Assembly Time Modeling through Connective Complexity Metrics

The work in this paper uses neural networks to develop a relationship model between assembly times and complexity metrics applied to defined mate connections within SolidWorks assembly models. This model is then used to develop a Design for Assembly (DFA) automation tool that can predict a product’s assembly time using defined mate connections within SolidWorks assembly models. The development of this new method consists of: creating a SolidWorks (SW) Add-in to automatically extract the mate connections from SW assembly models, parsing the mate connections into graphs, implementing a new complexity training algorithm to predict assembly times based on mate graphs, and evaluating the effectiveness of the new method. The motivation, development, and evaluation of the new automated DFA method are presented in this paper. Ultimately, the method that is trained on both fully defined and partially defined assembly models is shown to provide assembly time prediction results that are typically within 25% of target time, but with one outlier at 95% error, suggesting that a more robust training set is needed.

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Bayesian heterogeneous assembly time modeling for robotic performance prediction

Journal of Advanced Mechanical Design Systems and Manufacturing ◽

10.1299/jamdsm.2021jamdsm0007 ◽

2021 ◽

Vol 15 (1) ◽

pp. JAMDSM0007-JAMDSM0007

Author(s):

Mingyang LI ◽

Xuxue SUN ◽

Guoyuan LIANG ◽

Yingjun SHEN ◽

Qingpeng ZHANG ◽

...

Keyword(s):

Performance Prediction ◽

Assembly Time ◽

Time Modeling

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Assembly time modelling through connective complexity metrics

International Journal of Computer Integrated Manufacturing ◽

10.1080/0951192x.2012.684706 ◽

2013 ◽

Vol 26 (10) ◽

pp. 955-967 ◽

Cited By ~ 16

Author(s):

James L. Mathieson ◽

Bradley A. Wallace ◽

Joshua D. Summers

Keyword(s):

Assembly Time ◽

Complexity Metrics

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Continuous-Time Modeling in Econometrics and Engineering

SSRN Electronic Journal ◽

10.2139/ssrn.1673102 ◽

2002 ◽

Author(s):

Arie Ten Cate

Keyword(s):

Continuous Time ◽

Time Modeling

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A Literature Survey of Cognitive Complexity Metrics for Statechart Diagrams

SSRN Electronic Journal ◽

10.2139/ssrn.3441634 ◽

2019 ◽

Author(s):

Ann Wambui King’ori ◽

Geoffrey Muchiri Muketha ◽

Elyjoy Muthoni Micheni

Keyword(s):

Cognitive Complexity ◽

Literature Survey ◽

Complexity Metrics

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Handling Initial Conditions in Vector Fitting for Real Time Modeling of Power System Dynamics

Energies ◽

10.3390/en14092471 ◽

2021 ◽

Vol 14 (9) ◽

pp. 2471

Author(s):

Tommaso Bradde ◽

Samuel Chevalier ◽

Marco De Stefano ◽

Stefano Grivet-Talocia ◽

Luca Daniel

Keyword(s):

Dynamical Systems ◽

Power System ◽

System Dynamics ◽

Real Time ◽

Initial Conditions ◽

Test System ◽

Initial State ◽

Power System Dynamics ◽

Vector Fitting ◽

Time Modeling

This paper develops a predictive modeling algorithm, denoted as Real-Time Vector Fitting (RTVF), which is capable of approximating the real-time linearized dynamics of multi-input multi-output (MIMO) dynamical systems via rational transfer function matrices. Based on a generalization of the well-known Time-Domain Vector Fitting (TDVF) algorithm, RTVF is suitable for online modeling of dynamical systems which experience both initial-state decay contributions in the measured output signals and concurrently active input signals. These adaptations were specifically contrived to meet the needs currently present in the electrical power systems community, where real-time modeling of low frequency power system dynamics is becoming an increasingly coveted tool by power system operators. After introducing and validating the RTVF scheme on synthetic test cases, this paper presents a series of numerical tests on high-order closed-loop generator systems in the IEEE 39-bus test system.

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The effect of colonization dynamics in competition for space in metacommunities

Theoretical Ecology ◽

10.1007/s12080-021-00515-9 ◽

2021 ◽

Author(s):

Jorge Arroyo-Esquivel ◽

Nathan G. Marculis ◽

Alan Hastings

Keyword(s):

Continuous Time ◽

Habitat Suitability ◽

Limiting Factor ◽

Modeling Framework ◽

Competition For Space ◽

Time Modeling ◽

Functional Forms ◽

Colonization Dynamics ◽

Main Factors ◽

Metacommunity Dynamics

AbstractOne of the main factors that determines habitat suitability for sessile and territorial organisms is the presence or absence of another competing individual in that habitat. This type of competition arises in populations occupying patches in a metacommunity. Previous studies have looked at this process using a continuous-time modeling framework, where colonizations and extinctions occur simultaneously. However, different colonization processes may be performed by different species, which may affect the metacommunity dynamics. We address this issue by developing a discrete-time framework that describes these kinds of metacommunity interactions, and we consider different colonization dynamics. To understand potential dynamics, we consider specific functional forms that characterize the colonization and extinction processes of metapopulations competing for space as their limiting factor. We then provide a mathematical analysis of the models generated by this framework, and we compare these results to what is seen in nature and in previous models.

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