Model testing of fixture–workpiece interface compliance in dynamic conditions

Tadić, Branko; Vukelić, Djordje; Miljanic, Dragomir; Bogdanovic, Bojan; Mačužić, Ivan; Budak, Igor; Todorovič, P.

doi:10.1016/j.jmsy.2013.05.004

Cited by 19 publications

(8 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Studies on CNC machining centres clamping devices field [10][11] present weaknesses and strengths of clamping devices to achieve the desired results of experimental work. Studies as Theodoris et.…”

Section: Introductionmentioning

confidence: 99%

Using Quality Tools for Process Development and Improvement; Case Study on Cylinder Manufacturing

Eniko¹,

Soković²,

Kramar³

2017

IJAQ

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Using Quality Tools for Process Development and Improvement; Case Study on Cylinder Manufacturing

Eniko¹,

Soković²,

Kramar³

2017

IJAQ

View full text Add to dashboard Cite

“…Geometric locating tolerance analysis and FEA based structural deformation prediction methods were integrated into one framework to improve the machining performance of a thin-walled turbine blade. Tadic et al [20] focused on the problem of compliance of interface between clamping/locating fixture elements and workpiece. The results of experimental investigation showed that the clamping/locating elements with largerradius spherical tips provide significantly lower interface compliance.…”

Section: Introductionmentioning

confidence: 99%

Intelligent design and optimization of machining fixtures

et al. 2016

View full text Add to dashboard Cite

Original scientific paper This work presents an integral system for machining fixture layout design and optimization. The optimization module of this system allows determination of optimal positions of locating and clamping elements, which provides required accuracy and surface quality, while at the same time guarantees design of collision-free fixtures. The design module performs selection of required fixture elements based on a set of predefined production rules. Adequate criteria for the selection of fixture elements are defined for locating, clamping, tool guiding, and tool adjustment elements, as well as for fixture body elements, connecting elements and add-on elements. The system uses geometry and feature workpiece characteristics, as well as the additional machining, and process planning information. It has been developed to accommodate machining processes of turning, drilling, milling, and grinding of rotational and prismatic workpieces. A segment of output results is also shown. Finally, conclusions are presented with directions for future investigation. Keywords: artificial intelligence; fixture; process planningInteligentno projektiranje i optimizacija konstrukcija naprava za strojnu obradu Izvorni znanstveni rad U radu je predstavljen integralni sustav za projektiranje i optimizaciju konstrukcije naprava za strojnu obradu. Dio sustava za optimizaciju omogućuje, s jedne strane, određivanje optimalnih pozicija elemenata za baziranje i stezanje kako bi se postigla potrebna točnost i kvaliteta obrađene površine izratka, a s druge strane, generiranje konstrukcije naprava bez kolizija. Dio sustava za projektiranje osigurava izbor pojedinih elemenata naprava na osnovi prethodno definiranih produkcijskih pravila. Prilagođeni kriteriji izbora definirani su za elemente za baziranje, elemente za stezanje, elemente za vođenje alata, elemente za podešavanje položaja alata, elemente tijela naprava, elemente za povezivanje i nadogradne elemente. Sustav je baziran na geometrijskim karakteristikama i karakterističnim obilježjima djela, kao i dodatnim informacijama o obradi i informacijama iz tehnološkog procesa. Sustav je razvijan za operacije tokarenja, bušenja, glodanja i brušenja koje se izvode na rotacijskim i prizmatičnim radnim predmetima. U radu su djelomično prikazani izlazni rezultati razvijenog sustava. Na kraju rada dani su odgovarajući zaključci i istaknuti mogući pravci daljih istraživanja.

show abstract

“…Studies on CNC machining centres clamping devices field [10] and [11] present weaknesses and strengths of clamping devices to achieve the desired results of experimental work. Studies as Theodoris and Koutroumbas [12] and Hassan and Basksh [13] are focused on pattern recognition in Statistical Process Control (SPC) control charts.…”

Section: Introductionmentioning

confidence: 99%

Influence of Non-Productive Operations on Product Quality

Eniko¹,

Soković

Kramar

2016

SV-JME

View full text Add to dashboard Cite

Small batch production is mainly, due to the competitiveness of the market, oriented to achieve the required specifications with minimal manufacturing processes using standard cutting tools. Costume-made hydraulic valves are one of the unique cases of small batch production in combination with high tolerances requirements [1]. Honing represents the manufacturing process which enables achieving final geometric requirements for valve's cylinder bore and requires pre-processing on computer numerical control (CNC) machining centre with successive cutting processes drilling, milling and reaming. Specifications of the piston bore of the hydraulic valve housing prescribe cylindricity /○/ ≤ 12 µm and surface roughness Ra ≤ 1.6 µm after reaming and cylindricity /○/ ≤ 3 µm and surface roughness Ra ≤ 0.4 µm after honing.This paper deals with reaming process quality improvement. Experiment planning and process modelling were performed by design of experiments (DOE) methodology [2]. Measuring method for bore cylindricity was defined as suggested in [3] and [4] and surface topology with mean roughness parameter Ra [5]. Within the framework of an experimental investigation single and combined effects, as well as related reproducibility, of such parameters on bore geometry and surface finish were investigated.Factors that have been identified as key to achieve specifications (bolded factors in Fig. 1) have been studied within the experimental work. Authors in other reaming processes optimization studies investigated spindle speed n and feed rate f as numeric control factor [6] to [9]. In this study feed rate and spindle speed were recognized as the key productive operation factors as well.Studies The key non-productive operation factors that were analysed in this study were clamping device lack of rigidity and effect of surface cleanliness on measurements reproducibility. Clamping device weakness was minimized with focusing on only one (of three) clamping nest. Surface cleanliness impact was analysed with SEM analysis and was minimized with additional washing and degreasing. Influence of Non-Productive Operations on Product Quality

show abstract

Model testing of fixture–workpiece interface compliance in dynamic conditions

Cited by 19 publications

References 27 publications

Using Quality Tools for Process Development and Improvement; Case Study on Cylinder Manufacturing

Using Quality Tools for Process Development and Improvement; Case Study on Cylinder Manufacturing

Intelligent design and optimization of machining fixtures

Influence of Non-Productive Operations on Product Quality

Contact Info

Product

Resources

About