors’ perspectives of accomplished previous research work to cooperative optimal tolerance allocation approach for concurrent engineering area.
This study introduces the proposed GA modeling. The objective function of the proposed GA is to minimize total cost constrained by the equation of functional requirements tolerances considering difficulty coefficients. The manufacturing difficulty computation is based on tools for the study and analysis of reliability of the design or the process, as the failure mode, effects and criticality analysis (FMECA) and Ishikawa diagram.
The proposed approach, based on difficulty coefficient computation and GA optimization method [genetic algorithm optimization using difficulty coefficient computation (GADCC)], has been applied to mechanical assembly taken from the literature and compared to previous methods regarding tolerance values and computed total cost. The total cost is the summation of manufacturing cost and quality loss. The proposed approach is economic and efficient that leads to facilitate the manufacturing of difficult dimensions by increasing their tolerances and reducing the rate of defect parts of the assembly.
The originality of this new optimal tolerance allocation method is to make a marriage between GA and manufacturing difficulty. The computation of part dimensions difficulty is based on incorporating FMECA tool and Ishikawa diagram This comparative study highlights the benefits of the proposed GADCC optimization method. The results lead to obtain optimal tolerances that minimize the total cost and respect the functional, quality and manufacturing requirements.
Akram Bedeoui, Riadh Ben Hadj, Moncef Hammadi and Nizar Aifaoui
During the design of a new product, the generation of assembly sequences plans (ASPs) has become one of the most important problems taken into account by researchers. In…
During the design of a new product, the generation of assembly sequences plans (ASPs) has become one of the most important problems taken into account by researchers. In fact, a good mounting order allows the time decrease of the assembly process which leads to the reduction of production costs. In this context, researchers developed several methods to generate and optimize ASP based on various criteria. Although this paper aims to improve the quality of ASP it is necessary to increase the number of criteria which must be taken into account when generating ASPs.
In this paper, an ASP generation approach, which is based on three main algorithms, is proposed. The first one generates a set of assembly sequences based on stability criteria. The obtained results are treated by the second algorithm which is based on assembly tools (ATs) workspace criterion. An illustrative example is used to explain the different steps of this proposed approach. Moreover, a comparative study is done to highlight its advantages.
The proposed algorithm verifies, for each assembly sequence, the minimal required workspace of used AT and eliminates the ASPs non-respecting this criterion. Finally, the remaining assembly sequences are treated by the third algorithm to reduce the AT change during the mounting operation.
The proposed approach introduces the concept of AT workspace to simulate and select ASPs that respect this criterion. The dynamic interference process allows the eventual collision detection between tool and component and avoids it. The proposed approach reduces the AT change during the mounting operations.