Characterization of shape and dimensional accuracy of incrementally formed titanium sheet parts

Single Point Incremental Forming (SPIF) is a relatively new process that has been recently used to manufacture medical grade titanium sheets for implant devices. However, one limitation of the SPIF process may be characterized by dimensional inaccuracies of the final part as compared with the original designed part model. Elimination of these inaccuracies is critical to forming medical implants to meet required tolerances. In this study, a set of basic geometric shapes were formed using SPIF to characterize the dimensional inaccuracies of grade 1 titanium sheet parts. Response surface functions are then generated to model the deviations at individual vertices of the STL model of the part as a function of geometric shape parameters such as curvature, depth, wall angle, etc. The generated response functions are further used to predict dimensional deviations in a specific clinical implant case. The predicted deviations show a reasonable match with the actual formed shape and are used to generate optimized tool paths for minimized shape and dimensional inaccuracy. Further, an implant part is then made using the accuracy characterization functions for improved accuracy. The results show an improvement in shape and dimensional accuracy of incrementally formed titanium medical implants

Student perceptions of remote learning transitions in engineering disciplines during the COVID-19 pandemic: a cross-national study

This study captures student perceptions of the effectiveness of remote learning and assessment in two associated engineering disciplines, mechanical and industrial, during the COVID-19 pandemic in a cross-national study. A structured questionnaire with 24 items on a 5-point Likert scale was used. Parallel and exploratory factor analyses identified three primary subscales. The links between student perceptions and assessment outcomes were also studied. There was a clear preference for face-to-face teaching, with the highest for laboratories. Remote live lectures were preferred over recorded. Although students found the switch to remote learning helpful, group work and communication were highlighted as concern areas. Mean scores on subscales indicate a low preference for remote learning (2.23), modest delivery effectiveness (3.05) and effective digital delivery tools (3.61). Gender effects were found significant on all subscales, along with significant interactions with university and year-group. Preference for remote delivery of design-based modules was significantly higher than others

Energy consumption analysis of robot based SPIF

Part of: Seliger, Günther (Ed.): Innovative solutions : proceedings / 11th Global Conference on Sustainable Manufacturing, Berlin, Germany, 23rd - 25th September, 2013. - Berlin: Universitätsverlag der TU Berlin, 2013. - ISBN 978-3-7983-2609-5 (online). - http://nbn-resolving.de/urn:nbn:de:kobv:83-opus4-40276. - pp. 131–136.Production processes, as used for discrete part manufacturing, are responsible for a substantial part of the environmental impact of products, but are still poorly documented in terms of environmental impact. A thorough analysis of the causes affecting the environmental impact in metal forming processes is mandatory. The present study presents an energy consumption analysis, including a power study of Single Point Incremental Forming (SPIF) processes using a 6-axes robot platform. The present paper aims to investigate whether the fixed energy consumption is predominant or negligible in comparison to the actual forming operation. Power studies are performed in order to understand the contribution of each sub-unit towards the total energy demand. The influence of the most relevant process parameters, as well as the material being processed and the sheet positioning, with respect to the power demand are analysed

Numerical simulation of a pyramid steel sheet formed by single point incremental forming using solid-shell finite elements

peer reviewedSingle Point Incremental Forming (SPIF) is an interesting manufacturing process due to its dieless nature and its increased formability compared to conventional forming processes. Nevertheless, the process suffers from large geometric deviations when compared to the original CAD profile. One particular example arises when analyzing a truncated two-slope pyramid. In this paper, a finite element simulation of this geometry is carried out using a newly implemented solid-shell element, which is based on the Enhanced Assumed Strain (EAS) and the Assumed Natural Strain (ANS) techniques. The model predicts the shape of the pyramid very well, correctly representing the springback and the through thickness shear (TTS). Besides, the effects of the finite element mesh refinement, the EAS and ANS techniques on the numerical prediction are presented. It is shown that the EAS modes included in the model have a significant influence on the accuracy of the results

Exploiting lattice structures in shape grammar implementations

The ability to work with ambiguity and compute new designs based on both defined and emergent shapes are unique advantages of shape grammars. Realizing these benefits in design practice requires the implementation of general purpose shape grammar interpreters that support: (a) the detection of arbitrary subshapes in arbitrary shapes and (b) the application of shape rules that use these subshapes to create new shapes. The complexity of currently available interpreters results from their combination of shape computation (for subshape detection and the application of rules) with computational geometry (for the geometric operations need to generate new shapes). This paper proposes a shape grammar implementation method for three-dimensional circular arcs represented as rational quadratic Bézier curves based on lattice theory that reduces this complexity by separating steps in a shape computation process from the geometrical operations associated with specific grammars and shapes. The method is demonstrated through application to two well-known shape grammars: Stiny's triangles grammar and Jowers and Earl's trefoil grammar. A prototype computer implementation of an interpreter kernel has been built and its application to both grammars is presented. The use of Bézier curves in three dimensions opens the possibility to extend shape grammar implementations to cover the wider range of applications that are needed before practical implementations for use in real life product design and development processes become feasible

Characterization of shape and dimensional accuracy of incrementally formed titanium sheet parts with intermediate curvatures between two feature types

