Addressing the issues of surface machining quality and residual stress in small impellers, the outward opening integral small impeller was selected as the key research object, and the main evaluation indicators of the surface quality of the experiment were set as the surface roughness and residual stress. The finite element simulation technology was used to analyze how the process parameters can affect the residual stress and outer surface roughness of the small impeller. After obtaining the results, the genetic algorithm was used to optimize it to obtain the optimal combination of process parameters. The surface roughness is reduced by 34.2%, and the residual stress is reduced by 28.6%, and at the same time, proved the feasibility of the optimization of the process parameters. The numerical control machining test of the small impeller was carried out to verify the feasibility and accuracy of the process parameter optimization.

Straightening rolls used in aluminum strip production are progressively contaminated by metal particles and fine debris that adhere to their surfaces. Periodic polishing is therefore required to restore the surface condition of the rolls while avoiding excessive material removal or surface damage. This study developed an automated polishing machine for aluminum strip straightening rolls using the Theory of Inventive Problem Solving (TRIZ) as a systematic engineering-design framework. Two engineering problems were considered: achieving effective contaminant removal without degrading the roll surface and improving loading and unloading productivity without introducing excessive device complexity. The problems were formalized using TRIZ engineering parameters and a contradiction matrix, after which candidate inventive principles were screened according to the physical requirements of the polishing process. The contradiction matrix was therefore used as a candidate-generation tool and engineering screening as the selection criterion. Based on the resulting design requirements, the machine was configured with an abrasive-belt feed mechanism, a lifting mechanism, and an automated loading and unloading mechanism. A programmable logic controller, servo and stepper drives, and an abrasive-belt system were integrated to coordinate workpiece positioning and polishing. A physical prototype was fabricated and evaluated using a two-group comparative test against manual polishing. Surface roughness was measured at three axial positions using a Surftest SJ-210 portable surface roughness tester. In this workshop-scale comparison of three rolls per method, machine-polished rolls exhibited lower mean Ra values and markedly smaller scatter than manually polished rolls, with 0.075 ± 0.004 μm compared with 0.951 ± 0.179 μm. Workshop records indicate an increase in polishing throughput from approximately 55 to 165 rolls/month. All nine machine-polished measurements satisfied the workshop acceptance criterion of Ra ≤ 0.6 μm, whereas all nine manually polished measurements exceeded it. These observations support the engineering feasibility of the proposed machine architecture under the investigated conditions.

Addressing the problems of complex forms, low structurization and insufficient reliability of automatic acquisition of professional knowledge sources in the manufacturing industry, this paper proposes an improved multi-person collaborative knowledge acquisition method for professional fields. Drawing on the quality control concept of “three reviews and three proofs” in the publishing industry and combining the characteristics of professional knowledge acquisition tasks, this method constructs a knowledge acquisition process with the collaborative participation of editors and professionals. This paper designs a quality assurance mechanism from three dimensions, namely personnel quality, process quality and result quality; introduces triangular fuzzy numbers to evaluate personnel quality; and establishes a process quality control model under multi-level inspection. Taking the knowledge acquisition project of CNC Machining Manual as an example, 39 professionals completed large-scale professional knowledge processing tasks within 60 working days. Compared with the traditional manual knowledge acquisition method, under similar workload conditions, the proposed method reduces the task completion time by approximately 40% and improves knowledge quality by approximately 10%. The research results show that this method can enhance the organization, inspectability and result stability of the complex professional knowledge acquisition process, and is suitable for constructing vertical domain knowledge bases with high quality requirements.