A dynamic simulator for the ergonomics evaluation of powered torque tools for human assembly

2017 ◽  
Vol 37 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Haluk Ay ◽  
Anthony Luscher ◽  
Carolyn Sommerich
Keyword(s):  
Risk Factors ◽  
Joint Torque ◽  
Human Hand ◽  
Model Parameters ◽  
Test Rig ◽  
Musculoskeletal Discomfort ◽  
Data Set ◽  
Content Type ◽  
Working Posture ◽  
Displacement Measurements

Purpose The purpose of this study is to design and develop a testing device to simulate interaction between human hand–arm dynamics, right-angle (RA) computer-controlled power torque tools and joint-tightening task-related variables. Design/methodology/approach The testing rig can simulate a variety of tools, tasks and operator conditions. The device includes custom data-acquisition electronics and graphical user interface-based software. The simulation of the human hand–arm dynamics is based on the rig’s four-bar mechanism-based design and mechanical components that provide adjustable stiffness (via pneumatic cylinder) and mass (via plates) and non-adjustable damping. The stiffness and mass values used are based on an experimentally validated hand–arm model that includes a database of model parameters. This database is with respect to gender and working posture, corresponding to experienced tool operators from a prior study. Findings The rig measures tool handle force and displacement responses simultaneously. Peak force and displacement coefficients of determination (R2) between rig estimations and human testing measurements were 0.98 and 0.85, respectively, for the same set of tools, tasks and operator conditions. The rig also provides predicted tool operator acceptability ratings, using a data set from a prior study of discomfort in experienced operators during torque tool use. Research limitations/implications Deviations from linearity may influence handle force and displacement measurements. Stiction (Coulomb friction) in the overall rig, as well as in the air cylinder piston, is neglected. The rig’s mechanical damping is not adjustable, despite the fact that human hand–arm damping varies with respect to gender and working posture. Deviations from these assumptions may affect the correlation of the handle force and displacement measurements with those of human testing for the same tool, task and operator conditions. Practical implications This test rig will allow the rapid assessment of the ergonomic performance of DC torque tools, saving considerable time in lineside applications and reducing the risk of worker injury. DC torque tools are an extremely effective way of increasing production rate and improving torque accuracy. Being a complex dynamic system, however, the performance of DC torque tools varies in each application. Changes in worker mass, damping and stiffness, as well as joint stiffness and tool program, make each application unique. This test rig models all of these factors and allows quick assessment. Social implications The use of this tool test rig will help to identify and understand risk factors that contribute to musculoskeletal disorders (MSDs) associated with the use of torque tools. Tool operators are subjected to large impulsive handle reaction forces, as joint torque builds up while tightening a fastener. Repeated exposure to such forces is associated with muscle soreness, fatigue and physical stress which are also risk factors for upper extremity injuries (MSDs; e.g. tendinosis, myofascial pain). Eccentric exercise exertions are known to cause damage to muscle tissue in untrained individuals and affect subsequent performance. Originality/value The rig provides a novel means for quantitative, repeatable dynamic evaluation of RA powered torque tools and objective selection of tightening programs. Compared to current static tool assessment methods, dynamic testing provides a more realistic tool assessment relative to the tool operator’s experience. This may lead to improvements in tool or controller design and reduction in associated musculoskeletal discomfort in operators.

Suicidality in the Deep South: risks for adolescent Mississippians

2016 ◽  
Vol 8 (1) ◽  
pp. 61-70 ◽  
Author(s):  
Jon Mandracchia ◽  
Yen To ◽  
Shauna Pichette
Keyword(s):  
Risk Factors ◽  
Suicide Risk ◽  
Traumatic Experiences ◽  
Deep South ◽  
Data Set ◽  
Specific Data ◽  
Content Type ◽  
Inclusive Approach ◽  
History Of ◽  
Suicide Risk Factors

Purpose – The purpose of this paper is to better understand suicidality among adolescent Mississippians. Design/methodology/approach – Mississippi-specific data were obtained from an existing national health data set and utilized for two hierarchal linear regressions. Findings – Highest risk for adolescent suicidality is for females with poor body image and a history of traumatic experiences. Research limitations/implications – This study demonstrates the need for further research into unique suicide risk factors for adolescents in Mississippi. Causality cannot be inferred due to the correlational nature of this study, and direct comparison of the findings to adolescents from other states cannot be made. Originality/value – This exploratory study employed a holistic, inclusive approach toward better identifying adolescent Mississippians most at-risk for suicidality; findings lead to future, targeted research efforts for better understanding specific suicide risk factors in this population.

