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The purpose of this paper is to present a novel assembly spring-back model which takes surface contact conditions between sheet metal parts into consideration so that the assembly dimensions and variations can be more precisely predicted than existing assembly simulation models.

Because an assembly process is composed of four essential steps, i.e. locating, clamping, joining and tool releasing, the mechanistic models associated with these steps are developed in the paper. In particular, the surface contact between the weld flanges (in folding joint configuration) and the overlapping surfaces (in lap joint configurations) is included in the models. Sensitivity models are developed.

Two cases studies are presented, i.e. the cantilever beams assembly and the Z-plates assembly. More precise prediction results are shown.

The model developed in this paper is based upon analytical elastic beam theories. Therefore, the results and case studies are limited only to workpieces that can be approximately represented by beam geometries. However, the methods can be broadened to generic workpiece geometries by using finite element methods; thus, the developed method is highly valuable to a broad range of applications such as automotive body assembly and aerospace industries.

The novelty of this research lies in its inclusion of surface contact conditions in an assembly simulation model by using analytical beam mechanistic models to achieve more accurate assembly variation predictions.

“V-bending” is the most commonly used bending process in which the sheet metal is pressed into a “V-shaped” die using a “V-shaped” punch to form a required angular bend. When the punch is removed after the operation, because of elastic recovery, the bent angle varies. This shape discrepancy is known as spring back which causes problems in the assembly of the component in the modern aerospace industry. Regarding the optimization of spring-back accuracy, this research will illustrate the laws of the transition area (TA) of the nondeformation area (NDA) during the 90° “V-shape” bending process.

According to the traditional “V-bending” process to optimize the spring-back accuracy, the bent sheets are divided into deformation area (DA) and NDA. For this reason, the traditional “V-bending” process may prolong error to optimize the spring-back accuracy because NDA has a certain amount of deformation, which the researcher always avoids. Firstly, bent sheets are divided into three parts in this research: DA, TA and NDA to avoid the distortion error in TA that are not considered in the NDA in traditional theory. Then, the stress and strain in the DA and TA were discussed during theoretical derivation and some hypotheses were proposed. In this research, the interval, position and distortion degree of the TA of the bending sheet are used by finite element analysis. Finally, V-shape bending tests for aluminum alloy at room temperature are used and labeled all the work pieces' TAs to realize the deformation amount in the TA.

The bending radius does not affect the range of the TA, it only changes the position of TA in the bending sheet. It is evident that the laws of TA were explored in the width direction and gradually changed from the inner layer to the outer layer based on the ratio of width and thickness of the bending plate/sheet.

In the modern aerospace industry, aircraft manufacturing technology must maintain high accuracy. This research has practical value in the 90° “V-shape” bending of metal sheets and the development of its spring-back accuracy.

The term springback is defined as the change in geometry of a component after forming, when the forces are removed from forming tools. As springback affects the final shape of the part, it can lead to significant difficulties in the assembly of component when springback is not proper. This problem leads to fabrication of inconsistent sheet metal parts; the elastic strain recovery in the material after the tooling is removed. Bendingis the plastic deformation of metals about a linear axis called the bending axis with little or no change in the surface area. Bending types of forming operations have been used widely in sheet metal forming industries to produce structural stamping parts such as braces, brackets, supports, hinges, angles, frames, channel and other nonsymmetrical sheet metal parts. Among them, quite a few efforts have been made to obtain a deep understanding of the springback phenomenon. The beam theory has been applied to formulate the curvature before and after loading of pipe. This research work has focused on study effect of springback effect with a new approach. The ANSYS software is used to analyze spring back effect. The detail study of this springback effect is presented in this paper.

This present research aims to identify the optimum process parameters for enhancing geometric accuracy in single-point incremental forming of aviation-grade superalloy 625.

The geometric accuracy has been measured in terms of half-cone-angle, concentricity, roundness and wall-straightness errors. The Taguchi Orthogonal-Array L9 with desirability-function-analysis has been used to achieve improved accuracy.

To achieve maximum geometric accuracy, the optimum setting having a tooltip diameter of 10 mm, a step-size of 0.2 mm and a tool rotation speed (TRS) of 900 RPM has been derived. With this setting, the half-cone-angle accuracy increases by 42.96%, the concentricity errors decrease by 47.36%, the roundness errors decline by 45.2% and the wall straightness errors reduce by 1.06%.

Superalloy 625 is a widespread nickel-based alloy, finding enormous applications in aerospace, marine and chemical industries.

It has been recommended to increase TRS, reduce step-size and use moderate size tooltip diameter to enhance geometric accuracy. Step-size has been found to be the governing parameter among all the parameters.

This paper aims to propose a conceptual scale model of mobile drilling robot according to the actual drilling rig and working conditions to improve the safety and automation of drilling in tunnel construction and coal mining applications.

A couple of pinion and rack serves as the support mechanism driven by a motor with low rotation speed at high power, and these components are assembled in the center of the robot to tightly fasten the whole body together. The drilling rod and the sleeve are connected through a hole with screw thread so that the rod feeds and rotates simultaneously along with the sleeve. The robot model is automatically controlled by a single-chip microcomputer, and the anti-disturbance circuit is designed as well. A five-step rule obstacle avoidance method is proposed to ensure safe and reliable movement.

The results of simulation experiments on drilling operation do indicate that the mechanism and control method are feasible and effective.

The robot is nearly complete but indeed remains only an experimental machine.

The design of the mechanism structure for the conceptual robot is novelty. The method of five-step rule obstacle avoidance can improve reliability of obstacle avoidance according to the experimental results, which can meet the requirements of complex working conditions underground coal mine.

