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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.

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.

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.

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.

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.

The key control characteristics (KCCs) are very important to control dimensional quality of the final product. The purpose of this paper is to propose optimization algorithm and rules of design KCCs by optimizing KCCs of 2D and 3D workpieces based on equations and candidate locating points.

This paper analyzes optimization process of 2D and 3D rectangle workpieces based on equations and candidate locating points by using fruit fly optimization algorithm (FOA). For decreasing variables of the algorithm, the improved fruit fly optimization algorithm (IFOA) is presented. Moreover, the Euclidean norm of inverse Jacobian is used as the objective function of optimizing KCCs by comparing different objective functions. Finally, a case of side frame assembly is presented to illustrate design and optimization of KCCs through IFOA, and results show that the method proposed in this paper is efficient and precise.

The paper provides some reasonable conclusions for the design and optimization of KCCs.

This paper designs and optimizes KCCs of fixtures and parts to improve dimensional quality of the final product.

The purpose of this paper is to propose a new assembly variation analysis model to analyze assembly variation for sheet metal parts. The main focus is to analyze assembly processes based on the method of power balance.

Starting with issues in assembly variation analysis, the review shows the critical aspects of tolerance analysis. The method of influence coefficient (MIC) cannot accurately analyze the relationship between part variations and assembly variations, as the welding point is not a point but a small area. Therefore, new sensitivity matrices are generated based on the method of power balance.

Here two cases illustrate the processes of assembly variation analysis, and the results indicate that new method has higher accuracy than the MIC.

This study is limited to assembly variation analysis for sheet metal parts, which can be used in auto-body and airplane body.

This paper provides a new assembly variation analysis based on the method of power balance.

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.

This study aims to investigate the effect of countersunk rivet head dimensions on the fatigue performance of the riveted specimens of 2024-T3 alloy.

The relationship between rivet head dimensions and fatigue behavior was investigated by finite element method and fatigue test. The fatigue fracture of the specimens was analyzed by scanning electron microscopy.

A change of the rivet head dimensions will cause a change in the stress concentration and residual normal stress, the stress concentration near the rivet hole causes the fatigue crack source to be located on the straight section of the countersunk rivet hole and the residual normal stress can effectively restrain the initiation and expansion of fatigue cracks. The fatigue cycle will cause the rivet holes to produce different degrees of surface wear.

The fatigue life of the specimens with the height of the rivet head of 2.28 mm and 2.00 mm are similar, but the specimens with the height of the rivet head of 1.72 mm were far higher than the other specimens.

This paper aims to explore the possibility of converting the nitrile butadiene rubber (NBR) water-lubricated bearing material into a self-lubricating bearing material by the action of polytetrafluoroethylene (PTFE) particles and water lubrication.

A group of experimental studies was carried out on a ring-on-block friction test. The physical properties, tribological properties and interface structure of PTFE-NBR self-lubricating composites filled with different percentages of PTFE particles were investigated.

The experimental results indicated that the reduction in friction and wear is a result of the formation of the lubricating film on the surface of the composites. The lubricating film was formed of a large amount of PTFE particles continuously supplied under water lubrication conditions and the PTFE particles here can greatly enhance the load capacity and lubrication performance.

In this study, the tribological properties of PTFE particles added to the NBR water-lubricated bearing materials under water lubrication were investigated experimentally, and the research was carried out by a ring-on-block friction test. It is believed that this study can provide some guidance for the application of PTFE-NBR self-lubricating.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2020-0187/

This study aims to develop a new method to treat the numerical singularity at the critical nodes of two skew coordinates, and optimize the leakage of micro herringbone grooved journal bearings (MHGJBs) with this method.

A side leakage numerical algorithm is proposed by using the skew meshes with a virtual node (SMVN) method to evaluate the effects of groove angle, bank/groove ratio, groove depth and groove number on load capacity, friction and side leakage of MHGJB.

The SMVN method is effective in treating the numerical singularity at the critical nodes of two skew coordinates. Besides, a group of optimized parameters of micro herringbone groove is obtained which can not only minimize the side leakage but also improve the load capacity and friction force.

A virtual node method was proposed, which can significantly improve the calculation accuracy in the side leakage model.

Under the trend of global economic integration and the new context of stagflation, frequent fluctuations in international interest rates are exerting far-reaching impacts on the world economy. In this paper, the transmission mechanism of the impact of fluctuations in international interest rates (specifically, the American interest rate) on the bankruptcy risk in China's pillar industry, the construction industry (which is also sensitive to interest rates), is examined.

Using an improved contingent claims analysis, the bankruptcy risk of enterprises is calculated in this paper. Additionally, an individual fixed-effects model is developed to investigate the mediating effects of international interest rates on the bankruptcy risk in the Chinese construction industry. The heterogeneity of subindustries in the industrial chain and the impact of China's energy consumption structure are also analysed in this paper.

The findings show that fluctuations in international interest rates, which affect the bankruptcy risk of China's construction industry, are mainly transmitted through two major pathways, namely, commodity price effects and exchange rate effects. In addition, the authors examine the important impact of China's energy consumption structure on risk transmission and assess the transmission and sharing of risks within the industrial chain.

First, in the research field, the study of international interest rate risk is extended to domestic-oriented industries. Second, in terms of the research content, this paper is focused on China-specific issues, including the significant influence of China's energy consumption structure characteristics and the risk contagion (and risk sharing) as determined by the current development of the Chinese construction industry. Third, in terms of research methods a modified contingent claim analysis approach to bankruptcy risk indicators is adopted for this study, thus overcoming the problems of data frequency, market sentiment and financial data fraud, which are issues that are ignored by most relevant studies.

Environmental performance becomes a key issue for the sustainable development. Recently, incremental information technology is adopted to collect environmental data and improve environmental performance. Previous environmental efficiency measures mainly focus on individual decision-making units (DMUs). Benefited from the information technology, this paper develops a new environmental efficiency measure to explore the implicit alliances among DMUs and applies it to Xiangjiang River.

This study formulates a new data envelopment analysis (DEA) environmental cross-efficiency measure that considers DMUs' alliances. Each DMUs' alliance is formulated by the DMUs who are supervised by the same manager. In cross-efficiency evaluation context, this paper adopts DMUs' alliances rather than individual DMUs to derive the environmental cross-efficiency measure considering undesirable outputs. Furthermore, the Tobit regression is conducted to analyze the influence of exogenous factors about the environmental cross-efficiency.

The findings show that (1) Chenzhou performs the best while Xiangtan performed the worst along Xiangjiang River. (2) The environmental efficiency of cities in Xiangjiang River is generally low. Increasing public budgetary expenditure can improve environmental efficiency of cities. (3) The larger the alliance size, the higher environmental efficiency. (4) The income level is negatively correlated with environmental efficiency, indicating that the economy is at the expense of the environment in Xiangjiang River.

This paper contributes to developing a new environmental DEA cross-efficiency measure considering DMUs' alliance, and combining DEA cross-efficiency and Tobit regression in environmental performance measurement of Xiangjiang River. This paper examines the exogenous factors that have influences on environmental efficiency of Xiangjiang River and derive policy implications to improve the sustainable operation.