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JMMP
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Progress in Digital Twin Integration for Smart Machining
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Progress in Digital Twin Integration for Smart Machining

A special issue of Journal of Manufacturing and Materials Processing (ISSN 2504-4494).

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 21809

Special Issue Editor

Prof. Dr. Tuğrul Özel

E-Mail Website
Guest Editor
Industrial & Systems Engineering, Rutgers University—New Brunswick, 96 Frelinghuysen Rd, Piscataway, NJ 08854, USA
Interests: advanced manufacturing; additive manufacturing; automation; laser processing; machine learning; medical devices; micro-manufacturing; precision machining; predictive process modeling; process simulations; process optimization

Special Issue Information

The manufacturing industry is confronted with increasing demands of digitalization and ever-increasing global competitiveness. Successful development and implementation of digital twin for machining processes as key enablers for quality assurance require close collaboration between the physical world and virtual world, realistic digitization, and model reliability of the virtual representation.

This Special Issue aims to bring researchers together concerning the latest advances and progress in the integration of digital models, digital shadows, or digital twin using physics-based models, surrogate models, and supervised machine learning methods. This Special Issue invites the submission of high-quality research articles related to Progress in Digital Twin Integration for Smart Machining, including but not limited to:

  • Digital representation of machining process including mathematical, simulation models, etc.;
  • Discretized force model, cutting tool discretization;
  • Dynamic force model, surface location error model;
  • Digital shadow or digital twin;
  • Digital models with one-way or two-way automated data flow between physical and digital machining.

All submissions should be directly related to manufacturing or materials processing. Manuscripts should include experimental validation by using either authors own data or data from published literature and cannot be purely simulation work.

Prof. Dr. Tuğrul Özel
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. Journal of Manufacturing and Materials Processing is an international peer-reviewed open access semimonthly 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 1800 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.

Published Papers (6 papers)

