Intermethod Comparison and Evaluation of Near Surface Residual Stress in Aluminum Parts Subject to Various Milling Parameters

Chighizola, Christopher R.; D’Elia, Christopher R.; Hill, Michael R.

doi:10.1007/978-3-030-30098-2_10

Cited by 5 publications

(5 citation statements)

References 4 publications

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“…5). A hole with an approximate diameter of 2 mm is cut in an orbital path with a 1.59-mm-diameter end mill on an electric spindle [14]. At each incremental cut, the strain gage measures three components of strain.…”

Section: Mirs Hole-drilling Measurementsmentioning

confidence: 99%

“…The present research focuses on the repeatability of MIRS for multiple milled aluminum workpieces, machined with the same machining parameter. Our previous research studied the repeatability of RS measurement techniques (hole-drilling, slotting, sin 2 (ψ) XRD, cos(α) XRD) themselves [13,14]. It was found that data from hole-drilling (HD) are most consistent with machining-induced distortion for AA7050-T7451 parts and multiple measurements are necessary to describe the MIRS with good statistical confidence.…”

Section: Introductionmentioning

confidence: 99%

“…Machining parameters cutting speed v c , feed per tooth f z and resulting feed rate v f , material removal rate Q w , and average chip thickness h m[14,17] …”

mentioning

confidence: 99%

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Analysis of machining-induced residual stresses of milled aluminum workpieces, their repeatability, and their resulting distortion

Weber

Kirsch

Chighizola

et al. 2021

Int J Adv Manuf Technol

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Machining-induced residual stresses (MIRS) are a main driver for distortion of thin-walled monolithic aluminum workpieces. Before one can develop compensation techniques to minimize distortion, the effect of machining on the MIRS has to be fully understood. This means that not only an investigation of the effect of different process parameters on the MIRS is important. In addition, the repeatability of the MIRS resulting from the same machining condition has to be considered. In past research, statistical confidence of MIRS of machined samples was not focused on. In this paper, the repeatability of the MIRS for different machining modes, consisting of a variation in feed per tooth and cutting speed, is investigated. Multiple hole-drilling measurements within one sample and on different samples, machined with the same parameter set, were part of the investigations. Besides, the effect of two different clamping strategies on the MIRS was investigated. The results show that an overall repeatability for MIRS is given for stable machining (between 16 and 34% repeatability standard deviation of maximum normal MIRS), whereas instable machining, detected by vibrations in the force signal, has worse repeatability (54%) independent of the used clamping strategy. Further experiments, where a 1-mm-thick wafer was removed at the milled surface, show the connection between MIRS and their distortion. A numerical stress analysis reveals that the measured stress data is consistent with machining-induced distortion across and within different machining modes. It was found that more and/or deeper MIRS cause more distortion.

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Section: Mirs Hole-drilling Measurementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of machining-induced residual stresses of milled aluminum workpieces, their repeatability, and their resulting distortion

Weber

Kirsch

Chighizola

et al. 2021

Int J Adv Manuf Technol

Self Cite

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“…36 Fewer research efforts have tackled fusion welding processes, such as vibrationassisted laser keyhole welding. 37 Recent research in material removal operations have explored specific challenging phenomena, such as those attendant with ultraprecision machining of ceramics [38][39][40] ; machining-induced distortion in milling 41,42 ; through-tool minimum quantity lubrication drilling 43 ; and atomized dielectric-based electro discharge machining. 44 Research in this domain is also directed at improving machine tools, such as software-supported improvement of speed and accuracy of vibration-prone machines [45][46][47] ; at metrology, such as measurements of part features using freeform optics, [48][49][50] measurement of dynamic moving parts in manufacturing tools, 51 and manufacturing of optics used in metrology 52 ; and at nondestructive evaluation of composites.…”

Section: Conventional Manufacturingmentioning

confidence: 99%

Defining Near-Term to Long-Term Research Opportunities to Advance Metrics, Models, and Methods for Smart and Sustainable Manufacturing

