Computer-aided assignment of manufacturing tolerances

Patel, A. M.

doi:10.1145/800139.804521

Cited by 11 publications

(11 citation statements)

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“…Numerous researchers have proposed different search algorithms and different forms of empirical cost functions, as summarized in Table 2. Reciprocal A + B/T Lagrange mult Nonlin prog Reciprocal Squared A + B/T 2 Lagrange mult Spotts [1973] Reciprocal Power A + B/T k Lagrange mult Sutherland & Roth [1975] Multi/Recip Powers B/T k i Nonlin prog Lee & Woo [1990] Lagrange mult Bennett & Gupta [1969] Lagrange mult Chase et al [1990] Nonlin prog Andersen [1990] Exponential B e -mT Lagrange mult Speckhart [1972] Geom prog Wilde & Prentice [1975] Graphical Peters [1970] Expon/Recip Power B e -mT /T k Nonlin prog Michael & Siddall [1981 Piecewise Linear A i -B i T i Linear prog Bjork [1989], Patel [1980] Empirical Data Discrete points Zero-one prog Ostwald & Huang [1977] Combinatorial Monte & Datseris [1982] Branch & Bound Lee & Woo [1989] The constant coefficient A represents the fixed costs, such as tooling, setup, prior operations, etc. The B term represents the cost of producing a single component dimension to a specified tolerance T. All costs are calculated on a per part basis.…”

Section: Minimum Costmentioning

confidence: 99%

A survey of research in the application of tolerance analysis to the design of mechanical assemblies

Chase

Parkinson

1991

Research in Engineering Design

281

145

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Tolerance analysis is receiving renewed emphasis as industry recognizes that tolerance management is a key element in their programs for improving quality, reducing overall costs and retaining market share. The specification of tolerances is being elevated from a menial task to a legitimate engineering design function. New engineering models and sophisticated analysis tools are being developed to assist design engineers in specifying tolerances on the basis of performance requirements and manufacturing considerations. This paper presents an overview of tolerance analysis applications to design with emphasis on recent research that is advancing the state of the art. Major topics covered are:1) New models for tolerance accumulation in mechanical assemblies, including the Motorola Six Sigma model. 2) Algorithms for allocating the specified assembly tolerance among the components of an assembly.3) The development of 2-D and 3-D tolerance analysis models. 4) Methods which account for non-Normal statistical distributions and nonlinear effects. 5) Several strategies for improving designs through the application of modern analytical tools.

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Section: Minimum Costmentioning

confidence: 99%

A survey of research in the application of tolerance analysis to the design of mechanical assemblies

Chase

Parkinson

1991

Research in Engineering Design

281

145

View full text Add to dashboard Cite

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“…The manufacturing cost is described by C M = a 0 + a 1 t + ε, where ε represents the least-squares regression error. The expected manufacturing cost can then be written as E[C M ] = a 0 + a 1 t. This linear manufacturing cost-tolerance modeling is often applied in the literature (see Patel 34 , Bjorke 35 , and Chase and Parkinson 36 ). Substituting…”

Section: Assessment Of Manufacturing Costmentioning

confidence: 99%

Integrating the LambertW Function to a Tolerance Optimization Problem

Shin¹,

Govindaluri²,

Cho³

2005

Qual. Reliab. Engng. Int.

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This paper explores the integration of the Lambert W function to a tolerance optimization problem with the assessment of costs incurred by both the customer and a manufacturer. By trading off manufacturing and rejection costs, and a quality loss, this paper shows how the Lambert W function, widely used in physics, can be efficiently applied to the tolerance optimization problem, which may be the first attempt in the literature related to tolerance optimization and synthesis. Using the concept of the Lambert W function, a closed-form solution is derived, which may serve as a means for quality practitioners to make a quick decision on their optimal tolerance without resorting to rigorous optimization procedures using numerical methods. A numerical example is illustrated and a sensitivity analysis is performed.

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“…The origin of the vector represents the datum or locating surface and the tip of the vector points to the surface generated by the tool. As an example, the subset of operations combining to satisfy constraint c 3-4 which controls hardened depth on the left hand side are determined as follows: first, locate surfaces 3 and 4 on the manufacturing graph; next find the shortest path, riding manufacturing operation vectors, which relates surface 3 to surface 4; by inspection, this path goes right along x 9 to node 11, then left along x 2 to node 2 and finally right along x 7 to node 4; keeping track of the directions traveled allows the pair of planes generated by constraint c [3][4] to be written as …”

Section: Figure 1 (A) Conventional Tolerance Control (B) Sequentialmentioning

confidence: 99%

Sequential tolerance control in discrete parts manufacturing

Fraticelli

Lehtihet

Cavalier

1997

International Journal of Production Research

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Abstract:The machining of complex parts typically involves a sequence of n operations on m machine tools. Conventional tolerance control specifies a fixed set point for each such operation and permissible variation about this set point to insure compliance with tolerance specifications. However, this approach may be inadequate for complex, low-volume, highvalue added parts. This paper introduces the concept of Sequential Tolerance Control (STC), an approach that uses real-time measurement information at the completion of a stage to exploit available space inside a dynamic feasible zone and reposition the set point for subsequent operations so as to optimize the production of an acceptable part. It is also demonstrated that the measurement information acquired during STC can be used to compensate for systematic variation such as tool wear. STC is then used in the context of an implicit enumeration approach to select an optimal subset of technological processes required to execute a process plan. Finally, a probabilistic approach to the problem of optimal selection of technological processes under conventional tolerance control is presented and the First Order Second Moment Method (FOSMM) is used to estimate yield.Introduction: Interchangeability in mechanical assemblies and satisfactory functional aptitude of parts and products are only possible when component dimensions and other geometric features are produced inside prescribed tolerance zones. The drawing or print of a part translates the above requirement into a sketch of exact part geometry augmented by dimensional and geometric tolerance information; tolerance information specifies permissible deviations from perfect geometry. In machining, final specifications of a mechanical part are arrived at via a logical, chronological sequence of material removal operations. This sequence may involve several machine tools with each machine tool performing one or more material removal operations, under one or more distinct set-ups. During the processing of a complex part, design specification datums and manufacturing operations datums do not always coincide. This leads to the commonly encountered situation where, even under the best of manufacturing plans, a large subset of part specifications are satisfied by the combination of two or more manufactured dimensions. Knowing that the output of each manufacturing operation (dimension produced) x j will fall within a certain tolerance range such that ] , [

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Computer-aided assignment of manufacturing tolerances

Cited by 11 publications

References 0 publications

A survey of research in the application of tolerance analysis to the design of mechanical assemblies

A survey of research in the application of tolerance analysis to the design of mechanical assemblies

Integrating the LambertW Function to a Tolerance Optimization Problem

Sequential tolerance control in discrete parts manufacturing

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