This study aims to introduce a vision-based model to generate droplets with auto-tuned parameters. The model can auto-adjust the inherent uncertainties and errors involved with the fabrication and operating parameters in microfluidic platform, attaining precise size and frequency of droplet generation.

The photolithography method is utilized to prepare the microfluidic devices used in this study, and various experiments are conducted at various flow-rate and viscosity ratios. Data for droplet shape is collected to train the artificial intelligence (AI) models.

Growth phase of droplets demonstrated a unique spring back effect in droplet size. The fully developed droplet sizes in the microchannel were modeled using least absolute shrinkage and selection operators (LASSO) regression model, Gaussian support vector machine (SVM), long short term memory (LSTM) and deep neural network models. Mean absolute percentage error (MAPE) of 0.05 and R² = 0.93 were obtained with a deep neural network model on untrained flow data. The shape parameters of the droplets are affected by several uncontrolled parameters. These parameters are instinctively captured in the model.

Experimental data set is generated for varying viscosity values and flow rates. The variation of flow rate of continuous phase is observed here instead of dispersed phase. An automated computation routine is developed to read the droplet shape parameters considering the transient growth phase of droplets. The droplet size data is used to build and compare various AI models for predicting droplet sizes. A predictive model is developed, which is ready for automated closed loop control of the droplet generation.

Dimensional variation management is a major challenge in multi‐station sheet metal assembly processes involving complex products such as automotive body and aircraft fuselage assemblies. Very few studies have explored it at a preliminary design phase taking into consideration effects of part deformation on variation propagation, since early design phase involves the development of imprecise design models with scant or incomplete product and process knowledge. The objective of this paper is to present a variation model which can be built into the preliminary design phase taking into consideration all of the existing interactions between flexible parts and tools in multi‐station sheet metal assembly process.

The paper addresses this problem by first, presenting a beam‐based product and process model which shares the same data structure of the B‐Rep CAD models, and therefore can be embedded in CAD systems for automatic product skeletal design; second, determining the influence of part deformation, for various, differing joining and releasing schemes, on variation propagation; and third, utilizing this information to generate a vector‐based variation propagation model for multistation sheet metal assemblies.

This paper presents a beam‐based product and process model which shares the same data structure of the B‐Rep CAD models, and therefore can be embedded in CAD systems for automatic product skeletal design; determines the influence of part deformation, for various, differing joining and releasing schemes, on variation propagation; and utilizes this information to generate a vector‐based variation propagation model for multistation sheet metal assemblies.

A truck cab assembly is presented to demonstrate the advantages of the proposed model over the state‐of‐the‐art approach used in industry for sheet metal assemblies.

An important challenge of the osteotomy procedures, particularly in the case of large and complex corrections, is the fixation of the osteotomy site. The purpose of this study is to propose a practical and cost-effect methodology for the plate adapting problem of osteotomy surgery.

A novel patient-specific plate contouring methodology, based on rapid prototyping (RP) and multi-point forming (MPF) techniques, was developed and evaluated. In this methodology, a female mold is fabricated by RP, based on the geometry of the osteotomy site and estimation of the plate spring back. The mold is then used to configure a MPF die, which is then used for press forming of the factory-made locking plate. The applicability of the methodology was assessed in two case studies.

The results of implementing the methodology on a femoral and a tibial locking plate indicated very good conformity with the underlying bone, in both the frontal and sagittal planes. The surgical application of the pre-operatively contoured tibial plate facilitated the plate locating and screw inserting procedures, and provided a secure fixation for bone fragments.

The results are promising and provide a proof of concept for the feasibility and applicability of the proposed methodology in clinical practice, as a complementary to the existing surgical preplanning and patient-specific instrument preparations.

The advantageous features of RP and the MPF were used to provide a solution for the plate adapting problem of osteotomy surgery.

Material variation is inevitable in volume production, especially the sheet metal thickness variation, which influences part stiffness characteristic. The purpose of this paper is to present a new variation model of compliant sheet metal assembly with consideration of material variation influence.

The theory of computational solid mechanics is used to obtain the relationship between part stiffness matrix and material characteristic. The method of influence coefficients is adopted to deduce the assembly variation model.

Material variation‐induced influence coefficients to assembly variation are obtained, and a variation model of compliant sheet metal assembly with sources of material variations, part geometric variations and fixture variations is presented. Analysis shows that material variation has an important influence to assembly variations.

A quantitative relationship between assembly variations and material thickness variations is firstly given and a new variation model of compliant sheet metal assembly is presented to help designers to more exactly predict the assembly variation and diagnose variation sources.

The automotive industry is very interested in sheet metal forming simulation using numerical techniques such as the finite element method. A cooperative research program between the Stamping Division of FIAT Auto and the Mechanics Department of the Politecnico di Torino was established with the aim of exploring the present possibilities of these techniques. This paper deals with the simulation of the deep forming of an axisymmetrical component, the axisymmetry being characterized by a double curvature profile, and is considered to be the first feasibility study. A sheet was modelled by fournode axisymmetric elements; the punch, the die and the blankholder were modelled by gap elements. The metal sheet was free to move along the punch and the die edges, with a continuous variation of the boundary conditions. The highly non‐linear problem requires an adequate description through the carefully considered use of the appropriate options of the MARC package (release K2). Moreover, some subroutines were written ad hoc to complete the discretization. Results are presented as strain and stress histories during the stamping process and as total forming force exerted by the punch to deform the sheet. In addition the spring‐back phase was considered in order to calculate the back deformation and the residual stress. Lastly, a comparison of the behaviour obtained with two different kinds of steel are reported.