Coating matching design is one of the important parts of ship coating process design. The selection of coating matching is influenced by various factors such as marine corrosive environment, anti-corrosion period and working conditions. There are also differences in the coating performance requirements for different ship types and different coating parts. At present, the design of coating matching in shipyards depends on the experience of technologist, which is not conducive to the scientific management of ship painting process and the macro control of ship construction cost. Therefore, this paper proposes a hybrid algorithm of fuzzy comprehensive evaluation and collaborative filtering based on user label improvement (IFCE-CF). Based on the analytic hierarchy process (AHP), the evaluation index system of coating matching is constructed, and the weight calculation process of fuzzy comprehensive evaluation is optimized by introducing the user label weight. The collaborative filtering algorithm based on matrix decomposition is used to realize the accurate recommendation of coating matching. Historical coating process data of a shipyard between 2010 and 2020 are selected to verify the recommendation ability of the method in the paper. The results show that using the coating matching intelligent recommendation algorithm proposed in this paper, the root mean square error is < 1.02 and the mean absolute error is < 0.75, the prediction accuracy is significantly better than other research methods, which proves the effectiveness of the method.

The setting of rolling schedule in tandem cold mill is one of the most crucial contents in rolling process, which will have a direct impact on product quality and production e ciency. According to the actual requirements in the rolling process, a multiobjective function based on in uence function method was built. The objective function was aimed specially at thin gauge strip and solved by Tabu search algorithm. Meanwhile, in order to avoid strip slipping by the reduction of friction coe cient, the tension schedule was corrected according to the rolling length of work roll. The proposed optimization method was successfully applied to a 1450-mm 5-stand tandem cold mill. Application results show that the optimized rolling schedules are more close to the actual requirements and the atness quality is improved greatly.

In cold strip rolling control system, rolling force and forward slip are the prerequisites for the model setting calculation, and the deformation resistance and friction coefficient are the main parameters that affect their predictions. A new method based on objective function is first proposed in this paper to improve the calculation accuracy of rolling force and forward slip, and the deformation resistance and friction coefficient are taken as optimisation variables. Using the multi-population co-evolutionary algorithm to solve the objective function, the required rolling force and forward slip are obtained. The pre-set values of rolling force and roller line speed are compared with the actual measured ones in a 1450 mm five-stand tandem cold mill and other researcher's method. Results show that the calculated values are in fair agreements with the on-line measured ones, and the thickness and flatness accuracy of the final product are improved.

The painting process is an essential part of the shipbuilding process. Its quality is directly related to the service life and maintenance cost of the ship. Currently, the design of the painting process relies on the experience of technologists. It is not conducive to scientific management of the painting process and effective control of painting cost. Therefore, an intelligent design algorithm for the ship painting process is proposed in this paper. Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is used to form categories of painting objects by cluster analysis. The grey wolf optimization (GWO) is introduced to realize the adaptive determination of clustering parameters and avoid the deviation of clustering results. Then, a painting object classification model is constructed based on the random forest (RF). Finally, the recommendation of the painting process is realized based on the multi-objective evaluation function. Effectiveness is verified by taking the outer plate above the waterline of a shipyard H1127/7 as the object. The results show that the performance of DBSCAN is significantly improved. Furthermore, the accurate classification of painting objects by RF is achieved. The experiment proves that the dry film thickness qualification rate obtained by the painting process designed by IDBSCAN-RF is 92.3%, which meets the requirements of the performance standard of protective coatings (PSPC).

Under the background of industry 4.0, advanced strip control process is a central part of rolling intelligent manufacturing. In the mainstream rolling control process, the work roll bending and the intermediate roll bending are turned on at the same time. Both stepwise methods and alternative methods are conducted by sacrificing adjustment ability. In this paper, the dimension of influencing factors is increased by considering adjustment direction as constraint operator. In the rolling control process, a new intelligent assignation strategy of collaborative optimization based on artificial neural networks and Topkis-Veinott has been proposed. In AINTV collaborative optimization, the thought patterns of searching and the thought patterns of learning are combined. Five field test experiments are conducted and the flatness in different rolling stages and in different strip area is analyzed. Keywords Rolling control process Á Artificial neural networks Á Intelligent manufacturing Á Collaborative optimization Á Calculation of bending force

No abstract

Purpose In the process of cold rolled strip, there is tight coupling between flatness control and gauge control. The variation of the roll gap caused by the change of bending force will lead to the change of rolling force. Furthermore, it can cause a deep impact on the control accuracy of strip exit thickness and exit crown. The purpose of this paper is to improve the accuracy of the bending force preset value for cold rolled strip. Design/methodology/approach In this paper, the bending force preset control strategy with considering of rolling force was proposed for the first time and the preset objective function of bending force was established on the basis of the two-objective optimization of bending force and rolling force. Meanwhile, the multi-objective intelligent algorithm – INSGA-II – was used to solve the objective function. Findings The proposed bending force multi-objective preset model has been tested in a 1,450 mm tandem cold rolling line. The analyzed results of field data show that the deviations of strip exit thickness and exit crown are reduced effectively by using the improved model, and at the same time, more reasonable bending force preset values are obtained, which can enhance the accuracy of flatness preset control. Originality/value A preset model of bending force with considering flatness and gauge is proposed in this paper and the multi-objective function of bending force preset is established on the basis of the two-objective optimization of bending force and rolling force. The value lies in proposing a new decoupling method of rolling force and bending force.

Purpose The purpose of this study is to improve the global optimization ability of the Tabu search (TS) algorithm, and then improve the calculation efficiency and accuracy of rolling schedule in tandem cold rolling. Design/methodology/approach A case-based reasoning–Tabu search hybrid algorithm (CBRTS) has been presented. First, the case-based reasoning technology was adopted to obtain high-quality initial solution and then the TS algorithm was used for global optimization. Findings The optimization effect of CBRTS is compared with that of the traditional TS algorithm, and the analysis result indicates that the CBRTS has a faster convergence rate than TS, and the optimization results are closer to the global optimal. Meanwhile, the rolling schedule calculated by CBRTS is more reasonable, which can increase the production efficiency while giving full play to the capacity of equipment. Originality/value A CBRTS hybrid algorithm is presented. The strong dependence of the TS algorithm on the initial solution has been solved. The rolling schedule multi-objective optimization functions are established. The proposed algorithm is applied in a 1,450-mm tandem cold rolling production line. The improved method can reduce about half the iterations compared with the traditional one.