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The purpose of this paper is to explore the impact of using computers to obtain information on the farm household’s production and consumption based on a field survey of farm households in the northern China.

The most important methods applied are instrumental variable (IV) method and propensity score matching (PSM) method. Estimators of IV, PSM and nearest neighborhood matching approaches are considered together to check the robustness of empirical results.

This paper careful impact evaluation results suggest that the use of computer not only improves the size of arable land rented in but also reduces family labor input intensity and the probability of selling agricultural outputs at farm-gate markets. Moreover, it also stimulates transportation, garment, housing and insurance expenditures per capita.

The database of this research comprises cross-section data, which does not support a cross-time comparison.

These results imply that it is vital to expand the coverage of computer use in rural areas. This may suggest that the importance of improving computer access is crucial for stimulating rural consumption increase. Furthermore, the need for the expansion of internet network coverage in western areas is also of importance.

First, the authors directly estimate computer usage impacts on a broader range of production and consumption indicators by including land-relative investments, variable investments, labor input and household’s expenditure and provide rigorous impact evaluations on the impact of access to computer. Second, the authors use IV and PSM methods to correct self-selection bias, going beyond the single equation approach in other studies. This enables us to identify the causal relationship between computer usage and farmer’s production and consumption decisions.

The purpose of this paper is to assess how spatial heterogeneity and production diversification have affected the efficiency of households participating in the SLCP.

Based on household survey data collected from three sample counties in the Loess Plateau region, the paper analyzes how spatial heterogeneity and business diversification have affected the production efficiency of households participating in the SLCP. Using four-step bootstrap, input stochastic distance frontiers of multi-inputs and multi-outputs are developed simultaneously with a technical efficiency effects model in which participating in the SLCP is treated as an exogenous variable.

The household production in the three counties is constrained by land, labor, capital, and fixed inputs; thus, it is germane to using a multi-input and multi-output household production technology to evaluate the SLCP. However, the relative importance of each input and output, the productive diversification, and the technological structure are differentiated in the three counties; estimating the regression with pooled data appears to conceal the influences of local factors and blur the specific divergence, compared to running county-based, separate regressions.

The effects of the SLCP on farm household production are location dependent. It is necessary to include spatial heterogeneity within public policy evaluation. In addition to suggesting localized and differentiated schemes of subsidy, this implies that the government may provide means to facilitate different regions to make the economic transition.

This paper intends to make two contributions. First, the analysis will capture and explain the adjustments induced by the SLCP in off-farm and other activities for entire household production, and special attention is given to the diversification of household production outputs. Second, this analysis sheds new light to the significance of spatial differentiation in mediating the effectiveness of a public policy or program.

The study aims to fabricate large metal components with overhangs built on cylindrical or conical surfaces with a high dimensional precision. It proposes methods to address the problems of generating tool-paths on cylindrical or conical surfaces simply and precisely, and planning the welding process on these developable surfaces.

The paper presents the algorithm of tool-paths planning on conical surfaces using a parametric slicing equation and a spatial mapping method and deduces the algorithm of five-axis transformation by addressing the rotating question of two sequential points. The welding process is investigated with a regression fitting model on a flat surface, and experimented on a conical surface, which can be flattened onto a flat surface.

The paper provides slicing and path-mapping expressions for cylindrical and conical surfaces and a curvature-speed-width (CSW) model for wire and arc additive manufacturing to improve the surface appearances. The path-planning method and CSW model can be applied in the five-axis fabrication of the prototype of an underwater thruster. The CSW model has a confidence coefficient of 98.02% and root mean squared error of 0.2777 mm. The reverse measuring of the finished blades shows the residual deformation: an average positive deformation of about 0.5546 mm on one side of the blades and an average negative deformation of about −0.4718 mm on the other side.

Because of the chosen research approach, the research results may lack generalizability for the fabrication based on arbitrary surfaces.

This paper presented an integrated slicing, tool-path planning and welding process planning method for five-axis wire and arc additive manufacturing.

Large-scale aircraft parts usually with many frame features, which consist of intersections. Profile and tensile properties of junctions in wire and arc additive manufacturing (WAAM) are significantly affected by path strategies. The purpose of this paper is to propose a novel path strategy for intersections in WAAM and compare it with commonly used ones.

