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Article
Publication date: 18 January 2024

Zaihua Luo, Juliang Xiao, Sijiang Liu, Mingli Wang, Wei Zhao and Haitao Liu

This paper aims to propose a dynamic parameter identification method based on sensitivity analysis for the 5-degree of freedom (DOF) hybrid robots, to solve the problems of too…

Abstract

Purpose

This paper aims to propose a dynamic parameter identification method based on sensitivity analysis for the 5-degree of freedom (DOF) hybrid robots, to solve the problems of too many identification parameters, complex model, difficult convergence of optimization algorithms and easy-to-fall into a locally optimal solution, and improve the efficiency and accuracy of dynamic parameter identification.

Design/methodology/approach

First, the dynamic parameter identification model of the 5-DOF hybrid robot was established based on the principle of virtual work. Then, the sensitivity of the parameters to be identified is analyzed by Sobol’s sensitivity method and verified by simulation. Finally, an identification strategy based on sensitivity analysis was designed, experiments were carried out on the real robot and the results were verified.

Findings

Compared with the traditional full-parameter identification method, the dynamic parameter identification method based on sensitivity analysis proposed in this paper converges faster when optimized using the genetic algorithm, and the identified dynamic model has higher prediction accuracy for joint drive forces and torques than the full-parameter identification models.

Originality/value

This work analyzes the sensitivity of the parameters to be identified in the dynamic parameter identification model for the first time. Then a parameter identification method is proposed based on the results of the sensitivity analysis, which can effectively reduce the parameters to be identified, simplify the identification model, accelerate the convergence of the optimization algorithm and improve the prediction accuracy of the identified model for the joint driving forces and torques.

Details

Industrial Robot: the international journal of robotics research and application, vol. 51 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 4 June 2019

Marco Erling

This paper aims to analyze the sensitivity of different external factors to the returns of the precious metals of gold, silver, platinum and palladium. The goal is to find…

Abstract

Purpose

This paper aims to analyze the sensitivity of different external factors to the returns of the precious metals of gold, silver, platinum and palladium. The goal is to find similarities and differences between the dependencies of every factor to each metal in a time-varying framework.

Design/methodology/approach

A brief co-integration test for the precious metals is conducted followed by a Kalman smoother approach to study the different sensitivities to the price changes of precious metals. A dynamic time warping (DTW) approach finally compares sensitivities for pairs of precious metals to a specific factor.

Findings

Results point to strong time-dependencies of the sensitivities, such as a declining relationship of gold to equity volatility. Consistent strong relationships are rare and can be identified for the consumer price index and the dollar. the DTW approach finds higher similarities between platinum and palladium compared to other pairs.

Practical implications

The similarities and differences of the precious metals can be used by investors and risk managers in portfolio construction processes and risk analyses.

Originality/value

The focus of the research is put on a broader context of precious metals with different external factors instead of focusing on a single factor, enabling a comparison of differences and similarities of the sensitivities. The analysis via a Kalman Rauch–Tung–Striebel smoother together with a DTW approach has not been conducted before in this way and is able to characterize the dependencies by a single number.

Details

Studies in Economics and Finance, vol. 36 no. 1
Type: Research Article
ISSN: 1086-7376

Keywords

Article
Publication date: 1 February 2016

Xin Ye, Pan Liu, Zhijing Zhang, Chao Shao and Yan Li

The purpose of this paper is to analyze the sensitivity of the motion error parameters in microassembly process, thereby improving the assembly accuracy. The motion errors of the…

Abstract

Purpose

The purpose of this paper is to analyze the sensitivity of the motion error parameters in microassembly process, thereby improving the assembly accuracy. The motion errors of the precision motion stages directly affect the final assembly quality after the machine visual alignment.

Design/methodology/approach

This paper presents the error parameters of the in-house microassembly system with coaxial alignment function, builds the error transfer model by the multi-body system theory, analyzes the error sensitivity on the sensitive direction using the Sobol method, which was based on variance, and then gets the ones which made a great degree of influence. Before the sensitivity analyzing, parts of the error sources have been measured to obtain their distribution ranges.

