It is widely acknowledged that the allocation of part tolerances is a highly responsible task due to the complex repercussions on both product quality and cost. As a consequence, since its beginnings in the 1960s, least-cost tolerance allocation using optimization techniques, i.e. tolerance-cost optimization, was continuously in focus of numerous research activities. Nowadays, increasing cost and quality pressure, availability of real manufacturing data driven by Industry 4.0 technologies, and rising computational power result in a continuously growing interest in tolerance-cost optimization in both research and industry. However, inconsistent terminology and the lack of a classification of the various relevant aspects is an obstacle for the application of tolerance-cost optimization approaches. There is no literature comprehensively and clearly summarizing the current state of the art and illustrating the relevant key aspects. Motivated to overcome this drawback, this article provides a comprehensive as well as detailed overview of the broad research field in tolerance-cost optimization for both beginners and experts. To facilitate the first steps for readers who are less familiar with the topic, the paper initially outlines the fundamentals of tolerance-cost optimization including its basic idea, elementary terminology and mathematical formulation. These fundamentals serve as a basis for a subsequent detailed discussion of the key elements with focus on the different characteristics concerning the optimization problem, tolerance-cost model, technical system model and the tolerance analysis model. These aspects are gathered and summarized in a structured mind map, which equips the reader with a comprehensive graphical overview of all the various facets and aspects of tolerance-cost optimization. Beside this, the paper gives a retrospect of the past fifty years of research in tolerance cost-optimization, considering 290 relevant publications. Based thereon, current issues and future research needs in tolerance-cost optimization were identified.

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From tolerance allocation to tolerance-cost optimization: a comprehensive literature review

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 4515 Cr and its corresponding tolerances for machining process turning, drilling, face milling, face milling and drilling where 0063, 00508, 02127, 02127, 02540 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

/pdf/calculation-of-total-cost-tolerance-based-on-taguchi-s-17hf4t0to0.pdf

Calculation of Total Cost, Tolerance Based on Taguchi's, Asymmetric Quality Loss Function Approach

The tolerance allocation problem has been studied in the literature for decades, usually using mathematical programming (or) heuristic optimization approaches. Elegant tools for minimum cost tolerance allocation have been developed over several decades but still there is no specified tool to find the total cost with respect to machining cost and asymmetric quality loss functions. Objective of this paper is to find the optimized total cost by considering the machining cost and the asymmetric quality loss of an assembly. The non linear multi variable optimization of total cost problem formulated is solved using genetic algorithm. In this work, Piston and cylinder arrangement example was considered for concurrent allocation of design and machining tolerance, as well as to optimize the total cost. The result shows, optimized tolerance will enhances the quality and reduces the total cost

Integrated total cost and Tolerance Optimization with Genetic Algorith

Tolerances have a significant impact on manufacturing cost and product quality. In the design of discrete part shapes, the specification of tolerance constraints can have major consequences for product quality and cost. Traditional methods for tolerance analysis and synthesis are time consuming and have limited applicability. A more scientific approach is often desirable for better performance to overcome this difficulty. In this paper, the objective is to examine the optimal tolerance allocation by considering both tolerance cost and manufacturing cost so that the total assembly cost is minimized. A new global nonlinear optimization technique called Pattern search algorithm has been implemented to find the optimal tolerance allocation and asymmetric total cost to overcome the shortcomings in the conventional tolerance allocation problem.

	 

	Key words: Optimization, tolerance allocation, machining tolerance, pattern search.

Optimization of design tolerance and asymmetric quality loss cost using pattern search algorithm

Rapid changes in the market place have led designers and manufacturers to continuously develop new products to satisfy the demands of more exigent customers. Therefore, to be competitive, designers and manufacturers have to perform those steps accurately to ensure final Product quality and manufacturing cost. So Product quality and manufacturing cost have a significant impact on Tolerance. A more scientific approach is often desirable for better performance to overcome this Tolerance problem. In this paper, Design and machining tolerances have been allocated based on optimum total machining cost. New global nonlinear optimization techniques called Pattern Search algorithm and Genetic algorithm have been implemented to find the optimal tolerance allocation and total cost. Finally with respect to total cost both the methods have been compared.

Simultaneous Optimization of Design Tolerance and Total Cost for a Piston and Cylinder Assembly

Review of Tolerance Analysis, Allocation and Constraints in Manufacturing

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Review of Tolerance Analysis, Allocation and Constraints in Manufacturing