Planning and analysis of mechanical assembly sequences in design engineering – Part I: The Method

Sąsiadek, Michał

doi:10.17559/tv-20130428110530

Cited by 7 publications

(7 citation statements)

References 6 publications

(11 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Network Definition Matrix (NDM) size is initially encoded in a chromosome with data. The [17] Assembler Encoding Programme (AEP) can then change the size of the NDM using the ADDN and DELN operations (as shown in Figure 5). This method enables the NDM and, in turn, the Artificial Neural Network (ANN) to be dynamically adjusted.The ANN's existing connections are unaffected as a result of the ADDN operation's addition of new neurons to the network.…”

Section: Methodology 1 Neural Network Assumptionsmentioning

confidence: 99%

Evolutionary approach in Assembler by Implementation of Neural Networks

Verma¹

2021

MSEA

View full text Add to dashboard Cite

A neural network is represented using the Assembler Encoding approach as a straightforward computer programme called the Assembler Encoding Programme. The goal of this programme is to create a Network Definition Matrix, which has all the data required to build a neural network. In order to create the programmes and subsequently the neural networks, evolutionary techniques are used.Finding the ideal number of neurons for a neural network is one of the difficulties in Assembler Encoding. The current implementation of Assembler Encoding relies on an inefficient and time-consuming way to deal with this issue. The report offers four other approaches to address this problem, though. Experiments were performed utilising a predator-prey problem to assess various solutions. The network's design, including the number of layers, the number of neurons in each layer, and the connections between neurons, is specified by the Assembler Encoding Programme. These rules are expressed in a low-level language that resembles machine code very closely.The Network Definition Matrix is produced by running the Assembler Encoding Programme, and it acts as a design for the neural network. Typically, the matrix contains data on the biases and weights of the connections between neurons.Thepaper track the Assembler Encoding Programmes are frequently improved and evolved using evolutionary techniques like genetic algorithms. The programmes are iteratively enhanced through evolutionary processes to create neural networks that display desirable behaviour for certain tasks or issues.

show abstract

Section: Methodology 1 Neural Network Assumptionsmentioning

confidence: 99%

Evolutionary approach in Assembler by Implementation of Neural Networks

Verma¹

2021

MSEA

View full text Add to dashboard Cite

show abstract

“…A practical problem in the study was a dynamic approach adjusting enterprise's policy for conforming customers' needs. Sasiadek [21] presents theoretical notions related to assembly sequence planning in the process of elements design engineering and design for machines assembly. Kostic et al [22] describes the development of assembly mate references within the Webbased Virtual Laboratory for collaborative learning in industrial design.…”

Section: Literature Reviewmentioning

confidence: 99%

Robot and Plant Simulation for Automotive Part Production Process Design: A Case Study

Supsomboon¹,

Varodhomwathana²

2016

Int. j. simul. model.

View full text Add to dashboard Cite

Due to the higher competition in automobile industry, automotive part manufacturers who supply parts have also been challenged to improve the quality of their products to meet customers' requirements. Quality of parts or products could be controlled and improved since the stage of production process design. Efficient production process design could reduce work in process (WIP), wastes, reworks, errors, and failures, which could reduce system cost and increase quality of final products. However, production process design for the process which implements automatic systems is sophisticate due to the complication of the equipment itself and the synchronization requirement. This study presents the use of computer simulations to design an automotive part production process. Two objectives are proposed. The first one is to introduce three dimension robot (3D CAD) simulation for robotic work stations designed to meet the desired cycle time with minimum chance of robot collision and minimum number of robots in the system. The second one is to propose plant simulation for production planning design in order to produce product which could meet the desired capacity and customer needs with minimum number of workers.

show abstract

“…Lestan et al [27] have proposed the evolutionary optimization techniques, considered to be a Genetic Algorithm (GA) to measure the scheduling efficiency. Sasiadek [28] suggested theoretical approach for an assembly involving elements design and complex machine assembly. Govindarajalu et al [29] suggested a methodology for a piston cylinder assembly to reduce the manufacturing cost.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal Tolerance Allocation in a Complex Assembly Using Evolutionary Algorithms

Kumar¹,

Padmanaban²,

Balamurugan³

2016

Int. j. simul. model.

View full text Add to dashboard Cite

Tolerance design is a vital factor which influences product and process development. Further, it determines the manufacturing cost, the functionality and quality of a product. It is evident that optimal tolerance normally leads to produce ample parts, better operation of mechanical systems and excellent assembling. In contrast, tight tolerance leads to increase in manufacturing cost for an assembly. An ideal relationship exists among production cost and operation, while determining the optimum tolerance. Based on this relation a new approach by implementing the Non-traditional techniques: Genetic Algorithm (GA), Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and Differential Evolution (DE) for determining the optimum tolerance, zero percentage rejection and manufacturing cost considering the varying quality loss constants for an assembly namely overrunning clutch assembly, is discussed in this paper. From the result obtained, it is evident that, the proposed approach is best suitable for solving problems involving complex assemblies.

show abstract

Planning and analysis of mechanical assembly sequences in design engineering – Part I: The Method

Cited by 7 publications

References 6 publications

Evolutionary approach in Assembler by Implementation of Neural Networks

Evolutionary approach in Assembler by Implementation of Neural Networks

Robot and Plant Simulation for Automotive Part Production Process Design: A Case Study

Optimal Tolerance Allocation in a Complex Assembly Using Evolutionary Algorithms

Contact Info

Product

Resources

About