The TestSmart–HPV Program—Development of an Integrated Approach for Testing High Production Volume Chemicals

2001 ◽  
Vol 33 (2) ◽  
pp. 105-109 ◽  
Author(s):  
Sidney Green ◽  
Alan M. Goldberg ◽  
Joanne Zurlo
Keyword(s):  
Program Development ◽  
Integrated Approach ◽  
Production Volume ◽  
High Production Volume ◽  
High Production

scholarly journals Estimating the Impact of High-Production-Volume Chemicals on Remote Ecosystems by Toxic Pressure Calculation

2006 ◽  
Vol 40 (5) ◽  
pp. 1573-1580 ◽  
Author(s):  
Jasper V. Harbers ◽  
Mark A. J. Huijbregts ◽  
Leo Posthuma ◽  
Dik van de Meent
Keyword(s):  
Production Volume ◽  
High Production Volume ◽  
Pressure Calculation ◽  
High Production ◽  
The Impact

scholarly journals Animal Use and Lessons Learned in the U.S. High Production Volume Chemicals Challenge Program

2012 ◽  
Vol 120 (12) ◽  
pp. 1631-1639 ◽  
Author(s):  
Patricia L. Bishop ◽  
Joseph R. Manuppello ◽  
Catherine E. Willett ◽  
Jessica T. Sandler
Keyword(s):  
Lessons Learned ◽  
Production Volume ◽  
High Production Volume ◽  
Animal Use ◽  
High Production ◽  
The U.S

The High Production Volume Challenge Program

2006 ◽  
pp. 1-19
Author(s):  
Richard Hefter ◽  
Barbara Leczynski ◽  
Charles Auer
Keyword(s):  
Production Volume ◽  
High Production Volume ◽  
High Production ◽  
Volume Challenge

Integrating Impedance Control and Learning Based Search Scheme for Robotic Assemblies Under Uncertainty

2018 ◽  
Author(s):  
Rishi K. Malhan ◽  
Yash Shahapurkar ◽  
Ariyan M. Kabir ◽  
Brual Shah ◽  
Satyandra K. Gupta
Keyword(s):  
Search Strategy ◽  
Small Volume ◽  
Impedance Control ◽  
Production Volume ◽  
Control Parameters ◽  
Robotic Arms ◽  
High Production Volume ◽  
High Production ◽  
Assembly Operations ◽  
Assembly Tasks

Using fixtures for assembly operations is a common practice in manufacturing processes with high production volume. For automated assembly cells using robotic arms, trajectories are programmed manually and robots follow the same path repeatedly. It is not economically feasible to build fixed fixtures for small volume productions as they require high accuracy and are part specific. Moreover, hand coding robot trajectories is a time consuming task. The uncertainties in part localization and inaccuracy in robot motions make it challenging to automate the task of assembling two parts with tight tolerances. Researchers in past have developed methods for automating the assembly task using contact-based search schemes and impedance control-based trajectory execution. Both of these approaches may lead to undesired collision with critical features on the parts. Our method guarantees safety for parts with delicate features during the assembly process. Our approach enables us to select optimum impedance control parameters and utilizes a learning-based search strategy to complete assembly tasks under uncertainties in bounded time. Our approach was tested on an assembly of two rectangular workpieces using KUKA IIWA 7 manipulator. The method we propose was able to successfully select the optimal control parameters. The learning-based search strategy successfully estimated the uncertainty in pose of parts and converged in few iterations.

Fate of triclocarban during soil aquifer treatment: soil column studies

2010 ◽  
Vol 61 (7) ◽  
pp. 1779-1785 ◽  
Author(s):  
H. M. K. Essandoh ◽  
C. Tizaoui ◽  
M. H. A. Mohamed ◽  
G. Amy ◽  
D. Brdjanovic
Keyword(s):  
Soil Column ◽  
Soil Aquifer Treatment ◽  
Production Volume ◽  
Column Studies ◽  
Sand Column ◽  
Treatment Performance ◽  
High Production Volume ◽  
High Production ◽  
Current Concerns ◽  
As Toxicity

There are current concerns about the presence of persistent chemicals in recharge water used in soil aquifer treatment systems. Triclocarban (TCC) has been reported as a persistent, high production volume chemical with the potential to bioaccumulate in the environment. It is also known to have adverse effects such as toxicity and suspected endocrine disruption. This study was carried out to study the fate of TCC in soil aquifer treatment (SAT) through laboratory simulations in a soil column. The system performance was evaluated with regards to TCC influent concentration, sand (column) depth, and residence time. Results obtained confirmed the ability of SAT to reduce TCC concentrations in wastewater. Sorption and biodegradation were responsible for TCC removal, the latter mechanism however being unsustainable. The removal efficiency was found to be dependent on concentration and decreased over time and increased with column depth. Within the duration of the experimental run, TCC negatively impacted on treatment performance through a reduction in COD removals observed in the column.

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