Alkan Donmez

Additive Manufacturing: Current State, Future Potential, Gaps and Needs, and Recommendations

Additive manufacturing (AM), the process of joining materials to make objects from three-dimensional (3D) model data, usually layer by layer, is distinctly a different form and has many advantages over traditional manufacturing processes. Commonly known as “3D printing,” AM provides a cost-effective and time-efficient way to produce low-volume, customized products with complicated geometries and advanced material properties and functionality. As a result of the 2013 National Science Foundation (NSF) Workshop on Frontiers of Additive Manufacturing Research and Education, this paper summarizes AMs current state, future potential, gaps and needs, as well as recommendations for technology and research, university–industry collaboration and technology transfer, and education and training.

Kinematic couplings for precision fixturing — Part 2: Experimental determination of repeatability and stiffness

Abstract Results of tests performed to determine the repeatability of a large kinematic coupling are described. The coupling was constructed from two 356 mm (14 in) diameter 102 mm (4 in) thick cast iron discs with hardened steel gothic arch insects and 28.6 mm (1.125 in) diameter balls. A special load frame was constructed for performing cyclic tests of kinematic coupling while applying a 5800 N (1300 lbf) preload. Different types of balls and lubrication at the interface were tested. When using lubricated silicon nitride balls, axial and radial 3σ repeatability was on the order of 0.30 μm (12 μin). Worst case axial and radial stiffness was on the order of 1.09 × 10 8 N m −1 (0.62 × 10 6 lbf in −1 ) and 1.58 × 10 8 N m −1 (0.90 × 10 6 lbf in −1 ) , respectively, and at best was twice these values. Machined surface finishes on the order of 0.3 μm (12 μin) were obtained while using the coupling to hold a 304 stainless steel part machined with a depth of cut of 0.13 mm (0.005 in) at a rate of 55 surface metres per minute (180 SFM).

Uncertainty of temperature measurements by infrared thermography for metal cutting applications

This paper presents a comprehensive analysis of the uncertainty in the measurement of the peak temperature on the side face of a cutting tool, during the metal cutting process, by infrared thermography. The analysis considers the use of a commercial off-the-shelf camera and optics, typical of what is used in metal cutting research. A physics-based temperature measurement equation is considered and an analytical method is used to propagate the uncertainties associated with measurement variables to determine the overall temperature measurement uncertainty. A Monte Carlo simulation is used to expand on the analytical method by incorporating additional sources of uncertainty such as a point spread function (PSF) of the optics, difference in emissivity of the chip and tool, and motion blur. Further discussion is provided regarding the effect of sub-scenel averaging and magnification on the measured temperature values. It is shown that a typical maximum cutting tool temperature measurement results in an expanded uncertainty of U = 50.1 °C (k = 2). The most significant contributors to this uncertainty are found to be uncertainties in cutting tool emissivity and PSF of the imaging system.

Smart machining systems: issues and research trends

Smart Machining Systems (SMS) are an important part of Life Cycle Engineering (LCE) since its capabilities include: producing the first and every product correct; improving the response of the production system to changes in demand (just in time); realizing rapid manufacturing; and, providing data on an as needed basis. Thereby, SMS improve the performance of production systems and reduce production costs. In addition, an SMS not only has to improve a particular machining process, but it also has to determine the best optimized solution to produce the part faster, better, at lower cost, and with a minimum impact on the environment. In addition, new software tools are required to facilitate the improvement of a machining system, characterized by a high level of expertise or heuristic methods. A global approach requires integrating knowledge/information about the product design, production equipment, and machining process. This paper first discusses the main characteristics and components that are envisioned to be part of SMS. Then, uncertainties associated with models and data and the optimization tasks in SMS are discussed. Robust Optimization is an approach for coping with such uncertainties in SMS. Current use of machining models by production engineers and associated problems are discussed. Finally, the paper discusses interoperability needs for integrating SMS into the product life cycle, as well as the need for knowledge-based systems. The paper ends with a description of future research trends and work plans.

