Concurrent process tolerance design based on minimum product manufacturing cost and quality loss

Huang, M. F.; Zhong, Yisheng; Xu, Zhijie

doi:10.1007/s00170-003-1911-8

Cited by 70 publications

(40 citation statements)

References 18 publications

(37 reference statements)

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“…Lu et al [20] suggest an approach to attain least manufacturing cost and proper assimilability product to obtain an optimal solution. Cheng and Maghsoodloo [21], Wu et al [22] and Huang et al [23] used nonlinear programming method to design the tolerance. Cheng and Tsai [24,25] solved allocation of statistical tolerances with exponential cost function and obtained closed-form solution of optimal tolerances.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal Tolerance Allocation in a Complex Assembly Using Evolutionary Algorithms

Kumar¹,

Padmanaban²,

Balamurugan³

2016

Int. j. simul. model.

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Tolerance design is a vital factor which influences product and process development. Further, it determines the manufacturing cost, the functionality and quality of a product. It is evident that optimal tolerance normally leads to produce ample parts, better operation of mechanical systems and excellent assembling. In contrast, tight tolerance leads to increase in manufacturing cost for an assembly. An ideal relationship exists among production cost and operation, while determining the optimum tolerance. Based on this relation a new approach by implementing the Non-traditional techniques: Genetic Algorithm (GA), Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and Differential Evolution (DE) for determining the optimum tolerance, zero percentage rejection and manufacturing cost considering the varying quality loss constants for an assembly namely overrunning clutch assembly, is discussed in this paper. From the result obtained, it is evident that, the proposed approach is best suitable for solving problems involving complex assemblies.

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Section: Literature Reviewmentioning

confidence: 99%

Optimal Tolerance Allocation in a Complex Assembly Using Evolutionary Algorithms

Kumar¹,

Padmanaban²,

Balamurugan³

2016

Int. j. simul. model.

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“…Huang [8] has presented a robust optimization method in a concurrent tolerance environment. This method can determine multiple correlated critical tolerances and directly allocate them to process tolerances by using component process plans.…”

Section: Literature Reviewmentioning

confidence: 99%

Calculation of Total Cost, Tolerance Based on Taguchiâ€™s, AsymmetricQuality Loss Function Approach

Kumar¹,

Alagumurthi²,

Ramesh³

2009

American J. of Engineering and Applied Sciences

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Problem statement: Current world market force the manufacturing sectors to develop high quality product and process design with minimum possible cost. About 80% of problems in production units may be attributed to 20% of design tolerance causes. While design typically represents the smallest actual cost elements in products (around 5%), it leverages the largest cost influence (around 70%). So design engineers continuously stumble upon problem of design for high quality performance with lower cost. Objectives of this study where to: (i) simultaneous selection of design and manufacturing tolerance (ii) minimization of total cost (sum of the manufacturing cost and Taguchi's asymmetric quality cost) (iii) minimum cost and its machining tolerance. Approach: Rotor key base assembly was considered as case study to optimize the minimization of assembly total cost and machining tolerance. New global nonlinear optimization techniques called pattern search algorithm had been implemented to find optimal tolerance allocation and total cost. Results: In this study minimum cost arrived was 45.15 Cr and its corresponding tolerances for machining process turning, drilling, face milling, face milling and drilling where 0.063, 0.0508, 0.2127, 0.2127, 0.2540 mm respectively at worst case conditions. Conclusion: Results indicated that optimization by integer programming, sequential quadratic programming and exhaustive search, nonlinear programming, genetic algorithm, simulated annealing, fuzzy logic, number set theory and Monte Carlo simulation did not give much least total cost and also predicted that pattern search algorithm was robust method. Second the method, generally termed as concurrent tolerance synthesis was well suited for engineering environment, where high quality products with low total cost were designed and manufactured.

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“…Recently, Mustajib and Irianto [10] propossed an integrated model for tolerance allocation and selection process in multi-stage processes. Meanwhile, the importance of determining tolerances for multiple quality characteristics products has been demonstrated by Lee and Tang [11], Chou and Chen [12], Huang et al [13], and Peng et al [14]. Furthermore, many researches [15][16][17] extended this work on assembly products with multiple quality characteristics based on statistical approach.…”

Section: Introductionmentioning

confidence: 99%

“…manufacturing and quality costs. The development was carried out by enhancing on the model of previous study [8,9,[11][12][13][14] with respect to process capability and statistical approaches, also taking into account the quality loss cost is a function of tolerance as well as rework and scrap cost.…”

Section: Introductionmentioning

confidence: 99%

Concurrent Engineering of Tolerance Synthesis and Process Selection for Products With Multiple Quality Characteristcs Considering Process Capability

Mustajib¹

2012

MST

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The existences of variances that are very difficult to be removed from manufacturing processes provide significance of tolerance to the product quality characteristics target of customer functional requirement. Furthermore, quality loss incurred due to deviation of quality characteristics of the target with a specified tolerance. This article discusses the development of concurrent engineering optimization model of tolerance design and manufacturing process selection on product with multiple quality characteristics by minimizing total costs in the system, namely total manufacturing cost and quality loss cost as functions of tolerance, also rework and scrap costs. The considered multiple quality characteristics have interrelated tolerance chain. The formulation of proposed model is using mixed integer non linear programming as the method of solution finding. In order to validate of the model, this study presents a numerical example. It was found that optimal solution are achieved from proposed model in the numerical example. Abstrak Rekayasa Simultan Sintesis Toleransi dan Pemilihan Proses untuk Produk dengan Multi-karakteristik Kualitas yang Mempertimbangkan Kapabilitas Proses.Keberadaan variansi yang sangat sulit untuk dihilangkan dalam proses manufaktur memberikan peran penting adanya toleransi terhadap target karakteristik kualitas produk yang menjadi kebutuhan fungsional bagi konsumen. Selanjutnya timbul kerugian kualitas yang disebabkan oleh penyimpangan karakteristik kualitas dari target dengan toleransi yang ditetapkan. Makalah ini membahas pengembangan model optimisasi rekayasa simultan desain toleransi dan pemilihan proses manufaktur pada produk dengan multi karakteristik kualitas untuk meminimasi total ongkos dalam sistem, yaitu total ongkos manufaktur dan ongkos kerugian kualitas yang merupakan fungsi dari toleransi serta ongkos rework dan ongkos scrap. Karakteristik kualitas produk yang diperhatikan dalam penelitian ini memiliki rantai toleransi yang saling berkaitan (interrelated chain). Formulasi model yang dikembangkan menggunakan mixed integer non linear programming sebagai metode pencarian solusi.

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Concurrent process tolerance design based on minimum product manufacturing cost and quality loss

Cited by 70 publications

References 18 publications

Optimal Tolerance Allocation in a Complex Assembly Using Evolutionary Algorithms

Optimal Tolerance Allocation in a Complex Assembly Using Evolutionary Algorithms

Calculation of Total Cost, Tolerance Based on Taguchiâ€™s, AsymmetricQuality Loss Function Approach

Concurrent Engineering of Tolerance Synthesis and Process Selection for Products With Multiple Quality Characteristcs Considering Process Capability

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