Directed energy deposition is a typical laser remanufacturing technology, which can effectively repair failed parts and extend their service life, and has been widely used in aerospace, metallurgy, energy and other high-end equipment key parts remanufacturing. However, the repair quality and performance of the repaired parts have been limited by the morphological and quality control problems of the process because of the formation mechanism and process of the deposition. The main reason is that the coupling of multiple process parameters makes the deposited layer morphology and surface properties difficult to be accurately predicted, which makes it difficult to regulate the process. Thus, the deposited layer forming mechanism and morphological properties of directed energy deposition were systematically analyzed, the height and width of multilayer deposition layers were taken as prediction targets, and a PSO-BP-based model for predicting the morphology of directed energy deposited layers was settled. The weights and thresholds of Back Propagation (BP) neural networks were optimized using a Particle Swarm Optimization (PSO) algorithm, the predicted values of deposited layer morphology for different process parameters were obtained, and the problem of low accuracy of deposited layer morphology prediction due to slow convergence and poor uniformity of the solution set of traditional optimization models was addressed. Remanufacturing experiments were conducted, and the experimental results showed that the deposited layer morphology prediction model proposed in this paper has a high prediction accuracy, with an average prediction error of 1.329% for the layer height and 0.442% for the layer width. The research of the paper provided an effective way to control the morphology and properties of the directed energy deposition process. A valuable contribution is made to the field of laser remanufacturing technology, and significant implications are held for various industries such as aerospace, metallurgy, and energy.

When quality assurance is used in customization production mode, the most critical problem is how to maintain stable product quality and meet the customer individualized requirements constantly, quality management system model of customization based customer satisfaction is set up, collaborative quality design, production process quality management, application and service quality management and quality evaluation etc., the key functions in the model, are analyzed in detail. More over the evaluation method of customization product quality is studied. The quality management prototype system of individualized customization based customer satisfaction is developed, which is used in some Heavy Machinery Ltd., and verified rationality and validity.

Under harsh conditions involving high temperatures and severe abrasion, the copper plates of continuous casting crystallizers are highly susceptible to wear failure and thermal cracking. In this study, a Ni60AA transition layer is applied onto the copper plate via laser cladding to enhance the interfacial bonding properties. To further reinforce the coating, TiB₂ is incorporated into the nickel-based transition layer, leading to a significant improvement in overall performance. With the addition of 3 wt.% TiB₂ and 0.5% Y₂O₃, the coating microstructure undergoes notable refinement: coarse columnar grains transform into fine equiaxed grains, and the microhardness reaches 1225.3 HV0.1. The coating demonstrates excellent wear resistance, exhibiting a minimal wear depth of 97.09 μm, a low weight loss of 0.0089 g, and a stable friction coefficient of 0.32. By synergistically optimizing the transition layer and incorporating TiB₂, this study successfully enhances the surface strength and wear resistance of the crystallizer copper plate, offering a reliable technical approach for extending the service life of continuous casting crystallizers.