Industrial Application of Data-Driven Process Monitoring with an Automatic Selection Strategy for Modeling Data
Round 1
Reviewer 1 Report
The paper addresses an exciting issue. An information entropy-based automatic selection strategy for modeling data is proposed, based on which a general real-time process monitoring framework is developed for a large-scale industrial methanol to olefin unit with multiple operating conditions. However, the paper fails to sustain the readers' interest. I think that this paper lacks innovation and it is targeted more toward the industry rather than the general academic audience. Since this paper is not well written and organized, some comments on this paper see the attachment.
Comments for author File: 
Comments.pdf
Author Response
Please see the attachment.
Author Response File: 
Author Response.docx
Reviewer 2 Report
According to the purpose of the study, the article has a suitable framework to achieve the results, but observing a few points can improve its quality. The following are mentioned:
1- It is suggested that the main problem of the research should be clearly stated in the last two paragraphs of the introduction section.
2- It is suggested that diagrams and figures number 4, 5 and 7 be explained in more detail.
3- It is suggested that the conclusion section should be expanded and things such as practical study suggestions and research limitations and even suggestions for future research studies should be explained in detail in this section.
Author Response
Please see the attachment.
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
The paper has been revised according to the suggestions, and it can be accepted after the revised language.
Author Response
Please see the attachment.
Author Response File: Author Response.docx