Single point incremental forming (SPIF) is a relatively new manufacturing process that has been recently used to form medical grade titanium sheets for implant devices. However, one limitation of the SPIF process may be characterized by dimensional inaccuracies of the final part as compared with the original designed part model. Elimination of these inaccuracies is critical to forming medical implants to meet required tolerances. Prior work on accuracy characterization has shown that feature behavior is important in predicting accuracy. In this study, a set of basic geometric shapes consisting of ruled and freeform features were formed using SPIF to characterize the dimensional inaccuracies of grade 1 titanium sheet parts. Response surface functions using multivariate adaptive regression splines (MARS) are then generated to model the deviations at individual vertices of the STL model of the part as a function of geometric shape parameters such as curvature, depth, distance to feature borders, wall angle, etc. The generated response functions are further used to predict dimensional deviations in a specific clinical implant case where the curvatures in the part lie between that of ruled features and freeform features. It is shown that a mixed-MARS response surface model using a weighted average of the ruled and freeform surface models can be used for such a case to improve the mean prediction accuracy within ±0.5 mm. The predicted deviations show a reasonable match with the actual formed shape for the implant case and are used to generate optimized tool paths for minimized shape and dimensional inaccuracy. Further, an implant part is then made using the accuracy characterization functions for improved accuracy. The results show an improvement in shape and dimensional accuracy of incrementally formed titanium medical implants

Effect of stress relieving heat treatment on surface topography and dimensional accuracy of incrementally formed grade 1 titanium sheet parts

The forming of parts with an optimized surface roughness and high dimensional accuracy is important in many applications of incremental sheet forming (ISF). To realize this, the effect of stress relieving heat treatment of grade-1 Ti parts performed before and after forming on the surface finish and dimensional accuracy was studied. It was found that heat treatment at a temperature of 540 °C for 2 h improves the surface finish of formed parts resulting in a surface with little or no visible tool marks. Additionally, it improves the dimensional accuracy of parts after unclamping from the rig used for forming, in particular, that of parts with shallow wall angles (typically <25°). It was also noted that post-forming heat treatment improves the surface finish of parts. The surface topography of formed parts was studied using interferometry to yield areal surface roughness parameters and subsequently using secondary electron imaging. Back-scatter electron microscopy imaging results coupled with energy-dispersive X-ray (EDX) analysis showed that heat treatment prior to forming leads to tool wear as indicated by the presence of Fe in samples. Furthermore, post-forming heat treatment prevents curling up of formed parts due to compressive stresses if the formed part is trimmed

Sharing design definitions across product life cycles

The research reported in this paper explored the feasibility of embedding multiple design structures into design definitions with a view of sharing design definitions across product life cycles. Two separate case studies using (a) lattice theory and (b) a qualitative data analysis (QDA) software tool were used to illustrate the benefits of embedding. In the first case study, of a robotic arm assembly, lattices in the form of partially ordered sets are used to embed multiple design structures into a given design definition. A software prototype has been built that allows a design bill of materials (BoM) to be extracted from a STEP AP214 file and translated into a lattice that is visualized as a Hasse diagram. This lattice is a sub-lattice of a complete lattice that includes all possible BoM structures for the given collection of component parts in the assembly. New BoM design structures can be defined by selecting the required nodes in the complete lattice and alternative product definitions are then exported as new STEP files. The second case study introduces a collision avoidance robot with associated design structures. It is used to illustrate management of design information using a current technique, design structure matrix (DSM), and compared with how embedding using QDA has the potential to support the establishment of relationships between design structures. Results from these case studies demonstrate that it is feasible to use lattice theory as an underlying formalism and QDA as a means for sharing design definitions

Low-Energy Physics in Neutrino LArTPCs

In this white paper, we outline some of the scientific opportunities and challenges related to detection and reconstruction of low-energy (less than 100 MeV) signatures in liquid argon time-projection chamber (LArTPC) detectors. Key takeaways are summarized as follows. 1) LArTPCs have unique sensitivity to a range of physics and astrophysics signatures via detection of event features at and below the few tens of MeV range. 2) Low-energy signatures are an integral part of GeV-scale accelerator neutrino interaction final states, and their reconstruction can enhance the oscillation physics sensitivities of LArTPC experiments. 3) BSM signals from accelerator and natural sources also generate diverse signatures in the low-energy range, and reconstruction of these signatures can increase the breadth of BSM scenarios accessible in LArTPC-based searches. 4) Neutrino interaction cross sections and other nuclear physics processes in argon relevant to sub-hundred-MeV LArTPC signatures are poorly understood. Improved theory and experimental measurements are needed. Pion decay-at-rest sources and charged particle and neutron test beams are ideal facilities for experimentally improving this understanding. 5) There are specific calibration needs in the low-energy range, as well as specific needs for control and understanding of radiological and cosmogenic backgrounds. 6) Novel ideas for future LArTPC technology that enhance low-energy capabilities should be explored. These include novel charge enhancement and readout systems, enhanced photon detection, low radioactivity argon, and xenon doping. 7) Low-energy signatures, whether steady-state or part of a supernova burst or larger GeV-scale event topology, have specific triggering, DAQ and reconstruction requirements that must be addressed outside the scope of conventional GeV-scale data collection and analysis pathways