In this study, an interfacial slip model including the limiting shear stress is proposed and applied to the thermal elastohydrodynamic lubrication (EHL) analysis of a helical gear pair. The main difference between the proposed model and the classical EHL model is that, the term of entrainment velocity in Reynolds equation is modified. The influences of interfacial slip, thermal effect, initial limiting shear stress and operating conditions on the tribological properties are evaluated. Due to the interfacial slip, the pressure distribution moves towards the inlet region, and the fluctuation distributions of entrainment velocity and film thickness are similar to the trigonometric function. The influence of thermal effect on interfacial slip cannot be ignored, especially in the case of high speed and heavy load. As the input torque and input rotational speed increase, the interfacial slip gradually extends to the whole meshing process.
The multi-objective optimization problem includes plate nesting, production planning, scheduling, and equipment capacity optimization in the complex manufacturing process of metal structures. For the best optimization results, a global collaborative optimization of the manufacturing system is necessary. A multi-objective optimization model for optimized nesting, optimized scheduling, dispatch optimizing, and equipment load balancing is constructed, and an improved hierarchical genetic algorithm is then developed for a better solution. A hierarchical structure of three chromosomes is designed in this algorithm. The algorithm can be used to simultaneously solve the layout selection, process sequencing, and machine selection problems. The algorithm shortens the production cycle, reduces the number of work in process, and improves equipment utilization through the application of collaborative optimization. The computational result and comparison prove that the presented approach is quite effective to address the considered problem.
An integrated approach is put forward to solve the combined cut planning and nesting problem for metal structures manufacturing. In this article, a three-stage solution procedure is framed, which involves dividing the cutting parts into several groups by rules, generating different layouts or patterns in different strategy, and selecting apt cutting patterns. As some layouts with less trim-loss may lead to high setup cost and high stock level, a multiobjective mathematical model, which takes into account the trim-loss, setup cost, labor cost, and their tradeoffs, is developed. Furthermore, a method with ant colony optimization for solving the mathematical model is proposed. The key research of this article is to focus on the nesting problem by using parallel optimization on a variety of steel plates and choosing an apt cutting pattern by weighing the trim-loss, setup cost, and labor cost. The computational results and comparison prove that the presented approach is quite effective for solving the problem.
With the popularization of small batch production, the main cutting method for sheet metal parts has changed. Laser cutting has become the main production method for coil material cutting. Developing an irregular part nesting method for the continuous cutting of coil material is urgent. Based on the coil material cutting process, this paper proposes an intelligent approach for the unit nesting problem of coil material. Firstly, a unit nesting model of coil material was constructed. Secondly, an intelligent approach using an improved marine predator algorithm was used to solve this model. In solving the model, the minimum nesting unit was continuously updated by changing the position, angle, and quantity of the nesting parts. Thirdly, the geometric characteristics of this minimum nesting unit were extracted. Finally, the nesting units for production were obtained using a single row or opposite row of the minimum nesting unit. The computational results and comparison prove that the presented approach is feasible and effective in improving material utilization, reducing production costs, and meeting the requirements of the production site.
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