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Machines
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Advances in Process Machine Interactions
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Advances in Process Machine Interactions

A special issue of Machines (ISSN 2075-1702).

Deadline for manuscript submissions: closed (30 April 2017) | Viewed by 14252

Special Issue Editor

Prof. Dr. Hongrui Cao

E-Mail Website
Guest Editor
School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Interests: dynamnic modeling and fault diagnosis of machinery
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In order to improve product quality and lower production costs, machine tools are continually being improved with respect to their rotating speed, acceleration, and process force. Moreover, processes are also continually undergoing optimization. However, the machine and the process are not independent of each other. The continuity of interaction, i.e., the continuous and mutual influence exerted by both machine and process, results in the unpredictable effects on workpieces. It has been considered necessary to treat processes and machine structures in an integrated way, thereby overcoming the widespread independent treatment of such systems.

This Special Issue aims to bring together papers that report recent advances and challenges in addressing problems and finding new solutions for process machine interactions. With this call for papers, we hope to deliver readers promising new ideas and directions for future developments in this area. Topics include, but are not limited to:

  • Process modeling and simulation in cutting, grinding and forming operations.
  • Machine tool modeling, including spindles, feed drives, guideways, etc.
  • Virtual machining: simulation/optimization of machining process in virtual environment.
  • Chatter prediction, detection and control/suppression.
  • Process planning of machining operations.
  • Machining process monitoring and control, including tool wear/breakage, chatter, collision, temperatures/thermal error, balancing state, etc.
  • Experimental and industrial applications.

Dr. Hongrui Cao
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Process machine interactions
  • Process modeling
  • Machine tool modeling
  • Virtual machining
  • Chatter
  • Process monitoring and control

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

5265 KiB  
Article
Root Cause Identification of Machining Error Based on Statistical Process Control and Fault Diagnosis of Machine Tools
by Hongrui Cao, Denghui Li and Yiting Yue
Machines 2017, 5(3), 20; https://doi.org/10.3390/machines5030020 - 6 Sep 2017
Cited by 7 | Viewed by 6715
Abstract
The essence of the machining process is the interaction that occurs between machine tools and a workpiece under certain conditions of cutting parameters. Root cause identification (RCI) is critical to the quality control and productivity improvement of machining processes. The geometric error caused [...] Read more.
The essence of the machining process is the interaction that occurs between machine tools and a workpiece under certain conditions of cutting parameters. Root cause identification (RCI) is critical to the quality control and productivity improvement of machining processes. The geometric error caused by fixture faults can be identified in most RCI methods; however, the influence of machine tool degradation on workpiece quality is usually neglected. In this paper, a novel root cause identification scheme of machining error based on statistical process control and fault diagnosis of machine tools is proposed. With the pattern recognition of control charts, quality fluctuations can be detected in a timely manner. Once the machining error occurs, the fault diagnosis of machine tools are carried out. The relationship between machine tool condition and workpiece quality is established and the root cause identification of the machining error can be achieved. A case study of the machining of a complex welded box-type workpiece is presented to illustrate the feasibility of the proposed scheme. It is found that the coaxiality error of the two holes in two sides of the box’s wall is caused by the wear of the worm gear in the rotary work table of the machine tool. Full article
(This article belongs to the Special Issue Advances in Process Machine Interactions)
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5440 KiB  
Article
A Reliable Turning Process by the Early Use of a Deep Simulation Model at Several Manufacturing Stages
by Gorka Urbikain, Alvaro Alvarez, Luis Norberto López de Lacalle, Mikel Arsuaga, Miguel A. Alonso and Fernando Veiga
Machines 2017, 5(2), 15; https://doi.org/10.3390/machines5020015 - 2 May 2017
Cited by 26 | Viewed by 6890
Abstract
The future of machine tools will be dominated by highly flexible and interconnected systems, in order to achieve the required productivity, accuracy, and reliability. Nowadays, distortion and vibration problems are easily solved in labs for the most common machining operations by using models [...] Read more.
The future of machine tools will be dominated by highly flexible and interconnected systems, in order to achieve the required productivity, accuracy, and reliability. Nowadays, distortion and vibration problems are easily solved in labs for the most common machining operations by using models based on the equations describing the physical laws of the machining processes; however, additional efforts are needed to overcome the gap between scientific research and real manufacturing problems. In fact, there is an increasing interest in developing simulation packages based on “deep-knowledge and models” that aid machine designers, production engineers, or machinists to get the most out of the machine-tools. This article proposes a methodology to reduce problems in machining by means of a simulation utility, which uses the main variables of the system and process as input data, and generates results that help in the proper decision-making and machining plan. Direct benefits can be found in (a) the fixture/clamping optimal design; (b) the machine tool configuration; (c) the definition of chatter-free optimum cutting conditions and (d) the right programming of cutting toolpaths at the Computer Aided Manufacturing (CAM) stage. The information and knowledge-based approach showed successful results in several local manufacturing companies and are explained in the paper. Full article
(This article belongs to the Special Issue Advances in Process Machine Interactions)
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