Findings

The results of the sensitivity analysis by the Sobol method, which was based on variance, are coincident with the theoretical analysis. Besides, the results provide a reference for the error compensation in control process, for the selection of the precision motion stages and for the installation index of the motion stages of the assembly system with coaxial alignment.

Originality/value

This kind of error sensitivity analysis method is of great significance for improving the assembly accuracy after visual system positioning, and increasing efficiency from the initial motion stage selection to final error compensation for designers. It is suitable for general precision motion systems be of multi-degree of freedom, for the method of modeling, measuring and analyzing used in this paper are all universal and applicative.

Details

Assembly Automation, vol. 36 no. 1
Type: Research Article
ISSN: 0144-5154

Keywords

Article
Publication date: 3 April 2017

Xin Li, Jianzhong Shang and Hong Zhu

This paper aims to consider a problem of assembly sensitivity in a multi-station assembly process. The authors focus on the assembly process of aircrafts, which includes cabins…

Abstract

Purpose

This paper aims to consider a problem of assembly sensitivity in a multi-station assembly process. The authors focus on the assembly process of aircrafts, which includes cabins and inertial navigation system (INSs), and establish the assembly process state space model for their assembly sensitivity research.

Design/methodology/approach

To date, the process-related errors that cause large variations in key product characteristics remains one of the most critical research topics in assembly sensitivity analysis. This paper focuses on the unique challenges brought about by the multi-station system: a system-level model for characterizing the variation propagation in the entire process, and the necessity of describing the system response to variation inputs at both station-level and single fixture-level scales. State space representation is used to describe the propagation of variation in such a multi-station process, incorporating assembly process parameters such as fixture-locating layout at individual stations and station-to-station locating layout change.

Findings

Following the sensitivity analysis in control theory, a group of hierarchical sensitivity indices is defined and expressed in terms of the system matrices in the state space model, which are determined by the given assembly process parameters.

Originality/value

A case study of assembly sensitivity for a multi-station assembly process illustrates and validates the proposed methodology.

Details

Assembly Automation, vol. 37 no. 2
Type: Research Article
ISSN: 0144-5154

Keywords

Book part
Publication date: 20 October 2015

Mohammad Shamsuddoha

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured…

Abstract

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

Details

Sustaining Competitive Advantage Via Business Intelligence, Knowledge Management, and System Dynamics
Type: Book
ISBN: 978-1-78560-707-3

Keywords

Article
Publication date: 1 June 2003

B.J. Henz, K.K. Tamma, R. Kanapady, N.D. Ngo and P.W. Chung

The resin transfer molding process for composites manufacturing consists of either of two considerations, namely, the fluid flow analysis through a porous fiber preform where the…

1001

Abstract

The resin transfer molding process for composites manufacturing consists of either of two considerations, namely, the fluid flow analysis through a porous fiber preform where the location of the flow front is of fundamental importance, and the combined flow/heat transfer/cure analysis. In this paper, the continuous sensitivity formulations are developed for the process modeling of composites manufactured by RTM to predict, analyze, and optimize the manufacturing process. Attention is focused here on developments for isothermal flow simulations, and various illustrative examples are presented for sensitivity analysis of practical applications which help serve as a design tool in the process modeling stages.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 13 no. 4
Type: Research Article
ISSN: 0961-5539

Keywords

Article
Publication date: 13 November 2018

Xuchun Ren and Sharif Rahman

This paper aims to present a new method, named as augmented polynomial dimensional decomposition (PDD) method, for robust design optimization (RDO) and reliability-based design…

Abstract

Purpose

This paper aims to present a new method, named as augmented polynomial dimensional decomposition (PDD) method, for robust design optimization (RDO) and reliability-based design optimization (RBDO) subject to mixed design variables comprising both distributional and structural design variables.