scholarly journals Population Pharmacokinetic/Pharmacodynamic Analysis of the Bactericidal Activities of Sutezolid (PNU-100480) and Its Major Metabolite against Intracellular Mycobacterium tuberculosis inEx VivoWhole-Blood Cultures of Patients with Pulmonary Tuberculosis

2014 ◽  
Vol 58 (6) ◽  
pp. 3306-3311 ◽  
Author(s):  
Tong Zhu ◽  
Sven O. Friedrich ◽  
Andreas Diacon ◽  
Robert S. Wallis
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Hollow Fiber ◽  
Ex Vivo ◽  
Parent Compound ◽  
Plasma Concentrations ◽  
Population Pharmacokinetic ◽  
Model Parameters ◽  
Data Set ◽  
Content Type

ABSTRACTSutezolid (PNU-100480 [U-480]) is an oxazolidinone antimicrobial being developed for the treatment of tuberculosis. An active sulfoxide metabolite (PNU-101603 [U-603]), which reaches concentrations in plasma several times those of the parent, has been reported to drive the killing of extracellularMycobacterium tuberculosisby sutezolid in hollow-fiber culture. However, the relative contributions of the parent and metabolite against intracellularM. tuberculosisin vivoare not fully understood. The relationships between the plasma concentrations of U-480 and U-603 and intracellular whole-blood bactericidal activity (WBA) inex vivocultures were examined using a direct competitive population pharmacokinetic (PK)/pharmacodynamic 4-parameter sigmoid model. The data set included 690 PK determinations and 345 WBA determinations from 50 tuberculosis patients enrolled in a phase 2a sutezolid trial. The model parameters were solved iteratively. The median U-603/U-480 concentration ratio was 7.1 (range, 1 to 28). The apparent 50% inhibitory concentration of U-603 for intracellularM. tuberculosiswas 17-fold greater than that of U-480 (90% confidence interval [CI], 9.9- to 53-fold). Model parameters were used to simulatein vivoactivity after oral dosing with sutezolid at 600 mg twice a day (BID) and 1,200 mg once a day (QD). Divided dosing resulted in greater cumulative activity (−0.269 log10per day; 90% CI, −0.237 to −0.293 log10per day) than single daily dosing (−0.186 log10per day; 90% CI, −0.160 to −0.208 log10per day). U-480 accounted for 84% and 78% of the activity for BID and QD dosing, respectively, despite the higher concentrations of U-603. Killing of intracellularM. tuberculosisby orally administered sutezolid is mainly due to the activity of the parent compound. Taken together with the findings of other studies in the hollow-fiber model, these findings suggest that sutezolid and its metabolite act on different mycobacterial subpopulations.

scholarly journals Exploring the design risk factors for modular integrated construction projects

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ibrahim Yahaya Wuni ◽  
Geoffrey Qiping Shen ◽  
Maxwell Fordjour Antwi-Afari
Keyword(s):  
Risk Factors ◽  
Construction Projects ◽  
Relevant Literature ◽  
Uncertain Data ◽  
System Thinking ◽  
Design Stage ◽  
Data Set ◽  
Research Attention ◽  
Content Type ◽  
Knowledge Based

Purpose Modular integrated construction (MiC) is considered as a process innovation to improve the performance of construction projects. However, effective delivery of MiC projects requires management of risks and uncertainties throughout its delivery chain. Although the design stage of MiC projects is usually managed with limited knowledge based on highly uncertain data and associated with epistemic uncertainties, MiC design risks have not received adequate research attention relative to other stages. The purpose of this paper is to conduct a knowledge-based evaluation and ranking of the design risk factors (DRFs) for MiC projects. Design/methodology/approach The paper reviewed the relevant literature to identify potential DRFs and validated their relevance through pilot expert review. The paper then used questionnaires to gather data from international MiC experts from 18 countries and statistically analyzed the data set. Findings Analysis results showed that the five most significant DRFs for MiC projects include unsuitability of design for the MiC method; late involvement of suppliers, fabricators and contractors; inaccurate information, defective design and change order; design information gap between the designer and fabricator; and lack of bespoke MiC design codes and guidelines. A correlation analysis showed that majority of the DRFs have statistically significant positive relationships and could inform practitioners on the dynamic links between the DRFs. Practical implications The paper provides useful insight and knowledge to MiC practitioners and researchers on the risk factors that could compromise the success of MiC project designs and may inform design risk management. The dynamic linkages among the DRFs instruct the need to adopt a system-thinking philosophy in MiC project design. Originality/value This paper presents the first study that specifically evaluates and prioritizes the risk events at the design stage of MiC projects. It sets forth recommendations for addressing the identified DRFs for MiC projects.