Three typical intersections including T crossing (TC), square crossing (SC) and arbitrary-angle crossing (AAC) were built up with two commonly used path strategies (parallel and oscillation) and a proposed method named end lateral extension (ELE) which extends the weld track along the crossed direction. A robotic system and cold metal transfer (CMT) process were used to deposit Al-6.3Cu (2319) alloy. The profile of the bead was scanned by laser vision sensor. Tightened ratio (r), inter-layer height increment (Δh) and deviation to the fitting plane (d_f) are calculated based on the point cloud. Tensile tests were done for all built intersections.

Comparison to the commonly used path strategies, the proposed ELE method eliminated the tightened defects at the intersection, achieved a more stable inter-layer height increment (Δh) and improved the profile quality with a lower deviation to the fitting plane (d_f). Tensile tests show that the proposed strategy has exhibited favorable tensile properties.

In this paper, a novel path strategy named ELE is proposed, which provides a new path choice for fabricating intersections by WAAM.

The modeling and optimization of a weld bead in the middle of the weld are often simple, as the forming process is dynamically balanced. However, the arc striking (AS) and arc extinguishing (AE) areas of weld beads are generally abnormal because the dynamic processes at these areas are unstable. The purpose of this paper is to investigate the abnormal areas of the weld bead with optimization modeling methods in wire and arc additive manufacturing (WAAM).

A burning-back method was proposed to fill the slanted plane in the AE area. To optimize the welding parameters and obtain the optimal design, a response surface methodology was proposed to build the relationships between the input parameters and response variables.

The proposed burning-back method could fill the slanted plane in the AE area. Second-order models of abnormal areas were developed and the optimization effects were analyzed. The experimental results indicated that the relationship models at both ends were applicable and preferable for the optimization of weld beads.

In this paper, a burning-back method was proposed to optimize the slanted plane in the AE area. Second-order models of abnormal areas were established. The methods and models were preferable in the optimization of the abnormal areas in WAAM.

This paper aims to summarize the influence law of hybrid deposited and micro-rolling (HDMR) technology on the shaping strain and residual stress. And the rolling parameters combination was further optimized to guide the actual production.

This paper proposed a three-dimensional coupled thermo-mechanical model of the HDMR process. The validated model is used to investigate the influences of rolling parameters on stress and plastic strain (the distance between the energy source and roller [D_e–r], the rolling compression [c_r] and the friction coefficient [f_r]). The orthogonal optimization of three factors and three levels was carried out. The influence of rolling parameters on the plastic strain and residual stress is analyzed.

The simulation results show that HDMR technology can effectively increase the shaping strain of the weld bead and reduce the residual tensile stress on the weld bead surface. Furthermore, the influence of rolling parameters on stress and strain is obtained by orthogonal analysis, and the corresponding optimal combination is proposed. Also, the rolling temperature significantly affects the residual stress, and the rolling reduction has a substantial effect on the plastic deformation.

Owing to the choice of research methods, this paper failed to study microstructure evolution.

This paper provides a reference principle for the optimal selection of rolling parameters in HDMR.

The major problem that limits the widespread use of WAAM technology is the forming quality. However, most of the current research focuses on post-process detections that are time-consuming, expensive and destructive. This paper aims to achieve the on-line detection and classification of the common defects, including hump, deposition collapse, deviation, internal pore and surface slag inclusion.

This paper proposes an in-process multi-feature data fusion nondestructive testing method based on the temperature field of the WAAM process. A thermal imager is used to collect the temperature data of the deposition layer in real-time. Efficient processing methods are proposed in this paper, such as the temperature stack algorithm, width extraction algorithm and a classification model based on a residual neural network. Some features closely related to the forming quality were extracted, containing the profile image and width curve of the deposition layer and abnormal temperature features in longitudinal and cross-sections. These features are used to achieve the detection and classification of defects.

Thermal non-destructive testing is a potentially superior technology for in-process detection in the industrial field. Based on the temperature field, extracting the most relevant features of the defect information is crucial. This paper pushes current infrared (IR) monitoring methods toward real-time detection and proposes an in-process multi-feature data fusion non-destructive testing method based on the temperature field of the WAAM process.

In this paper, the single-layer and multi-layer WAAM samples are preset with various defects, such as hump, deposition collapse, deviation, pore and slag inclusion. A multi-feature nondestructive testing methodology is proposed to realize the in-process detection and classification of the defects. A temperature stack algorithm is proposed, which improves the detection accuracy of profile change and solves the problem of uneven temperature from arc striking to arc extinguishing. The combination of residual neural network greatly improves the accuracy and efficiency of detection.