Friction characterization experiments on a single point diamond turning machine tool

Abstract Sub-micron precision machining requires very precise position and speed control of the motion of the machine tool axes. The accuracy of coordinated position control determines the profile accuracy of a part in contour machining, while the accuracy of speed control is the most significant factor in the resulting sub-surface damage that may occur in contour or non-contour machining. In high precision machining of brittle materials, it is desirable that the chip removal process be in the ductile regime of the material. The fundamental hypothesis is that if ductile regime chip removal is not accomplished, sub-surface damage will occur on the machined part. Although this can be partially corrected by removing the damaged layer by polishing, that is a very slow manual and costly operation. Therefore, it is desirable to machine such parts at the ductile regime to avoid sub-surface damage. Such a chip removal process requires precise control of feed rates at extremely slow speeds. This motion control problem is difficult due to the large friction and the unpredictable nature of the friction at very low speeds. The standard proportional-integral-derivative (PID) type servo control algorithms are not capable of delivering the desired precision in motion control. The friction must be accurately compensated for by the real-time control algorithm. This requires an accurate means of predicting the friction on-line. To this end, off-line experiments, designed with statistical considerations of factors affecting friction, were conducted. The data collected from these experiments were analyzed to understand the friction characteristics and to develop appropriate model structures for on-line predictions.

Measurement of powder bed density in powder bed fusion additive manufacturing processes

Many factors influence the performance of additive manufacturing (AM) processes, resulting in a high degree of variation in process outcomes. Therefore, quantifying these factors and their correlations to process outcomes are important challenges to overcome to enable widespread adoption of emerging AM technologies. In the powder bed fusion AM process, the density of the powder layers in the powder bed is a key influencing factor. This paper introduces a method to determine the powder bed density (PBD) during the powder bed fusion (PBF) process. A complete uncertainty analysis associated with the measurement method was also described. The resulting expanded measurement uncertainty, U PBD (k = 2), was determined as 0.004 g cm−3. It was shown that this expanded measurement uncertainty is about three orders of magnitude smaller than the typical powder bed density. This method enables establishing correlations between the changes in PBD and the direction of motion of the powder recoating arm.

An IEEE 1451.5–802.11 standard-based wireless sensor network with embedded WTIM

This paper introduces a reference implementation of the Institute of Electrical and Electronics Engineers (IEEE) 1451.5–802.11 standard-based wireless sensor network (WSN) developed at the National Institute of Standards and Technology (NIST). The WSN consists of a Network Capable Application Processor (NCAP) and two Wireless Transducer Interface Modules (WTIM). The NCAP, a gateway node of the WSN, was developed on a laptop in Java language according to the IEEE 1451.5–802.11 standard. The embedded WTIM, a wireless sensor node, was developed based on the IEEE 1451.5–802.11 standard on a single board computer in Dynamic C language. The wireless communications between the NCAP and WTIMs are based on IEEE 1451.0 messages using Transmission Control Protocol/Internet Protocol (TCP/IP) and User Datagram Protocol/Internet Protocol (UDP/IP) sockets. A few examples are provided to illustrate the functionalities of the WSN.

Development of a metrology frame to improve the positioning accuracy of micro/meso-scale machine tools

The small work volumes of Micro/Meso-scale Machine Tools (MMMTs) often present problems for calibration and error compensation, but also allow solutions not practical on the traditional scale. Measuring tool position with a separate metrology frame and compensating for error motions is one such solution. The metrology frame design follows principles of precision design and allows measurement of the position of the tool tip with respect to the workpiece while minimising Abbe errors. Kinematic analysis provides the relationship between metrology frame measurements and machine tool coordinates. Error analysis reveals that sensor error has the only first order influence on measurement accuracy.

Robust Optimization for Smart Machining Systems: An Enabler for Agile Manufacturing

This paper reports our efforts towards developing a mathematical and information framework for optimization of machining processes within a Smart Machining System (SMS). An SMS uses diverse integrated technologies that enable an enterprise to: (1) produce the first and every product correct; (2) improve the response of the production system to changes in demand (just in time); (3) realize rapid and agile manufacturing; and (4) provide data to the rest of the enterprise as needed. Optimization of machining processes is an important component of an SMS and contributes to realizing these capabilities. Based on a prototype, we demonstrate the concepts for robust optimization within an SMS and develop requirements and challenges for robust optimization in an SMS.

Interlaboratory Study for Nickel Alloy 625 Made by Laser Powder Bed Fusion to Quantify Mechanical Property Variability

Six different organizations participated in this interlaboratory study to quantify the variability in the tensile properties of Inconel 625 specimens manufactured using laser powder bed fusion-additive manufacturing machines. The tensile specimens were heat treated and tensile tests were conducted until failure. The properties measured were yield strength, ultimate tensile strength, elastic modulus, and elongation. Statistical analysis revealed that between-participant variability for yield strength, ultimate tensile strength, and elastic modulus values were significantly higher (up to four times) than typical within-participant variations. Only between-participant and within-participant variability were both similar for elongation. A scanning electron microscope was used to examine one tensile specimen for fractography. The fracture surface does not have many secondary cracks or other features that would reduce the mechanical properties. In fact, the features largely consist of microvoid coalescence and are entirely consistent with ductile failure.