Impact Score 5.45
In today's world, there are unprecedented changes in various industries, mainly characterized by progressive digital transformation, the creation of the connection networks between products, value chains and business models. These activities take place within the fourth industrial revolution, called "Industry 4.0". The new technologies, in particular: Digitization and computerization of production processes and market processes, drive Industry 4.0 but the need to build a competitive advantage remains the real foundation of ongoing change. Today, this advantage is primarily created by the unprecedented flexibility of business. The central issue in Economy 4.0 is to understand the impact of robotization and artificial intelligence on industry and the economy, and to adapt business models to increasingly-demanding customers. The active role of the state as a creator and regulator of innovation is also indispensable.
Industry is undergoing the so-called “fourth revolution” with a trend towards fully automated cyber-physical systems (CPS) and an augmented data exchange provided by the internet of things (IoT). This revolution is highly correlated and supported by an increasing adoption of machine learning techniques that allow, on the one hand, to generate valuable predictions for the daily work in smart factories, and on the other hand, to help the operators make the right decisions, or even to take decisions on their own. While research in machine learning is rapidly evolving, the transfer to industry is still slow. To overcome this issue, researchers and factories must work together to get the most of both sides. This way, industries can add value to their data and processes, and researchers can study ways of facilitating the application of theoretical results to real world scenarios.
The aim of this topical collection is to integrate cutting edge research from the fields of machine learning and deep learning into industrial production and manufacturing processes, to leverage their technological transformation towards the new era of smart factories. We cordially invite researchers to contribute original research papers that report novel systems, applications, as well as survey papers that review the novel technologies and new trends on the intersection between these two areas. A strong focus should be on applicability and transferability, so that the interested readers should find it easy to reproduce and replicate the published results of the paper into their own use industrial cases. We will welcome papers that, inter alia, refer to (but are not limited to) themes such as:
Haibo Liang, Professor, Southwest Petroleum University, China, [email protected] (Lead Guest Editor)
Weidong Liu, Associate Professor, Inner Mongolia University, China, [email protected]
Manuscript Due: May 1, 2021First Round of Reviews: July 1, 2021Final Decision: July 30, 2021
Peer Review Process
All the papers will go through peer review, and will be reviewed by at least three reviewers. A thorough check will be completed, and the guest editors will check any significant similarity between the manuscript under consideration and any published paper or submitted manuscripts of which they are aware. In such case, the article will be directly rejected without proceeding further. Guest editors will make all reasonable effort to receive the reviewer’s comments and recommendation on time.
The submitted papers must provide original research that has not been published nor currently under review by other venues. Previously published conference papers should be clearly identified by the authors at the submission stage and an explanation should be provided about how such papers have been extended to be considered for this special issue (with at least 30% difference from the original works).
Paper submissions for the special issue should strictly follow the submission format and guidelines (https://www.springer.com/journal/521/submission-guidelines). Each manuscript should not exceed 16 pages in length (inclusive of figures and tables).
Manuscripts must be submitted to the journal online system at https://www.editorialmanager.com/ncaa/default.aspx.Authors should select “TC: NC for Industry 4.0” during the submission step ‘Additional Information’.