Design/methodology/approach

The method involves a new augmented PDD of a high-dimensional stochastic response for statistical moments and reliability analyses; an integration of the augmented PDD, score functions, and finite-difference approximation for calculating the sensitivities of the first two moments and the failure probability with respect to distributional and structural design variables; and standard gradient-based optimization algorithms.

Findings

New closed-form formulae are presented for the design sensitivities of moments that are simultaneously determined along with the moments. A finite-difference approximation integrated with the embedded Monte Carlo simulation of the augmented PDD is put forward for design sensitivities of the failure probability.

Originality/value

In conjunction with the multi-point, single-step design process, the new method provides an efficient means to solve a general stochastic design problem entailing mixed design variables with a large design space. Numerical results, including a three-hole bracket design, indicate that the proposed methods provide accurate and computationally efficient sensitivity estimates and optimal solutions for RDO and RBDO problems.

Article
Publication date: 20 July 2015

Önder Ökmen and Ahmet Öztaş

Actual costs frequently deviate from the estimated costs in either favorable or adverse direction in construction projects. Conventional cost evaluation methods do not take the…

Abstract

Purpose

Actual costs frequently deviate from the estimated costs in either favorable or adverse direction in construction projects. Conventional cost evaluation methods do not take the uncertainty and correlation effects into account. In this regard, a simulation-based cost risk analysis model, the Correlated Cost Risk Analysis Model, previously has been proposed to evaluate the uncertainty effect on construction costs in case of correlated costs and correlated risk-factors. The purpose of this paper is to introduce the detailed evaluation of the Cost Risk Analysis Model through scenario and sensitivity analyses.

Design/methodology/approach

The evaluation process consists of three scenarios with three sensitivity analyses in each and 28 simulations in total. During applications, the model’s important parameter called the mean proportion coefficient is modified and the user-dependent variables like the risk-factor influence degrees are changed to observe the response of the model to these modifications and to examine the indirect, two-sided and qualitative correlation capturing algorithm of the model. Monte Carlo Simulation is also applied on the same data to compare the results.

Findings

The findings have shown that the Correlated Cost Risk Analysis Model is capable of capturing the correlation between the costs and between the risk-factors, and operates in accordance with the theoretical expectancies.

Originality/value

Correlated Cost Risk Analysis Model can be preferred as a reliable and practical method by the professionals of the construction sector thanks to its detailed evaluation introduced in this paper.

Details

Engineering, Construction and Architectural Management, vol. 22 no. 4
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 3 September 2020

Chenggang Li, Weishan Song and Yong Song

Six-axis force sensors play an important role in civilian and military fields because of their multifunctionality. In the context of sensor structure design, sensitivity and…

Abstract

Purpose

Six-axis force sensors play an important role in civilian and military fields because of their multifunctionality. In the context of sensor structure design, sensitivity and sensitivity isotropy are often considered. This paper aims to study the possible relationship between the sensitivity/sensitivity isotropy and structural parameters of an 8/4–4 parallel six-axis force sensor. A comprehensive evaluation index and structural optimization design scheme are suggested in the end.

Design/methodology/approach

Based on the conditional number of the Jacobian matrix spectral norm, the sensitivity and sensitivity isotropy of the sensor are derived. Orthogonal experiments are used to determine the degree of primary and secondary factors that have a substantial effect on the sensor characteristics. The relationship between the performance indices and the structural parameters is analyzed by the performance atlas method. The comprehensive evaluation index lays the foundation for the structural optimization design of an 8/4–4 parallel six-axis force sensor.

Findings

The variation in each performance index of the sensor for each of the structural parameters is analyzed, and the structural parameters of the sensor with the desired performance indices can be easily selected from the performance atlases. A comprehensive performance evaluation index with a target value of 1 is proposed, and the overall influence of the structural parameters on the sensor performance index is investigated. A simulation example shows the feasibility of the proposed evaluation index.

