Optimal tolerance design for mechanical assembly considering thermal impact

Jayaprakash, G.; Thilak, M.; Sivakumar, K.

doi:10.1007/s00170-014-5845-0

Cited by 20 publications

(13 citation statements)

References 21 publications

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“…( f 1 ) is the inhomogeneity of the magnetic field, H, on the bottom of the Petri dish, to be minimised as in [37] with a tolerance interval of ±10 A/m. Once (8) and (9) are solved, the H-field intensity can be computed from magnetic vector potential A in a straight forward way. Therefore the inhomogeneity of H in terms of the H-norm discrepancy, that is dimensionless, is evaluated on the bottom of the Petri dish on a fixed grid of points; ( f 2 ) is the sensitivity of f 1 with respect to the set of uncertain design variables shown in Table 2, evaluated according to (5), to be minimised; and ( f 3 ) is the end voltage (or current) when the inductor is supplied by applying a current (or a voltage, respectively).…”

Section: Optimisation Problemmentioning

confidence: 99%

“…In fact, in production process, the device and its components are affected by tolerances that can significantly modify its performance [8][9][10][11][12] and tolerance intervals are given to each geometrical dimension. The design of a device needs to find optimal solutions insensitive to small perturbations of design variables.…”

Section: Introductionmentioning

confidence: 99%

“…Currently, the optimal design of electromagnetic device is largely researched also to include the effect of uncertainties on design variables or parameters [1][2][3][4][5][6][7]. In fact, in production process, the device and its components are affected by tolerances that can significantly modify its performance [8][9][10][11][12] and tolerance intervals are given to each geometrical dimension. The design of a device needs to find optimal solutions insensitive to small perturbations of design variables.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sensitivity‐based optimal shape design of induction‐heating devices

Barba

Dughiero

Forzan

et al. 2015

IET Science, Measurement & Technology

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A design of experiment (DOE) strategy applied to multi-objective optimisation is proposed in order to evaluate the influence of design variables variations to optimised quantities. A secondary objective function is the sensitivity of a primary objective function to design variable variations evaluated by means of DOE strategy. The optimisation problem includes also a thir objective function that considers device constraint because of technological limitations on power generator. The proposed case study deals with the design of an electromagnetic device that will be used to carry out laboratory experiments on magneto-fluid hyperthermia, that is, a clinic treatment for cancer cure. The induction system is designed to apply a controlled time-varying magnetic field to biological cells, cultured in Petri dish and mixed with magnetic nanoparticles. This study presents an original cost-effective method of multi-objective design optimisation taking into account design uncertainties

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Section: Optimisation Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Sensitivity‐based optimal shape design of induction‐heating devices

Barba

Dughiero

Forzan

et al. 2015

IET Science, Measurement & Technology

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“…This can significantly affect assembly variation. 8,9 Many instruments for large-volume metrology are also afflicted by uncertainties due to ambient refractive index changes. Temperature is one of the main contributors to refractive index variation, 10 alongside other variables such as pressure, humidity, air composition (e.g.…”

Section: Introductionmentioning

confidence: 99%

Thermal compensation using the hybrid metrology approach compared to traditional scaling

Ross-Pinnock

Mullineux

2017

Proceedings of the Institution of Mechanical Engineers, Part B:

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Control of temperature in large-scale manufacturing environments is not always practical or economical, introducing thermal effects including variation in ambient refractive index and thermal expansion. Thermal expansion is one of the largest contributors to measurement uncertainty; however, temperature distributions are not widely measured. Uncertainties can also be introduced in scaling to standard temperature. For more complex temperature distributions with non-linear temperature gradients, uniform scaling is unrealistic. Deformations have been measured photogrammetrically in two thermally challenging scenarios with localised heating. Extended temperature measurement has been tested with finite element analysis to assess a compensation methodology for coordinate measurement. This has been compared to commonly used uniform scaling and has outperformed this with a highly simplified finite element analysis simulation in scaling a number of coordinates at once. This work highlighted the need for focus on reproducible temperature measurement for dimensional measurement in non-standard environments.

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“…Finite element analysis has also been used recently in combination with machine learning algorithms to model thermo-mechanical loads in turning processes [7]. Thermal variation has also been studied for mechanical assemblies and the thermal impact on tolerances [8,9]. A recent study included temperature as one of several operating parameters in tolerance analysis to determine the 'operating window' of an assembly process [10].…”

Section: Introductionmentioning

confidence: 99%

Review of industrial temperature measurement technologies and research priorities for the thermal characterisation of the factories of the future

Ross-Pinnock

Maropoulos

2015

Proceedings of the Institution of Mechanical Engineers, Part B:

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As the largest source of dimensional measurement uncertainty, addressing the challenges of thermal variation is vital to ensure product and equipment integrity in the factories of the future. Whilst it is possible to closely control room temperature, this is often not practical or economical to realise in all cases where inspection is required. This paper reviews recent progress and trends in seven key commercially available industrial temperature measurement sensor technologies primarily in the range 0-50˚C for invasive, semi-invasive and non-invasive measurement. These sensors will ultimately be used to measure and model thermal variation in the assembly, test and integration (AIT) environment. The intended applications for these technologies are presented alongside some consideration of measurement uncertainty requirements with regard to the thermal expansion of common materials. Research priorities are identified and discussed for each of the technologies as well as temperature measurement at large. Future developments are briefly discussed to provide some insight into which direction the development and application of temperature measurement technologies are likely to head.

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Optimal tolerance design for mechanical assembly considering thermal impact

Cited by 20 publications

References 21 publications

Sensitivity‐based optimal shape design of induction‐heating devices

Sensitivity‐based optimal shape design of induction‐heating devices

Thermal compensation using the hybrid metrology approach compared to traditional scaling

Review of industrial temperature measurement technologies and research priorities for the thermal characterisation of the factories of the future

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