Gramian-constrained optimization process for the stiffness model identification of industrial manipulators

Robotica ◽  
2021 ◽  
pp. 1-18
Author(s):  
W. R. Oliveira ◽  
L. G. Trabasso
Keyword(s):  
Industrial Robot ◽  
Linear Optimization ◽  
Model Identification ◽  
Optimization Method ◽  
Optimization Process ◽  
Matrix Formulation ◽  
Reduction Techniques ◽  
Stiffness Matrices ◽  
Stiffness Model ◽  
Industrial Manipulators

Abstract This work deals with the elastostatic identification of industrial manipulators. By reviewing the basics of the physical elastic properties of both links and joints in the framework of the lumped stiffness modeling techniques, the Gramian nature of the stiffness matrices has been found out adequate to do so. Then, a novel optimization method has been developed, which incorporates the Gramian matrix formulation along a non-linear optimization process, acting as an intrinsic constraint for the conservativeness of the elastostatic modeling. Numerical and experimental analyses evince the effectiveness of the proposed method, as the elastostatic models obtained by means of the proposed technique predict more than 93.7% of the compliance deviations of a real industrial robot. The proposed method is simple enough to be jointly applicable to the most recent elastostatic model reduction techniques.

Cable-path optimization method for industrial robot arms

2022 ◽  
Vol 73 ◽  
pp. 102245
Author(s):  
Shintaro Iwamura ◽  
Yoshiki Mizukami ◽  
Takahiro Endo ◽  
Fumitoshi Matsuno
Keyword(s):  
Industrial Robot ◽  
Optimization Method ◽  
Path Optimization ◽  
Robot Arms

Shape-design optimization of hull structures considering thermal deformation

2013 ◽  
Vol 228 (13) ◽  
pp. 2266-2277
Author(s):  
Myung-Jin Choi ◽  
Min-Geun Kim ◽  
Seonho Cho
Keyword(s):  
Optimal Design ◽  
Design Optimization ◽  
Thermal Deformation ◽  
Parametric Design ◽  
Optimization Method ◽  
Optimization Process ◽  
Design Parameters ◽  
Shape Design ◽  
Shape Design Optimization ◽  
Modified Method

We developed a shape-design optimization method for the thermo-elastoplasticity problems that are applicable to the welding or thermal deformation of hull structures. The point is to determine the shape-design parameters such that the deformed shape after welding fits very well to a desired design. The geometric parameters of curved surfaces are selected as the design parameters. The shell finite elements, forward finite difference sensitivity, modified method of feasible direction algorithm and a programming language ANSYS Parametric Design Language in the established code ANSYS are employed in the shape optimization. The objective function is the weighted summation of differences between the deformed and the target geometries. The proposed method is effective even though new design variables are added to the design space during the optimization process since the multiple steps of design optimization are used during the whole optimization process. To obtain the better optimal design, the weights are determined for the next design optimization, based on the previous optimal results. Numerical examples demonstrate that the localized severe deviations from the target design are effectively prevented in the optimal design.

Simulation-Based Hybrid Optimization Method for the Digital Twin of Garment Production Lines

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Woo-Kyun Jung ◽  
Young-Chul Park ◽  
Jae-Won Lee ◽  
Eun Suk Suh
Keyword(s):  
Expert Knowledge ◽  
Structural Characteristics ◽  
Optimization Method ◽  
Hybrid Optimization ◽  
Optimization Process ◽  
Production Lines ◽  
Distribution Method ◽  
Workload Analysis ◽  
Hybrid Optimization Method ◽  
Simulation Based

AbstractImplementing digital transformation in the garment industry is very difficult, owing to its labor-intensive structural characteristics. Further, the productivity of a garment production system is considerably influenced by a combination of processes and operators. This study proposes a simulation-based hybrid optimization method to maximize the productivity of a garment production line. The simulation reflects the actual site characteristics, i.e., process and operator level indices, and the optimization process reflects constraints based on expert knowledge. The optimization process derives an optimal operator sequence through a genetic algorithm (GA) and sequentially removes bottlenecks through workload analysis based on the results. The proposed simulation optimization (SO) method improved productivity by ∼67.4%, which is 52.3% higher than that obtained by the existing meta-heuristic algorithm. The correlation between workload and production was verified by analyzing the workload change trends. This study holds significance because it presents a new simulation-based optimization model that further applies the workload distribution method by eliminating bottlenecks and digitizing garment production lines.

scholarly journals Fast Quadratic Shape From Shading With Unknown Light Direction

2021 ◽  
Author(s):  
Kuros Yalpani
Keyword(s):  
Linear Optimization ◽  
Quadratic Function ◽  
Optimization Method ◽  
Shape From Shading ◽  
Surface Patch ◽  
Algebraic Complexity ◽  
Surface Patches ◽  
Quadratic Surface ◽  
Least Squares Optimization ◽  
Light Source Direction

