In the era of digitalization, manufacturing companies expect their growing access to data to lead to improvements and innovations. Manufacturing engineers will have to collaborate with data scientists to analyse the ever-increasing volume of data. This process of adopting data science techniques into an engineering organisation is a sociotechnical process fraught with challenges. This paper uses a participant observation case study to to investigate and discuss the sociotechnical nature of the adoption data science technology into an engineering organisation. In the case study, a young data scientist / statistician interacted with experienced production engineers in a global automotive organisation to mutual satisfaction. However, the case ...
The goal of data science is to improve decision making through the analysis of data. Today data scie...
Much of the recent work in the field of smart manufacturing is dependent on a data-driven approach, ...
Designing in large-scale engineering systems is a difficult cognitive task undertaken by experts. Kn...
The condition under which the data wrangling process is undertaken has a profound impact on the qual...
The conditions under which the data wrangling process is undertaken has a profound impact on the qua...
Organizations of all sizes are dealing with rapidly growing volumes of data and are trying to decide...
Data-Centric Engineering is an emerging branch of science that certainly will take on a leading role...
As of today, organizations are still struggling to derive consistent value from data science project...
This research investigates how to break through intra-organizational data silos in multinational eng...
Although our capabilities to store and process data have been increasing exponentially since the 196...
© 2020 American Society for Engineering EducationIn this theory paper, we integrate literature from ...
223 pagesIt takes a lot of human work to do data science, and this thesis explains what that work is...
Abstract. Although our capabilities to store and process data have been increasing exponentially sin...
The digital revolution made available vast amounts of data both in industry and in the research land...
Data is becoming the new valuable raw material in business and in our everyday life. Like any other ...
The goal of data science is to improve decision making through the analysis of data. Today data scie...
Much of the recent work in the field of smart manufacturing is dependent on a data-driven approach, ...
Designing in large-scale engineering systems is a difficult cognitive task undertaken by experts. Kn...
The condition under which the data wrangling process is undertaken has a profound impact on the qual...
The conditions under which the data wrangling process is undertaken has a profound impact on the qua...
Organizations of all sizes are dealing with rapidly growing volumes of data and are trying to decide...
Data-Centric Engineering is an emerging branch of science that certainly will take on a leading role...
As of today, organizations are still struggling to derive consistent value from data science project...
This research investigates how to break through intra-organizational data silos in multinational eng...
Although our capabilities to store and process data have been increasing exponentially since the 196...
© 2020 American Society for Engineering EducationIn this theory paper, we integrate literature from ...
223 pagesIt takes a lot of human work to do data science, and this thesis explains what that work is...
Abstract. Although our capabilities to store and process data have been increasing exponentially sin...
The digital revolution made available vast amounts of data both in industry and in the research land...
Data is becoming the new valuable raw material in business and in our everyday life. Like any other ...
The goal of data science is to improve decision making through the analysis of data. Today data scie...
Much of the recent work in the field of smart manufacturing is dependent on a data-driven approach, ...
Designing in large-scale engineering systems is a difficult cognitive task undertaken by experts. Kn...