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This paper aims to provide a shimming method based on scanned data and finite element analysis (FEA) for a wing box assembly involving non-uniform gaps. The effort of the present work is to deal with gap compensation problem using hybrid shims composed of solid and liquid forms.

First, the assembly gaps of the mating components are calculated based on the scanned surfaces. The local gap region is extracted by the seed point and region growth algorithm from the scattered point cloud. Second, with the constraints of hole margin, gap space and shim specification, the optional shimming schemes are designed by the exhaustive searching method. Finally, the three-dimensional model of the real component is reconstructed based on the reverse engineering techniques, such as section lines and sweeping. Using FEA software ABAQUS, the stress distribution and damage status of the joints under tensile load are obtained for optimal scheme selection.

With the scanned mating surfaces, the non-uniform gaps are digitally evaluated with accurate measurement and good visualization. By filling the hybrid shims in the assembly gaps, the joint structures possess similar load capacity but stronger initial stiffness compared to the custom-shimmed structures.

This method has been tested with the interface data of a wing tip, and the results have shown good efficiency and automation of the shimming process.

The proposed method can decrease the manufacturing cost of shims, shorten the shimming process cycle and improve the assembly efficiency.

The purpose of this paper is to present an optimal posture evaluation model to control the assembly gaps in aircraft wing assembly. The gaps between two mating surfaces should be strictly controlled in precision manufacturing. Oversizing of gaps will decrease the dimensional accuracy and may reduce the fatigue life of a mechanical product. To reduce the gaps and keep them within tolerance, the relative posture (orientation and position) of two components should be optimized in the assembly process.

Based on the step alignment strategy, i.e. preliminary alignment and refined alignment, the concept of a small posture transformation (SPT) is introduced. In the preliminary alignment, an initial posture is estimated by a set of auxiliary locating points, with which the components can be quickly aligned near each other. In the refined alignment, the assembly gaps are calculated and the formulation of the gaps with component posture is derived by the SPT. A comprehensive weighted minimization model with gap tolerance constraints is established for redistributing the gaps in multi-regions. Powell-Hestenes-Rockafellar optimization, Singular Value Decomposition and K-Dimensional tree searching are introduced for the solution of the optimal posture for localization.

Using the SPT, the trigonometric posture transformation is linearized, which benefits the iterative solution process. Through the constrained model, overall gaps are minimized and excess gaps are controlled within tolerance.

This method has been tested with simulated model data and real product data, the results of which have shown efficient coordination of mating components.

This paper proposed an optimal posture evaluation method for minimizing the gaps between mating surfaces through component adjustments. This will promote the assembly automation and variation control in aircraft wing assembly.

The coal-fired power plants have been confronted with new operation challenge since the unified carbon trading market was launched in China. To make the optimal decision for the carbon emissions and power production has already been an important subject for the plants. Most of the previous studies only considered the market prices of electricity and coal to optimize the generation plan. However, with the opening of the carbon trading market, carbon emission has become a restrictive factor for power generation. By introducing the carbon-reduction target in the production decision, this study aims to achieve both the environmental and economic benefits for the coal-fired power plants to positively deal with the operational pressure.

A dynamic optimization approach with both long- and short-term decisions was proposed in this study to control the carbon emissions and power production. First, the operation rules of carbon, electricity and coal markets are analyzed, and a two-step decision-making algorithm for annual and weekly production is presented. Second, a production profit model based on engineering constraints is established, and a greedy heuristics algorithm is applied in the Gurobi solver to obtain the amounts of weekly carbon emission, power generation and coal purchasing. Finally, an example analysis is carried out with five generators of a coal-fired power plant for illustration.

The results show that the joint information of the multiple markets of carbon, electricity and coal determines the real profitability of power production, which can assist the plants to optimize their production and increase the profits. The case analyses demonstrate that the carbon emission is reduced by 2.89% according to the authors’ method, while the annual profit is improved by 1.55%.

As an important power producer and high carbon emitter, coal-fired power plants should actively participate in the carbon market. Rather than trade blindly at the end of the agreement period, they should deeply associate the prices of carbon, electricity and coal together and realize optimal management of carbon emission and production decision efficiently.

This paper offers an effective method for the coal-fired power plant, which is struggling to survive, to manage its carbon emission and power production optimally.

The purpose of this paper is to design a reasonable joining path and achieve assembly automation for multiple arc-shaped panels. A fuselage panel is primarily composed of skins, stringers, frames and clips. Both inserted and nested structures are adopted in the panels to improve the strength and hermeticity of the fuselage. Due to the complex structures and relationships, it is a challenge to coordinate the arc-shaped panels in the assembly process.

A motion sequence model which achieves arc approximation based on the relative motion of multiple panels is established. The initial position of the panels is obtained by decomposing the computer-aided design model of the panels. Two translation rules, i.e. progressively decreasing translation and limited deformation translation, are applied to determine the moving path of the panels. If a panel is not at its path node, a search algorithm is used to find the nearest path node. Finally, the key algorithms are implemented in an integration system to promote joining automation of multiple panels.

The zigzag path is effective for the joining of multiple panels with complex mating relationships. The automation of the join–separate–rejoin operations is time-saving and safety-assuring. The proposed method is demonstrated in practical engineering and a good efficiency is obtained.

This method has been used in a middle fuselage assembly project. The practical results show that the zigzag path is convenient to be stored and reused, and the synchronous movements of multiple curved panels are precisely realized. Additionally, the posture accuracy of panels is significantly improved, and the operating time is reduced considerably.

This paper gives a solution including path planning and process integration to solve the joining problem of multiple panels. The research will promote the automation of fuselage assembly.