Boeing 737 MAX: Expectation of Human Capability in Highly Automated Systems

Author(s):  
Zachary Spielman ◽  
Katya Le Blanc
1996 ◽  
Vol 26 (12) ◽  
pp. 1420-1427 ◽  
Author(s):  
T. BRUNNEE ◽  
A. SEEBERGER ◽  
J. KLEINE-TEBBE ◽  
G. KUNKEL

2017 ◽  
Vol 68 (10) ◽  
pp. 2289-2292
Author(s):  
Dorin Badoiu ◽  
Georgeta Toma

One of the solutions to reduce the production and maintenance costs of the sucker rod pumping installations is to develop automated systems for regulating and controlling their operations. The development of these automated systems requires an attentive modeling of the dynamics of the mechanism of the pumping unit, process in which the identification of the values of the parameters involved in the calculations plays an essential role. The paper presents the manner of determining the values of some parameters of the mechanism of a C-320D-256-100 pumping unit starting from the variation on a cinematic cycle of the motor torque at the crank shaft. Simulations were performed with a computer program developed by the authors, and the experimental records were processed with the program Total Well Management.


2014 ◽  
Author(s):  
Stephanie M. Merritt ◽  
Kelli Huber ◽  
Jennifer LaChapell-Unnerstall ◽  
Deborah Lee
Keyword(s):  

2019 ◽  
Vol 19 (1) ◽  
pp. 10-14
Author(s):  
Ryan Scott ◽  
Malcolm Le Lievre

Purpose The purpose of this paper is to explore insights methodology and technology by using behavioral to create a mind-set change in the way people work, especially in the age of artificial intelligence (AI). Design/methodology/approach The approach is to examine how AI is driving workplace change, introduce the idea that most organizations have untapped analytics, add the idea of what we know future work will look like and look at how greater, data-driven human behavioral insights will help prepare future human-to-human work and inform people’s work with and alongside AI. Findings Human (behavioral) intelligence will be an increasingly crucial part of behaviorally smart organizations, from hiring to placement to adaptation to team building, compliance and more. These human capability insights will, among other things, better prepare people and organizations for changing work roles, including working with and alongside AI and similar tech innovation. Research limitations/implications No doubt researchers across the private, public and nonprofit sectors will want to further study the nexus of human capability, behavioral insights technology and AI, but it is clear that such work is already underway and can prove even more valuable if adopted on a broader, deeper level. Practical implications Much “people data” inside organizations is currently not being harvested. Validated, scalable processes exist to mine that data and leverage it to help organizations of all types and sizes be ready for the future, particularly in regard to the marriage of human capability and AI. Social implications In terms of human capability and AI, individuals, teams, organizations, customers and other stakeholders will all benefit. The investment of time and other resources is minimal, but must include C-suite buy in. Originality/value Much exists on the softer aspects of the marriage of human capability and AI and other workplace advancements. What has been lacking – until now – is a 1) practical, 2) validated and 3) scalable behavioral insights tech form that quantifiably informs how people and AI will work in the future, especially side by side.


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