Raman

Haapala

Raoufi

et al. 2020

Smart and Sustainable Manufacturing Systems

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Over the past century, research has focused on continuously improving the performance of manufacturing processes and systems—often measured in terms of cost, quality, productivity, and material and energy efficiency. With the advent of smart manufacturing technologies—better production equipment, sensing technologies, computational methods, and data analytics applied from the process to enterprise levels—the potential for sustainability performance improvement is tremendous. Sustainable manufacturing seeks the best balance of a variety of performance measures to satisfy and optimize the goals of all stakeholders. Accurate measures of performance are the foundation on which sustainability objectives can be pursued. Historically, operational and information technologies have undergone disparate development, with little convergence across the domains. To focus future research efforts in advanced manufacturing, the authors organized a one-day workshop, sponsored by the U.S. National Science Foundation, at the joint manufacturing research conferences of the American Society of Mechanical Engineers and Society of Manufacturing Engineers. Research needs were identified to help harmonize disparate manufacturing metrics, models, and methods from across conventional manufacturing, nanomanufacturing, and additive/hybrid manufacturing processes and systems. Experts from academia and government labs presented invited lightning talks to discuss their perspectives on current advanced manufacturing research challenges. Workshop participants also provided their perspectives in facilitated brainstorming breakouts and a reflection activity. The aim was to define advanced manufacturing research and educational needs for improving manufacturing process performance through improved sustainability metrics, modeling approaches, and decision support methods. In addition to these workshop outcomes, a review of the recent literature is presented, which identifies research opportunities across several advanced manufacturing domains. Recommendations for future research describe the short-, mid-, and long-term needs of the advanced manufacturing community for enabling smart and sustainable manufacturing.

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“…The slitting method is relatively easy to perform, can be performed quickly, and provides excellent repeatability, which makes it very useful for actual laboratory residual stress measurements [ 27 ]. As the experimental deviation of the slitting method was smaller than that of the hole drilling method [ 29 ], the slitting method was chosen in the present experiment.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Residual Stress Measurement Conditions for a 2D Method Using X-ray Diffraction and Its Application for Stainless Steel Treated by Laser Cavitation Peening

et al. 2021

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As the fatigue strength of metallic components may be affected by residual stress variation at small length scales, an evaluation method for studying residual stress at sub-mm scale is needed. The sin2ψ method using X-ray diffraction (XRD) is a common method to measure residual stress. However, this method has a lower limit on length scale. In the present study, a method using at a 2D XRD detector with ω-oscillation is proposed, and the measured residual stress obtained by the 2D method is compared to results obtained from the sin2ψ method and the slitting method. The results show that the 2D method can evaluate residual stress in areas with a diameter of 0.2 mm or less in a stainless steel with average grain size of 7 μm. The 2D method was further applied to assess residual stress in the stainless steel after treatment by laser cavitation peening (LCP). The diameter of the laser spot used for LCP was about 0.5 mm, and the stainless steel was treated with evenly spaced laser spots at 4 pulses/mm2. The 2D method revealed fluctuations of LCP-induced residual stress at sub-mm scale that are consistent with fluctuations in the height of the peened surface.

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Intermethod Comparison and Evaluation of Near Surface Residual Stress in Aluminum Parts Subject to Various Milling Parameters

Cited by 5 publications

References 4 publications

Analysis of machining-induced residual stresses of milled aluminum workpieces, their repeatability, and their resulting distortion

Analysis of machining-induced residual stresses of milled aluminum workpieces, their repeatability, and their resulting distortion

Defining Near-Term to Long-Term Research Opportunities to Advance Metrics, Models, and Methods for Smart and Sustainable Manufacturing

Optimization of Residual Stress Measurement Conditions for a 2D Method Using X-ray Diffraction and Its Application for Stainless Steel Treated by Laser Cavitation Peening

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