scholarly journals Risk factors influencing the debt leverage of project financing initiatives in the energy industry

2017 ◽  
Vol 11 (3) ◽  
pp. 444-462 ◽  
Author(s):  
Alberto De Marco ◽  
Giulio Mangano
Keyword(s):  
Risk Factors ◽  
Capital Structure ◽  
Capital Investment ◽  
Stability Index ◽  
Energy Industry ◽  
Project Financing ◽  
Data Set ◽  
Content Type ◽  
Average Size ◽  
The Capital Structure

Purpose This paper aims to contribute to understanding the crucial influence of risks on the capital structure of project financing (PF) initiatives in the energy sector. Design/methodology/approach The debt leverage of a capital investment is selected as the response variable, and its relation with select identified risk factors is examined using a regression analysis on a data set of 72 projects carried out all over the world in the energy industry. Findings Results have highlighted that the debt leverage is significantly influenced by several sources of risk measured through specific indicators, namely, country stability index, the construction duration, the concession period and the average size of partners. Therefore, country, project and special purpose vehicle-related risks have been shown to have an impact on the debt leverage of a PF scheme. Research limitations/implications The results could support both investors and lenders to better define the financial leverage of projects delivered under a PF mechanism. In particular, the study could help to have a better understanding of the main factors that influence the debt leverage in PF initiatives. Originality/value This paper contributes to filling the lack of works addressing the relationship between risk factors and capital structure in PF projects. In this way, this research leads to a better understanding of the risk factors that influence the capital structure of a PF initiative, and they have, therefore, been proposed as a basis for the establishment of improved methods to design refined capital structures.

scholarly journals The influence of risk on the equity share of build-operate-transfer projects

2017 ◽  
Vol 7 (1) ◽  
pp. 45-58 ◽  
Author(s):  
Alberto De Marco ◽  
Giulio Mangano ◽  
Timur Narbaev
Keyword(s):  
Risk Factors ◽  
Capital Structure ◽  
Design Methodology ◽  
Data Set ◽  
Content Type ◽  
Special Purpose Vehicle ◽  
Main Factors ◽  
The Relationship ◽  
Improved Methods ◽  
The Capital Structure

Purpose The purpose of this paper is to contribute to the understanding of the crucial influence of risks on the capital structure of build-operate-transfer (BOT) projects. Design/methodology/approach The equity portion of capital injected in a BOT investment is selected as the response variable and its relation with select identified risk factors is examined using a regression analysis on a data set of BOT projects. Findings Results have pointed out that the level of equity is significantly influenced by several sources of risk. Country, revenue, project and special purpose vehicle-related risks have been shown to have an impact on the size of the equity share of a BOT investment. Research limitations/implications The results could support both investors and lenders to better define the financial leverage of BOT projects. In particular, the study could help to have a better understanding of the main factors that influence the equity apportion of capital in BOT investments. Originality/value This paper contributes to fulfilling the lack of works addressing the relationship between risk factors and capital structure in BOT projects. In this way, this research leads to a better understanding of the risk factors that influence the capital structure of BOT project and they have therefore been proposed as a base for the establishment of improved methods to design refined capital structures in BOT projects.