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Research

16 pages, 3235 KiB  
Article
Laser Scanning Based Object Detection to Realize Digital Blank Shadows for Autonomous Process Planning in Machining
by Berend Denkena, Marcel Wichmann, Klaas Maximilian Heide and René Räker
J. Manuf. Mater. Process. 2022, 6(1), 1; https://0-doi-org.brum.beds.ac.uk/10.3390/jmmp6010001 - 22 Dec 2021
Cited by 2 | Viewed by 3443
Abstract
The automated process chain of an unmanned production system is a distinct challenge in the technical state of the art. In particular, accurate and fast raw-part recognition is a current problem in small-batch production. This publication proposes a method for automatic optical raw-part [...] Read more.
The automated process chain of an unmanned production system is a distinct challenge in the technical state of the art. In particular, accurate and fast raw-part recognition is a current problem in small-batch production. This publication proposes a method for automatic optical raw-part detection to generate a digital blank shadow, which is applied for adapted CAD/CAM (computer-aided design/computer-aided manufacturing) planning. Thereby, a laser-triangulation sensor is integrated into the machine tool. For an automatic raw-part detection and a workpiece origin definition, a dedicated algorithm for creating a digital blank shadow is introduced. The algorithm generates adaptive scan paths, merges laser lines and machine axis data, filters interference signals, and identifies part edges and surfaces according to a point cloud. Furthermore, a dedicated software system is introduced to investigate the created approach. This method is integrated into a CAD/CAM system, with customized software libraries for communication with the CNC (computer numerical control) machine. The results of this study show that the applied method can identify the positions, dimensions, and shapes of different raw parts autonomously, with deviations less than 1 mm, in 2.5 min. Moreover, the measurement and process data can be transferred without errors to different hardware and software systems. It was found that the proposed approach can be applied for rough raw-part detection, and in combination with a touch probe for accurate detection. Full article
(This article belongs to the Special Issue Progress in Digital Twin Integration for Smart Machining)
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16 pages, 6385 KiB  
Article
Anticipatory Online Compensation of Tool Deflection Using a Priori Information from Process Planning
by Berend Denkena, Benjamin Bergmann and Tim Schumacher
J. Manuf. Mater. Process. 2021, 5(3), 90; https://0-doi-org.brum.beds.ac.uk/10.3390/jmmp5030090 - 17 Aug 2021
Viewed by 2414
Abstract
Removing excess material from build-up welding by milling is a critical step in the repair of blades from aircraft engines. This so-called recontouring is a very challenging machining task. Shape deviations often result from the deflection of tool and workpiece due to process [...] Read more.
Removing excess material from build-up welding by milling is a critical step in the repair of blades from aircraft engines. This so-called recontouring is a very challenging machining task. Shape deviations often result from the deflection of tool and workpiece due to process forces. Considering the individuality of repair cases, compensation of those deflections by process force measurement and online tool path adaption is a very suitable method. However, there is one caveat to this reactive approach. Due to causality, a corrective movement, following a force variation, is always delayed by a finite reaction time. At this moment, though, the displacement has already manifested itself as a deviation in the machined surface. To overcome those limitations and to improve compensation beyond the reduction of control delays, this study proposes a novel approach of anticipatory online compensation. Flank-milling experiments with abrupt changes in the tool-workpiece engagement conditions are conducted to investigate the limitations of reactive compensation and to explore the potential of the new anticipatory approach. Full article
(This article belongs to the Special Issue Progress in Digital Twin Integration for Smart Machining)
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18 pages, 6385 KiB  
Article
Digital Twins for High-Tech Machining Applications—A Model-Based Analytics-Ready Approach
by Albrecht Hänel, André Seidel, Uwe Frieß, Uwe Teicher, Hajo Wiemer, Dongqian Wang, Eric Wenkler, Lars Penter, Arvid Hellmich and Steffen Ihlenfeldt
J. Manuf. Mater. Process. 2021, 5(3), 80; https://0-doi-org.brum.beds.ac.uk/10.3390/jmmp5030080 - 27 Jul 2021
Cited by 29 | Viewed by 5930
Abstract
This paper presents a brief introduction to competition-driven digital transformation in the machining sector. On this basis, the creation of a digital twin for machining processes is approached firstly using a basic digital twin structure. The latter is sub-grouped into information and data [...] Read more.
This paper presents a brief introduction to competition-driven digital transformation in the machining sector. On this basis, the creation of a digital twin for machining processes is approached firstly using a basic digital twin structure. The latter is sub-grouped into information and data models, specific calculation and process models, all seen from an application-oriented perspective. Moreover, digital shadow and digital twin are embedded in this framework, being discussed in the context of a state-of-the-art literature review. The main part of this paper addresses models for machine and path inaccuracies, material removal and tool engagement, cutting force, process stability, thermal behavior, workpiece and surface properties. Furthermore, these models are superimposed towards an integral digital twin. In addition, the overall context is expanded towards an integral software architecture of a digital twin providing information system. The information system, in turn, ties in with existing forward-oriented planning from operational practice, leading to a significant expansion of the initially presented basic structure for a digital twin. Consequently, a time-stratified data layer platform is introduced to prepare for the resulting shadow-twin transformation loop. Finally, subtasks are defined to assure functional interfaces, model integrability and feedback measures. Full article
(This article belongs to the Special Issue Progress in Digital Twin Integration for Smart Machining)
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16 pages, 10510 KiB  
Article
Physics-Based Simulations of Chip Flow over Micro-Textured Cutting Tool in Orthogonal Cutting of Alloy Steel
by Kaushalendra V. Patel, Krzysztof Jarosz and Tuğrul Özel
J. Manuf. Mater. Process. 2021, 5(3), 65; https://0-doi-org.brum.beds.ac.uk/10.3390/jmmp5030065 - 22 Jun 2021
