scholarly journals What guides information consensus Approaching the reduction of equivocality in process innovations

2020 ◽  
Vol 15 (1) ◽  
pp. 1
Author(s):  
Mats Jackson ◽  
Magnus Wiktorsson ◽  
Jessica Bruch ◽  
Erik Flores Garcia
2020 ◽  
Vol 15 (1) ◽  
pp. 73
Author(s):  
Erik Flores García ◽  
Jessica Bruch ◽  
Magnus Wiktorsson ◽  
Mats Jackson

Author(s):  
Yi-Chun Chen ◽  
Bo-Huei He ◽  
Shih-Sung Lin ◽  
Jonathan Hans Soeseno ◽  
Daniel Stanley Tan ◽  
...  

In this article, we discuss the backgrounds and technical details about several smart manufacturing projects in a tier-one electronics manufacturing facility. We devise a process to manage logistic forecast and inventory preparation for electronic parts using historical data and a recurrent neural network to achieve significant improvement over current methods. We present a system for automatically qualifying laptop software for mass production through computer vision and automation technology. The result is a reliable system that can save hundreds of man-years in the qualification process. Finally, we create a deep learning-based algorithm for visual inspection of product appearances, which requires significantly less defect training data compared to traditional approaches. For production needs, we design an automatic optical inspection machine suitable for our algorithm and process. We also discuss the issues for data collection and enabling smart manufacturing projects in a factory setting, where the projects operate on a delicate balance between process innovations and cost-saving measures.


Author(s):  
Kingsley Okoye ◽  
Arturo Arrona-Palacios ◽  
Claudia Camacho-Zuñiga ◽  
Nisrine Hammout ◽  
Emilia Luttmann Nakamura ◽  
...  

AbstractToday, modern educational models are concerned with the development of the teacher-student experience and the potential opportunities it presents. User-centric analyses are useful both in terms of the socio-technical perspective on data usage within the educational domain and the positive impact that data-driven methods have. Moreover, the use of information and communication technologies (ICT) in education and process innovation has emerged due to the strategic perspectives and the process monitoring that have shown to be missing within the traditional education curricula. This study shows that there is an unprecedented increase in the amount of text-based data in different activities within the educational processes, which can be leveraged to provide useful strategic intelligence and improvement insights. Educators can apply the resultant methods and technologies, process innovations, and contextual-based information for ample support and monitoring of the teaching-learning processes and decision making. To this effect, this paper proposes an Educational Process and Data Mining (EPDM) model that leverages the perspectives or opinions of the students to provide useful information that can be used to enhance the end-to-end processes within the educational domain. Theoretically, this study applies the model to determine how the students evaluate their teachers by considering the gender of the teachers. We analyzed the underlying patterns and determined the emotional valence of the students based on their comments in the Students Evaluation of Teaching (SET). Thus, this work implements the proposed EPDM model using SET comments captured in a setting of higher education.


2021 ◽  
pp. 1-9
Author(s):  
Baigang Zhao ◽  
Xianku Zhang

Abstract To solve the problem of identifying ship model parameters quickly and accurately with the least test data, this paper proposes a nonlinear innovation parameter identification algorithm for ship models. This is based on a nonlinear arc tangent function that can process innovations on the basis of an original stochastic gradient algorithm. A simulation was carried out on the ship Yu Peng using 26 sets of test data to compare the parameter identification capability of a least square algorithm, the original stochastic gradient algorithm and the improved stochastic gradient algorithm. The results indicate that the improved algorithm enhances the accuracy of the parameter identification by about 12% when compared with the least squares algorithm. The effectiveness of the algorithm was further verified by a simulation of the ship Yu Kun. The results confirm the algorithm's capacity to rapidly produce highly accurate parameter identification on the basis of relatively small datasets. The approach can be extended to other parameter identification systems where only a small amount of test data is available.


2005 ◽  
Vol 6 (4) ◽  
pp. 259-273 ◽  
Author(s):  
Robert Strohmeyer ◽  
Vartuhi Tonoyan

Analysing 1,055 female- and 2,207 male-owned businesses in Germany, the authors found that the former underperformed compared with the latter in terms of employment growth and firm innovativeness. Controlling for endogeneity, ie feedback effects between employment growth and innovation, it was demonstrated that the lower employment growth in women-owned businesses was mainly due to women's lower commitment to product and process innovations, a phenomenon that is referred to in this study as the ‘female–male innovation gap’. The female–male innovation gap apparently goes back to occupational sex segregation, with women populating occupations and choosing fields of study or apprenticeship training that are less technical or technology-oriented and thus less likely to provide them with important resources (eg technical know-how) and favourable conditions needed for the development and implementation of product and process innovations.


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