Three-dimensional parametric contact analysis of planetary roller screw mechanism and its application in grouping for selective assembly

The planetary roller screw mechanism(PRSM)is a novel precision transmission mechanism that realizes the conversion between linear and rotary motions.The contact characteristics of helical surfaces directly determine PRSM’s performance in load-carrying capacity and transmission accuracy.Therefore,studying the contact characteristics of PRSM forms the fundamental basis for enhancing its transmission performance.In this study,a three-dimensional parametric analysis method of contact characteristics is proposed based on the PRSM meshing principle and PyVista(a high-level API to the Visualization Toolkit).The proposed method considers the influence of machining errors among various thread teeth.The effects of key machining errors on contact positions and axial clearance,as well as their sensitivities,are analyzed.With excellent solution accuracy,this method exhibits higher calculation efficiency and stronger robustness than the analytical and numerical meshing models.The influence of nominal diameter and pitch errors of the screw,roller,and nut on the axial clearance follows a linear relationship,whereas flank angle errors have negligible effects on the axial clearance.The corresponding influence coefficients for these three machining errors on the axial clearance are 0.623,0.341,and 0.036.The variations in contact positions caused by individual errors are axisymmetric.Flank angle errors and roller diameter errors result in linear displacements of the contact points,whereas pitch errors cause the contact points to move along the arc of the roller diameter.Based on the proposed threedimensional parametric contact characteristics analysis method,the Fuzzy C-Means clustering algorithm considering error sensitivity is utilized to establish a component grouping technique in the selective assembly of critical PRSM components,ensuring the rational and consistent clearances based on the given component’s machining errors.This study provides effective guidance for analyzing contact characteristics and grouping in selective assembly for PRSM components.It also presents the proposed method’s potential applicability to similar calculation problems for contact positions and clearances in other transmission systems.

Minimizing assembly variation in selective assembly for auto-body parts based on IGAOT

Purpose–Dimensional quality of sheet metal assemblies is an important factor for the final product.However,the part tolerance is not easily controlled because of the spring back deformation during the stamping process.Selective assembly is a means to decrease assembly tolerance of the assembly from low-precision components.Therefore,the purpose of this paper is to propose a fully efficient method of selective assembly optimization based on an improved genetic algorithm for optimization toolbox(IGAOT)in MATLAB.Design/methodology/approach–The method of influence coefficient is first applied to calculate the assembly variation of sheet metal components since the traditional rigid assembly variation model cannot be used due to welding deformation.Afterwards,the IGAOT is proposed to generate optimal selective groups,which consists of advantages of genetic algorithm for optimization toolbox(GAOT)and simulated annealing.Findings–The cases of two simple planes and the tail lamp bracket assembly are used to illustrate the flowchart of optimizing combinations of selective groups.These cases prove that the proposed IGAOT has better precision than that of GAOT with the same parameters for selective assembly.Originality/value–The research objective of this paper is to evaluate the changes from rigid bodies to sheet metal parts which are very complex for selective assembly.The method of IGAOT was proposed to the selected groups which has better precision than that of current optimization algorithms.

Error Modeling and Sensitivity Analysis of a Parallel Robot with SCARA(Selective Compliance Assembly Robot Arm) Motions

Parallel robots with SCARA（selective compliance assembly robot arm） motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parallelogram structures included by the robots as a link. As the established error model fails to reflect the error feature of the parallelogram structures, the effect of accuracy design and kinematic calibration based on the error model come to be undermined. An error modeling methodology is proposed to establish an error model of parallel robots with parallelogram structures. The error model can embody the geometric errors of all joints, including the joints of parallelogram structures. Thus it can contain more exhaustively the factors that reduce the accuracy of the robot. Based on the error model and some sensitivity indices defined in the sense of statistics, sensitivity analysis is carried out. Accordingly, some atlases are depicted to express each geometric error’s influence on the moving platform’s pose errors. From these atlases, the geometric errors that have greater impact on the accuracy of the moving platform are identified, and some sensitive areas where the pose errors of the moving platform are extremely sensitive to the geometric errors are also figured out. By taking into account the error factors which are generally neglected in all existing modeling methods, the proposed modeling method can thoroughly disclose the process of error transmission and enhance the efficacy of accuracy design and calibration.

Visible and selective gel assembly via covalent click chemistry

This study marks the birth of visible and selective click covalent assembly.It is achieved by amplifying orthogonal alkyne−azide click chemistry through interfacial multisite interactions between azide/alkyne functionalized polymer hydrogels.Macroscopic assembly of hydrogels via host−guest chemistry or noncovalent interactions such as electrostatic interactions has been reported.Unlike macroscopic supramolecular assembly,here we report visible and selective“click”covalent assembly of hydrogels at the macroscale.LEGO-like hydrogels modified with alkyne and azide groups,respectively,can click together via the formation of covalent bonds.Monomer concentration-dependent assembly and selective covalent assembly have been studied.Notably,macroscopic gel assembly clearly elucidates click preferences and component selectivity not observed in the solution reactions of competing monomers.

Population transcriptomics reveals a potentially positive role of expression diversity in adaptation

While it is widely accepted that genetic diversity determines the potential of adaptation,the role that gene expression variation plays in adaptation remains poorly known.Here we show that gene expression diversity could have played a positive role in the adaptation of Miscanthus lutarioriparius.RNA-seq was conducted for 80 individuals of the species,with half planted in the energy crop domestication site and the other half planted in the control site near native habitats.A leaf reference transcriptome consisting of 18,503 high-quality transcripts was obtained using a pipeline developed for de novo assembling with population RNA-seq data.The population structure and genetic diversity of M.lutarioriparius were estimated based on 30,609 genic single nucleotide polymorphisms.Population expression（Ep） and expression diversity（Ed）were defined to measure the average level and the magnitude of variation of a gene expression in the population,respectively.It was found that expression diversity increased while genetic Resediversity decreased after the species was transplanted from the native habitats to the harsh domestication site,especially for genes involved in abiotic stress resistance,histone methylation,and biomass synthesis under water limitation.The increased expression diversity could have enriched phenotypic variation directly subject to selections in the new environment.