Cited by 14 | Viewed by 2647
Abstract
Physics-based process simulations have the potential to allow virtual process design and the development of digital twins for smart machining applications. This paper presents 3D cutting simulations using the finite element method (FEM) and investigates the physical state variables that are fundamental to [...] Read more.
Physics-based process simulations have the potential to allow virtual process design and the development of digital twins for smart machining applications. This paper presents 3D cutting simulations using the finite element method (FEM) and investigates the physical state variables that are fundamental to the reduction in cutting forces, friction, and tool wear when micro-textured cutting tools are employed. For this goal, textured cemented carbide cutting tool inserts are designed, fabricated, and tested in the orthogonal dry cutting of a nickel-chromium-molybdenum alloy steel. Cutting forces and friction coefficients are compared against the non-textured tool, revealing the effects of texture parameters. Chip flow over the textured tool surface and process variables at the chip-tool contact are investigated and compared. The results reveal the fundamental sources of such improvements. Archard’s wear rate as a composition of process variables is utilized to compare experimental and simulated wear on the textured cutting tools. The effects of texture and cutting conditions on tool wear and adhesion characteristics are further discussed on the simulation results with experimental comparisons. It was found that the results obtained from these simulations provide further fundamental insights about the micro-textured cutting tools. Full article
(This article belongs to the Special Issue Progress in Digital Twin Integration for Smart Machining)
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21 pages, 9387 KiB  
Article
Simulation Based Prediction of Compliance Induced Shape Deviations in Internal Traverse Grinding
by Tountzer Tsagkir Dereli, Nils Schmidt, Tim Furlan, Raphael Holtermann, Dirk Biermann and Andreas Menzel
J. Manuf. Mater. Process. 2021, 5(2), 60; https://0-doi-org.brum.beds.ac.uk/10.3390/jmmp5020060 - 08 Jun 2021
Cited by 3 | Viewed by 2971
Abstract
Internal traverse grinding (ITG) using electroplated cBN tools in high-speed grinding conditions is a highly efficient manufacturing process for bore machining in a single axial stroke. However, process control is difficult. Due to the axial direction of feed, changes in process normal force [...] Read more.
Internal traverse grinding (ITG) using electroplated cBN tools in high-speed grinding conditions is a highly efficient manufacturing process for bore machining in a single axial stroke. However, process control is difficult. Due to the axial direction of feed, changes in process normal force and thus radial deflection of the tool and workpiece spindle system, lead to deviations in the workpiece contour along the length of the bore, especially at tool exit. Simulations including this effect could provide a tool to design processes which enhance shape accuracy of components. A geometrical physically-based simulation is herein developed to model the influence of system compliance on the resulting workpiece contour. Realistic tool topographies, obtained from measurements, are combined with an FE-calibrated surrogate model for process forces and with an empirical compliance model. In quasistatic experimental investigations, the spindle deflection is determined in relation to the acting normal forces by using piezoelectric force measuring elements and eddy current sensors. In grinding tests with in-process force measurement technology and followed by measurement of the resulting workpiece contours, the simulation system is validated. The process forces and the resulting characteristic shape deviations are predicted in good qualitative accordance with the experimental results. Full article
(This article belongs to the Special Issue Progress in Digital Twin Integration for Smart Machining)
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10 pages, 10011 KiB  
Communication
An Approach to Detect White Spots during Pre-Turning of DA718 Components
by Daniel Pfirrmann, Jonas Baumann, Eugen Krebs, Dirk Biermann and Petra Wiederkehr
J. Manuf. Mater. Process. 2021, 5(2), 57; https://0-doi-org.brum.beds.ac.uk/10.3390/jmmp5020057 - 01 Jun 2021
Cited by 1 | Viewed by 2639
Abstract
The increasing demand for high-performance components is leading to a greater use of advanced alloys such as DA718, which is, e.g., used in engine parts due to its high-temperature strength. The strict quality requirements pose major challenges for the machining of engine components [...] Read more.
The increasing demand for high-performance components is leading to a greater use of advanced alloys such as DA718, which is, e.g., used in engine parts due to its high-temperature strength. The strict quality requirements pose major challenges for the machining of engine components for aircrafts. Quality deviations along the value chain can lead to high costs due to rework and, in the worst case, rejections in order to prevent material failure within a safety-critical environment. These deviations include, e.g., an increased surface roughness, deviations in the shape tolerances as well as increased internal stresses or surface deformations. Material defects are an additional reason to reject the manufactured components. These are usually inspected only at the end of the value chain and—due to measurement limitations—only if they occur close to the surface of the workpiece. Ultrasonic testing is used in order to detect defects near the surface of the raw part. For the evaluation of the finished part, etching and optical inspection of the surface is used. However, defects inside the components cannot be detected in this way. If material defects are located in areas subjected to intense load changes and high temperatures, the components have to be rejected since engine parts require a high level of fatigue strength. Such rejects constitute a significant economic risk, as a large part of the added value has already been completed and a significant amount of machine time has been invested. Thus, an identification of material defects in an earlier stage of the manufacturing process is required. In this paper, fundamental investigations on machining artificially generated material defects in a micro-milling process and the signal analysis during the pre-turning of turbine disks made of nickel-based materials like DA718 will be presented. Based on force measurements, characteristic signals were identified that could indicate material defects during the turning process. Full article
(This article belongs to the Special Issue Progress in Digital Twin Integration for Smart Machining)
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