---

The most essential problem in lapping process is low material removal rate which leads to increase in production costs and time. Thus, in this process, it's essential to select a condition that besides producing pieces with required flatness and roughness, has a high material removal rate. In this research, effects of parameters such as abrasive particle size, abrasive particles concentration in slurry, and lapping pressure on material removal rate, flatness and surface roughness were studied by experimental method in single sided lapping of flat workpieces made of 440c steel. In the following, effect of aforementioned parameters on material removal rate, flatness and surface roughness of lapped surface has been modeled using artificial neural network. Finally, by exerting multi-objective particle swarm optimization, simultaneous optimization of material removal rate, surface roughness and flatness of lapping pieces has been conducted and related Pareto front has been obtained. Obtained results show that by using Multi-objective particle swarm optimization algorithm we can produce workpieces with required surface roughness and flatness with high material removal rate. Consequently, by using this method moreover producing workpieces with desired quality, production cost and time would decrease.

---

In this paper, optimal trajectories of soft landing on the Moon are designed based on different landing strategies. For this purpose, the problem of soft landing is defined as an optimal control problem to minimize fuel consumption and solved by a combinational direct method. The used solution method in this paper is a combination of direct collocation method, nonlinear programming, differential flatness and B-spline curves. In this method, by using differential flatness, dynamic equations of landing are expressed by the minimum number of state variables in the minimum dimensional space. Also, state variables are approximated by B-spline curves, and control points of these curves are considered as optimization variables of the nonlinear programming problem. By simultaneously using of differential flatness and B-spline curves, the number of variables and constraints of the optimal control problem decrease significantly and the problem is solved with high accuracy and speed. In the paper, three different strategies for soft landing on the Moon are investigated. These strategies are defined based on direct or indirect landing from the parking orbit and separation of horizontal braking and vertical descent phases. According to achieved optimal trajectories, by indirect landing from an intermediate orbit, the space vehicle can be landed on the Moon with the minimum fuel consumption. Also, by separation of horizontal braking and vertical descent phases, a more applicable landing trajectory can be achieved.