Originality/value

The importance of each structural parameter of the 8/4–4 parallel six-axis force sensor is determined through orthogonal experiments in this paper. Relations among the structural parameters meeting the performance indices are derived and shown in the performance atlases. A comprehensive evaluation index is proposed to analyze the overall sensor performance.

Details

Sensor Review, vol. 40 no. 5
Type: Research Article
ISSN: 0260-2288

Keywords

Article
Publication date: 13 January 2022

Zeinab Rahimi Rise and Mohammad Mahdi Ershadi

This paper aims to analyze the socioeconomic impacts of infectious diseases based on uncertain behaviors of social and effective subsystems in the countries. The economic impacts…

Abstract

Purpose

This paper aims to analyze the socioeconomic impacts of infectious diseases based on uncertain behaviors of social and effective subsystems in the countries. The economic impacts of infectious diseases in comparison with predicted gross domestic product (GDP) in future years could be beneficial for this aim along with predicted social impacts of infectious diseases in countries.

Design/methodology/approach

The proposed uncertain SEIAR (susceptible, exposed, infectious, asymptomatic and removed) model evaluates the impacts of variables on different trends using scenario base analysis. This model considers different subsystems including healthcare systems, transportation, contacts and capacities of food and pharmaceutical networks for sensitivity analysis. Besides, an adaptive neuro-fuzzy inference system (ANFIS) is designed to predict the GDP of countries and determine the economic impacts of infectious diseases. These proposed models can predict the future socioeconomic trends of infectious diseases in each country based on the available information to guide the decisions of government planners and policymakers.

Findings

The proposed uncertain SEIAR model predicts social impacts according to uncertain parameters and different coefficients appropriate to the scenarios. It analyzes the sensitivity and the effects of various parameters. A case study is designed in this paper about COVID-19 in a country. Its results show that the effect of transportation on COVID-19 is most sensitive and the contacts have a significant effect on infection. Besides, the future annual costs of COVID-19 are evaluated in different situations. Private transportation, contact behaviors and public transportation have significant impacts on infection, especially in the determined case study, due to its circumstance. Therefore, it is necessary to consider changes in society using flexible behaviors and laws based on the latest status in facing the COVID-19 epidemic.

Practical implications

The proposed methods can be applied to conduct infectious diseases impacts analysis.

Originality/value

In this paper, a proposed uncertain SEIAR system dynamics model, related sensitivity analysis and ANFIS model are utilized to support different programs regarding policymaking and economic issues to face infectious diseases. The results could support the analysis of sensitivities, policies and economic activities.

Highlights:

  • A new system dynamics model is proposed in this paper based on an uncertain SEIAR model (Susceptible, Exposed, Infectious, Asymptomatic, and Removed) to model population behaviors;

  • Different subsystems including healthcare systems, transportation, contacts, and capacities of food and pharmaceutical networks are defined in the proposed system dynamics model to find related sensitivities;

  • Different scenarios are analyzed using the proposed system dynamics model to predict the effects of policies and related costs. The results guide lawmakers and governments' actions for future years;

  • An adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the gross domestic product (GDP) in future years and analyze effects of COVID-19 based on them;

  • A real case study is considered to evaluate the performances of the proposed models.

A new system dynamics model is proposed in this paper based on an uncertain SEIAR model (Susceptible, Exposed, Infectious, Asymptomatic, and Removed) to model population behaviors;

Different subsystems including healthcare systems, transportation, contacts, and capacities of food and pharmaceutical networks are defined in the proposed system dynamics model to find related sensitivities;

Different scenarios are analyzed using the proposed system dynamics model to predict the effects of policies and related costs. The results guide lawmakers and governments' actions for future years;

An adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the gross domestic product (GDP) in future years and analyze effects of COVID-19 based on them;

A real case study is considered to evaluate the performances of the proposed models.

Details

Journal of Economic and Administrative Sciences, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1026-4116

Keywords

1 – 10 of over 47000