An algorithm is proposed that extracts 3D shape from shading information in a digital image. The algorithm assumes that there is only a single source of light producing the image, that the surface of the shape giving rise to the image is Lambertian (matte) and that its shape can be locally approximated by a quadratic function. Previous work shows that under these assumptions, robust shape from shading is possible, though slow for large images because a non-linear optimization method is applied in order to estimate local quadratic surface patches from image intensities. The work presented here shows that local quadratic surface patch estimates can be computed, without prior knowledge of the light source direction, via a linear least squares optimization, thus greatly improving the algebraic complexity and run-time of this existing algorithms.

An Applied Analytics Approach for Facility Location Optimization in Logistics With Actionable Insights for Logistics Managers

2021 ◽  
pp. 124-138
Author(s):  
Vala Ali Rohani ◽  
Flavio Guerreiro ◽  
Tiago Pinho
Keyword(s):  
Optimization Algorithm ◽  
Linear Optimization ◽  
Distribution Networks ◽  
Facility Management ◽  
The Other ◽  
Optimization Process ◽  
Logistic Distribution ◽  
Location Optimization ◽  
Logistics Networks ◽  
Data Driven Decisions

The structure of logistic distribution networks is one of the most strategic topics in industrial facility management. This study aims to optimize the logistics structure of the LPR company in Portugal by utilizing the applied analytics methods. In doing so, both locations of facilities and structure of the logistics networks were considered as the target of the optimization process. After analyzing the 12-month historical data of the studied company with more than 8,000 customers and drop points, the optimized logistics structure and warehouse locations were determined that could deduct the logistics costs by 22%. To this end, a linear optimization algorithm was developed to identify the optimum logistic structure among more than 20 million possible network configurations. The proposed solution is applicable in the other industries with logistics operations, helping the managers to make data-driven decisions.

scholarly journals Optimization of Deflection of a Big NEO through Impact with a Small One

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Kaijian Zhu ◽  
Weiping Huang ◽  
Yuncai Wang ◽  
Wei Niu ◽  
Gongyou Wu
Keyword(s):  
Small Body ◽  
Optimization Method ◽  
Optimization Process ◽  
Earth Object

Using a small near-Earth object (NEO) to impact a larger and potentially threatening NEO has been suggested as an effective method to avert a collision with Earth. This paper develops a procedure for analysis of the technique for specific NEOs. First, an optimization method is used to select a proper small body from the database. Some principles of optimality are achieved with the optimization process. Then, the orbit of the small body is changed to guarantee that it flies toward and impacts the big threatening NEO. Kinetic impact by a spacecraft is chosen as the strategy of deflecting the small body. The efficiency of this method is compared with that of a direct kinetic impact to the big NEO by a spacecraft. Finally, a case study is performed for the deflection of the Apophis NEO, and the efficiency of the method is assessed.

Shuffled shepherd optimization method: a new Meta-heuristic algorithm

2020 ◽  
Vol 37 (7) ◽  
pp. 2357-2389 ◽  
Author(s):  
Ali Kaveh ◽  
Ataollah Zaerreza
Keyword(s):  
Heuristic Algorithm ◽  
Optimization Algorithm ◽  
Design Methodology ◽  
Optimization Method ◽  
Optimization Process ◽  
Heuristic Optimization ◽  
Benchmark Problems ◽  
Content Type

Purpose This paper aims to present a new multi-community meta-heuristic optimization algorithm, which is called shuffled shepherd optimization algorithm (SSOA). In this algorithm. Design/methodology/approach The agents are first separated into multi-communities and the optimization process is then performed mimicking the behavior of a shepherd in nature operating on each community. Findings A new multi-community meta-heuristic optimization algorithm called a shuffled shepherd optimization algorithm is developed in this paper and applied to some attractive examples. Originality/value A new metaheuristic is presented and tested with some classic benchmark problems and some attractive structures are optimized.

Optimization of Radial Cams with Translating Roller Follower through Genetic Algorithms

2015 ◽  
Vol 783 ◽  
pp. 83-94
Author(s):  
Alberto Borboni
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Contact Pressure ◽  
Optimization Problem ◽  
Optimization Method ◽  
Optimization Process ◽  
Radius Of Curvature ◽  
Design Problems ◽  
Computational Optimization ◽  
Different Types

In this work, the optimization problem is studied for a planar cam which rotates around its axis and moves a centered translating roller follower. The proposed optimization method is a genetic algorithm. The paper deals with different design problems: the minimization of the pressure angle, the maximization of the radius of curvature and the minimization of the contact pressure. Different types of motion laws are tested to found the most suitable for the computational optimization process.

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