Effectiveness of multi-gated sequence model for the learning of kinematics and dynamics of an industrial robot

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aditya Singh ◽  
Padmakar Pandey ◽  
G.C. Nandi
Keyword(s):  
Deep Learning ◽  
Inverse Kinematics ◽  
Inverse Dynamics ◽  
Industrial Robot ◽  
Closed Form Solution ◽  
Humanoid Robots ◽  
Industrial Robots ◽  
Joint Torque ◽  
Data Set ◽  
Content Type

Purpose For efficient trajectory control of industrial robots, a cumbersome computation for inverse kinematics and inverse dynamics is needed, which is usually developed using spatial transformation using Denavit–Hartenberg principle and Lagrangian or Newton–Euler methods, respectively. The model is highly non-linear and needs to deal with uncertainties because of lack of accurate measurement of mechanical parameters, noise and non-inclusion of joint friction, which results in some inaccuracies in predicting accurate torque trajectories. To get a guaranteed closed form solution, the robot designers normally follow Pieper’s recommendation and compromise with the mechanical design. While this may be acceptable for the industrial robots where the aesthetic look is not that important, it is not for humanoid and social robots. To help solve this problem, this study aims to propose an alternative machine learning-based computational approach based on a multi-gated sequence model for finding appropriate mapping between Cartesian space to joint space and motion space to joint torque space. Design/methodology/approach First, the authors generate sufficient data required for the sequence model, using forward kinematics and forward dynamics by running N number of nested loops, where N is the number of joints of the robot. Subsequently, to develop a learning-based model based on sequence analysis, the authors propose to use long short-term memory (LSTM) and hence, train an LSTM model, the architecture details of which have been discussed in the paper. To make LSTM learning algorithms perform efficiently, the authors need to detect and eliminate redundant features from the data set, which the authors propose to do using an elegant statistical tool called Pearson coefficient. Findings To validate the proposed model, the authors have performed rigorous experiments using both hardware and simulation robots (Baxter/Anukul robot) available in their laboratory and KUKA simulation robot data set made available from Neural Learning for Robotics Laboratory. Through several characteristic plots, it has been shown that a sequence-based LSTM model of deep learning architecture with non-redundant features could help the robots to learn smooth and accurate trajectories more quickly compared to data sets having redundancy. Such data-driven modeling techniques can change the future course of direction of robotics research for solving the classical problems such as trajectory planning and motion planning for manipulating industrial as well as social humanoid robots. Originality/value The present investigation involves development of deep learning-based computation model, statistical analyses to eliminate redundant features, data creation from one hardware robot (Anukul) and one simulation robot model (KUKA), rigorously training and testing separately two computational models (specially configured two LSTM models) – one for learning inverse kinematics and one for learning inverse dynamics problem – and comparison of the inverse dynamics model with the state-of-the-art model. Hence, the authors strongly believe that the present paper is compact and complete to get published in a reputed journal so that dissemination of new ideas can benefit the researchers in the area of robotics.

Rurality or distance to care and the risk of homelessness among Afghanistan and Iraq veterans

2017 ◽  
Vol 20 (2) ◽  
pp. 45-59 ◽  
Author(s):  
Richard E. Nelson ◽  
Adi Gundlapalli ◽  
Marjorie Carter ◽  
Emily Brignone ◽  
Warren Pettey ◽  
...  
Keyword(s):  
Risk Factors ◽  
Urban Areas ◽  
Medical Center ◽  
National Policy ◽  
Department Of Veterans Affairs ◽  
Data Set ◽  
Content Type ◽  
Distance To Care ◽  
The Military ◽  
The Relationship

Purpose Several risk factors have been identified in ongoing efforts by the US Department of Veterans Affairs (VA) to mitigate high rates of homelessness among veterans. To date, no studies have examined the relationship of rurality and distance to nearest VA facility to risk of homelessness. Due to challenges in accessing available services, the hypothesis was that rural-residing veterans are at greater risk for homelessness. The paper aims to discuss these issues. Design/methodology/approach The cohort consisted of veterans who had separated from the military between 2001 and 2011. The authors used a forwarding address provided by the service member at the time of separation from the military to determine rurality of residence and distance to care. The authors examined differences in the rate of homelessness within a year of a veteran’s first encounter with the VA following last military separation based on rurality and distance to the nearest VA facility using multivariable log-binomial regressions. Findings In the cohort of 708,318 veterans, 84.3 percent were determined to have a forwarding address in urban areas, 60.4 and 88.7 percent lived within 40 miles of the nearest VA medical center (VAMC), respectively. Veterans living in a rural area (RR=0.763; 95 percent CI=0.718-0.810) and those living between 20 and 40 miles (RR=0.893; 95 percent CI=0.846-0.943) and 40+ miles away from the nearest VAMC (RR=0.928; 95 percent CI=0.879-0.979) were at a lower risk for homelessness. Originality/value The unique data set allowed the authors to explore the relationship between geography and homelessness. These results are important to VA and national policy makers in understanding the risk factors for homelessness among veterans and planning interventions.

