A novel Geometric feasibility method to perform assembly sequence planning through oblique orientations

Kumar, Gulivindala Anil; Bahubalendruni, M. V. A. Raju; Prasad, Vandana; Ashok, Dara; Sankaranarayanasamy, K.

doi:10.1016/j.jestch.2021.04.013

Cited by 27 publications

(23 citation statements)

References 45 publications

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“…According to Table 3, there are tool conflicts among Part 14, Part 18, and Part 30. The corresponding APD disassembly sequence can be expressed as K = fk 1 , k 2 , k 3 g: 32,22,23,25,36,21,35,20,34,31,19,10,12,13,11,9,38,8,30,18,40,37,14,26,16,29,24,27,28,39,7,17,2,4,3,1,5,6,15, 41…”

Section: Case Studymentioning

confidence: 99%

Asynchronous parallel disassembly sequence planning method of complex products using discrete multi-objective optimization

Qiu

Dong

Wang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part B:

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Disassembly is a necessary link to realize the integrity of product life cycle. Asynchronous Parallel Disassembly (APD) is an important way to achieve efficient disassembly. Due to the asynchronous start of disassembly tasks by operators in APD, the calculation complexity of disassembly sequence planning optimization increases more obviously with the increase of product complexity. Further, the disassembly sequence is a discrete numerical value, which is difficult to be efficiently realized by existing optimization algorithms. To overcome these difficulties, we introduced a complex products APD description. It helped to describe the APD problem with multiple disassembly resources. Based on the APD resources overall matrix, a three-objective, viz., the total disassembly time-consuming, the disassembly direction change times, and the disassembly tools replacement times, optimization model was constructed. To obtain the optimal disassembly planning sequence, the improved discrete NSGA-II (IDNSGA-II) was proposed, which introduced a novel population restart mechanism. The proposed method was verified in a bevel gearbox disassembly process from the EAS4633 rescue inspection equipment. The optimal results showed the APD sequence planning multi-objective optimized results obtained by the IDNSGA-II algorithm can be close to the single object optimized results. For the rest objects, the optimal solution obtained from the multi-objective genetic algorithm is obviously better.

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Section: Case Studymentioning

confidence: 99%

Asynchronous parallel disassembly sequence planning method of complex products using discrete multi-objective optimization

Qiu

Dong

Wang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…The input layer consists of neurons to which the input signals are sent to the first hidden layer. The set of input data is divided into three groups: (1) training data string that allows reflection on prediction tasks, (2) test data, which check the operation of the network, (3) verification data, which evaluate the network performance based on new, previously unused set of numerical data. The number of neurons and hidden layers is selected empirically, enabling a compromise between its extensive structure and the correct generalization of the processed data.…”

Section: Neural Network Assumptionsmentioning

confidence: 99%

“…One of the most important problems at this level is the determination of the most advantageous sequence [1][2][3][4][5] of the assembly and components of the production cycle but also the problem of assembly line balancing (ALB) in linear systems, which in principle are also part of activities occurring at the production process stage. These issues are fundamentally related to the degree of process automation but also to the production conditions in a given enterprise.…”

Section: Introductionmentioning

confidence: 99%

Assembly Sequence Planning Using Artificial Neural Networks for Mechanical Parts Based on Selected Criteria

Suszyński

Peta

2021

Applied Sciences

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The proposed model of the neural network describes the task of planning the assembly sequence on the basis of predicting the optimal assembly time of mechanical parts. In the proposed neural approach, the k-means clustering algorithm is used. In order to find the most effective network, 10,000 network models were made using various training methods, including the steepest descent method, the conjugate gradients method, and Broyden–Fletcher–Goldfarb–Shanno algorithm. Changes to network parameters also included the following activation functions: linear, logistic, tanh, exponential, and sine. The simulation results suggest that the neural predictor would be used as a predictor for the assembly sequence planning system. This paper discusses a new modeling scheme known as artificial neural networks, taking into account selected criteria for the evaluation of assembly sequences based on data that can be automatically downloaded from CAx systems.

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“…In, 34 Deepak and Raju proposed a path planning algorithm for an unmanned ground vehicle on a predefined structured environment. Further, Anil et al, 35 developed a novel geometric feasibility method for performing the assembly sequence planning operations through oblique orientations. The developed method was tested on real-time products and confirmed that the developed approach was successful in identifying the collision-free paths.…”

Section: Introductionmentioning

confidence: 99%

An efficient path planning algorithm for the biped robot in a static environment using fast sweeping method

Parappagoudar¹,

MANDAVA

Pandu

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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Generating a collision-free path for a biped walking machine/robot in an obstacle clustered environment is a challenging task. To overcome this difficulty, researchers around the world have implemented several collision-free path planning algorithms. It is significant to note that an efficient path-planning methodology helps the biped robot to achieve a collision-free path and minimize the distance of path travelled. In the current investigation, the authors have proposed a new path planning procedure, the Fast Sweeping Method (FSM), to obtain an optimal path for the biped robot in a static environment. In the present investigation, the authors have tested it in both simulations as well as on an actual biped robot in a static domain to check the effectiveness of the developed procedure. Further, the results of the current algorithm are compared with two established path planning algorithms, Fast Marching Method (FMM) and A-star algorithms. In the end, it has been observed that the proposed algorithm obtains the best collision-free optimal path when compared with the FMM and A-star algorithms.

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A novel Geometric feasibility method to perform assembly sequence planning through oblique orientations

Cited by 27 publications

References 45 publications

Asynchronous parallel disassembly sequence planning method of complex products using discrete multi-objective optimization

Asynchronous parallel disassembly sequence planning method of complex products using discrete multi-objective optimization

Assembly Sequence Planning Using Artificial Neural Networks for Mechanical Parts Based on Selected Criteria

An efficient path planning algorithm for the biped robot in a static environment using fast sweeping method

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