Quality and Automated Process Gauging

2020 ◽  
pp. 295-327
Author(s):  
Thomas H. George
Keyword(s):  
2020 ◽  
Vol 40 (6) ◽  
pp. 488-490
Author(s):  
S. Yu. Kalyakulin ◽  
V. V. Kuz’min ◽  
E. V. Mitin ◽  
S. P. Sul’din

Author(s):  
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Author(s):  
L.R. Kashapova ◽  
D.L. Pankratov ◽  
V.G. Shibakov

The procedure of automated process reliability evaluation is developed in order to prevent recurrent defects in parts manufactured by die stamping. The procedure is based on the analysis of such factors as part design, material, its mechanical and physical properties; equipment parameters, tool performance, etc. The list of reliability factors may vary according to type of operation as deformation process is different for each group of operations. The adjustment of stamping process reliability performance prevents any defects emerging during production of critical parts as early as the work preparation stage.


Author(s):  
Christoph Mayr-Dorn ◽  
Michael Vierhauser ◽  
Stefan Bichler ◽  
Felix Keplinger ◽  
Jane Cleland-Huang ◽  
...  

2021 ◽  
Vol 1889 (2) ◽  
pp. 022040
Author(s):  
N A Merentsov ◽  
A V Persidskiy ◽  
A B Golovanchikov ◽  
V N Lebedev ◽  
V V Groshev

2019 ◽  
Vol 9 (1) ◽  
pp. 631-640 ◽  
Author(s):  
Leopold Hrabovský ◽  
David Dluhoš

AbstractIn a parking house with KOMA TOWER computer-controlled automated parking system it happens that a control system is locked out of service after a pallet has failed to reach the required position during the shifting of pallets, loaded with cars, into rack cells.In this paper is described testing equipment designed by the Institute of Transport, Faculty of Mechanical Engineering, VŠB Technical University of Ostrava for the purpose of simulating the process of pallets shifting into the rack cells in order that the frequency of error messages from the control system during the automated process of cars positioning in rack cells in the parking house may be limited.The paper details two completed parts of the designed testing equipment which provide for the calibration of strain-gauge force transducers and for the detection of coil compressive spring compression in relation to acting pressure force.The description of the third, principal design part will be provided in the next paper, together with the experimentally measured acting forces which generate, in both horizontal and vertical directions, as a pallet brake pulley rolls along a brake haunch length.


2010 ◽  
Author(s):  
Ifeoma Nwogu ◽  
Mark Frank ◽  
Venu Govindaraju
Keyword(s):  

1983 ◽  
Vol 15 (1) ◽  
pp. 70-72
Author(s):  
A. K. Naumov ◽  
V. P. Linnik ◽  
V. I. Tishchenko ◽  
V. G. Shevchenko

2021 ◽  
pp. 107815522199284
Author(s):  
Ana C Riestra ◽  
Carmen López-Cabezas ◽  
Marion Jobard ◽  
Mertxe Campo ◽  
María J Tamés ◽  
...  

Introduction The aim of this study is to compare productivity of the KIRO Oncology compounding robot in three hospital pharmacy departments and identify the key factors to predict and optimize automatic compounding time. Methods The study was conducted in three hospitals. Each hospital compounding workload and workflow were analyzed. Data from the robotic compounding cycles from August 2017 to July 2018 were retrospectively obtained. Nine cycle specific parameters and five productivity indicators were analysed in each site. One-to-one differences between hospitals were evaluated. Next, a correlation analysis between cycle specific factors and productivity indicators was conducted; the factors presenting a highest correlation to automatic compounding time were used to develop a multiple regression model (afterwards validated) to predict the automatic compounding time. Results A total of 2795 cycles (16367 preparations) were analysed. Automatic compounding time showed a relevant positive correlation (ǀrs|>0.40) with the number of preparations, number of vials and total volume per cycle. Therefore, these cycle specific parameters were chosen as independent variables for the mathematical model. Considering cycles lasting 40 minutes or less, predictability of the model was high for all three hospitals (R2:0.81; 0.79; 0.72). Conclusion Workflow differences have a remarkable incidence in the global productivity of the automated process. Total volume dosed for all preparations in a cycle is one of the variables with greater influence in automatic compounding time. Algorithms to predict automatic compounding time can be useful to help users in order to plan the cycles launched in KIRO Oncology.


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