EXPONENTIATED HALF-LOGISTIC LOMAX DISTRIBUTION WITH PROPERTIES AND APPLICATION

2019 ◽  
Vol XVI (2) ◽  
pp. 1-11
Author(s):  
Farrukh Jamal ◽  
Hesham Mohammed Reyad ◽  
Soha Othman Ahmed ◽  
Muhammad Akbar Ali Shah ◽  
Emrah Altun
Keyword(s):  
Real Data ◽  
Continuous Model ◽  
Model Parameters ◽  
Data Set ◽  
Lomax Distribution ◽  
Mathematical Properties ◽  
Proposed Model ◽  
Probability Weighted Moment ◽  
Record Statistics ◽  
Maximum Likelihood Criterion

A new three-parameter continuous model called the exponentiated half-logistic Lomax distribution is introduced in this paper. Basic mathematical properties for the proposed model were investigated which include raw and incomplete moments, skewness, kurtosis, generating functions, Rényi entropy, Lorenz, Bonferroni and Zenga curves, probability weighted moment, stress strength model, order statistics, and record statistics. The model parameters were estimated by using the maximum likelihood criterion and the behaviours of these estimates were examined by conducting a simulation study. The applicability of the new model is illustrated by applying it on a real data set.

Financial distress determinants among SMEs: empirical evidence from Sweden

2020 ◽  
Vol 47 (3) ◽  
pp. 547-560 ◽  
Author(s):  
Darush Yazdanfar ◽  
Peter Öhman
Keyword(s):  
Financial Crisis ◽  
Financial Distress ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Binary Logistic Regression ◽  
Data Availability ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type ◽  
The Global Financial Crisis

PurposeThe purpose of this study is to empirically investigate determinants of financial distress among small and medium-sized enterprises (SMEs) during the global financial crisis and post-crisis periods.Design/methodology/approachSeveral statistical methods, including multiple binary logistic regression, were used to analyse a longitudinal cross-sectional panel data set of 3,865 Swedish SMEs operating in five industries over the 2008–2015 period.FindingsThe results suggest that financial distress is influenced by macroeconomic conditions (i.e. the global financial crisis) and, in particular, by various firm-specific characteristics (i.e. performance, financial leverage and financial distress in previous year). However, firm size and industry affiliation have no significant relationship with financial distress.Research limitationsDue to data availability, this study is limited to a sample of Swedish SMEs in five industries covering eight years. Further research could examine the generalizability of these findings by investigating other firms operating in other industries and other countries.Originality/valueThis study is the first to examine determinants of financial distress among SMEs operating in Sweden using data from a large-scale longitudinal cross-sectional database.

Light touch, heavy hand: principals and data-use PLCs

2017 ◽  
Vol 55 (4) ◽  
pp. 376-389 ◽  
Author(s):  
Alice Huguet ◽  
Caitlin C. Farrell ◽  
Julie A. Marsh
Keyword(s):  
Professional Learning ◽  
Low Income ◽  
Equal Opportunity ◽  
Data Use ◽  
Opportunity To Learn ◽  
School Level ◽  
Comparative Case Study ◽  
Data Set ◽  
Content Type ◽  
Principal's Role

Purpose The use of data for instructional improvement is prevalent in today’s educational landscape, yet policies calling for data use may result in significant variation at the school level. The purpose of this paper is to focus on tools and routines as mechanisms of principal influence on data-use professional learning communities (PLCs). Design/methodology/approach Data were collected through a comparative case study of two low-income, low-performing schools in one district. The data set included interview and focus group transcripts, observation field notes and documents, and was iteratively coded. Findings The two principals in the study employed tools and routines differently to influence ways that teachers interacted with data in their PLCs. Teachers who were given leeway to co-construct data-use tools found them to be more beneficial to their work. Findings also suggest that teachers’ data use may benefit from more flexibility in their day-to-day PLC routines. Research limitations/implications Closer examination of how tools are designed and time is spent in data-use PLCs may help the authors further understand the influence of the principal’s role. Originality/value Previous research has demonstrated that data use can improve teacher instruction, yet the varied implementation of data-use PLCs in this district illustrates that not all students have an equal opportunity to learn from teachers who meaningfully engage with data.

Sign in / Sign up

Export Citation Format

Share Document