Showing papers in "Journal of Manufacturing Science and Engineering-transactions of The Asme in 2015"

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

Abstract: 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 AM's 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.

Online Real-Time Quality Monitoring in Additive Manufacturing Processes Using Heterogeneous Sensors

Abstract: The objective of this work is to identify failure modes and detect the onset of process anomalies in additive manufacturing (AM) processes, specifically focusing on fused filament fabrication (FFF). We accomplish this objective using advanced Bayesian nonparametric analysis of in situ heterogeneous sensor data. Experiments are conducted on a desktop FFF machine instrumented with a heterogeneous sensor array including thermocouples, accelerometers, an infrared (IR) temperature sensor, and a real-time miniature video borescope. FFF process failures are detected online using the nonparametric Bayesian Dirichlet process (DP) mixture model and evidence theory (ET) based on the experimentally acquired sensor data. This sensor data-driven defect detection approach facilitates real-time identification and correction of FFF process drifts with an accuracy and precision approaching 85% (average F-score). In comparison, the F-score from existing approaches, such as probabilistic neural networks (PNN), naive Bayesian clustering, support vector machines (SVM), and quadratic discriminant analysis (QDA), was in the range of 55–75%.

Manufacturing Service Management in Cloud Manufacturing: Overview and Future Research Directions

Abstract: As a new service-oriented manufacturing paradigm, cloud manufacturing (CMfg) has experienced rapid development in the past five years. The research on its theories, key technologies, developments, and applications still keeps attracting attentions from more and more researchers. One of the most important issues to its improvements and quality of service (QoS) is the manufacturing service management (MSM). CMfg aims to realize the full-scale sharing, free circulation and transaction, and on-demand use of various manufacturing resource and capabilities in the form of manufacturing service. Without the effective operation and technical support of MSM, the implementation of CMfg and its aim cannot be achieved. It is therefore necessary to summarize the existing works and technologies on MSM in CMfg. This paper first provides a brief overview of CMfg and then focuses on the problem of MSM in CMfg from the service lifecycle perspective. The advances on MSM technology from eleven aspects are investigated and summarized. Finally, future research directions are identified and discussed. It is evident that the future MSM in CMfg is closely related to Internet of things (IoT), big data, and cloud computing.

Development of a Low-Cost Parallel Kinematic Machine for Multidirectional Additive Manufacturing

Abstract: Most additive manufacturing (AM) processes are layer-based with three linear motions in the X, Y, and Z axes. However, there are drawbacks associated with such limited motions, e.g., nonconformal material properties, stair-stepping effect, and limitations on building-around-inserts. Such drawbacks will limit AM to be used in more general applications. To enable 6-axis motions between a tool and a work piece, we investigated a Stewart mechanism and the feasibility of developing a low-cost 3D printer for the multidirectional fused deposition modeling (FDM) process. The technical challenges in developing such an AM system are discussed including the hardware design, motion planning and modeling, platform constraint checking, tool motion simulation, and platform calibration. Several test cases are performed to illustrate the capability of the developed multidirectional AM system. A discussion of future development on multidirectional AM systems is also given. [DOI: 10.1115/1.4028897]

Cloud based platform for optimal machining parameter selection based on function blocks and real time monitoring

Abstract: The way machining operations have been running has changed over the years. Nowadays, machine utilization and availability monitoring are becoming increasingly important for the smooth operation of modern workshops. Moreover, the nature of jobs undertaken by manufacturing small and medium enterprises (SMEs) has shifted from a mass production to small batch. To address the challenges caused by modern fast changing environments, a new cloud-based approach for monitoring the use of manufacturing equipment, dispatching jobs to the selected computer numerical control (CNC) machines, and creating the optimum machining code is presented. In this approach the manufacturing equipment is monitored using a sensor network and though an information fusion technique it derives and broadcasts the data of available tools and machines through the internet to a cloud-based platform. On the manufacturing equipment event driven function blocks with embedded optimization algorithms are responsible for selecting the optimal cutting parameters and generating the moves required for machining the parts while considering the latest information regarding the available machines and cutting tools. A case study based on scenario from a shop floor that undertakes machining jobs is used to demonstrate the developed methods and tools.

Selective Laser Melting Additive Manufacturing of Novel Aluminum Based Composites With Multiple Reinforcing Phases

Abstract: Donghua Dai College of Materials Science and Technology, Nanjing University of Aeronautics and Astronautics (NUAA), Yudao Street 29, Nanjing 210016, China; Institute of Additive Manufacturing (3D Printing), Nanjing University of Aeronautics and Astronautics (NUAA), Yudao Street 29, Nanjing 210016, China Selective Laser Melting Additive Manufacturing of Novel Aluminum Based Composites With Multiple Reinforcing Phases

A Generalized Feed Forward Dynamic Adaptive Mesh Refinement and Derefinement Finite Element Framework for Metal Laser Sintering—Part I: Formulation and Algorithm Development

Abstract: A novel multiscale thermal analysis framework has been formulated to extract the physical interactions involved in localized spatiotemporal additive manufacturing processes such as the metal laser sintering. The method can be extrapolated to any other physical phenomenon involving localized spatiotemporal boundary conditions. The formulated framework, named feed forward dynamic adaptive mesh refinement and derefinement (FFD-AMRD), reduces the computational burden and temporal complexity needed to solve the many classes of problems. The current study is based on application of this framework to metals with temperature independent thermal properties processed using a moving laser heat source. The melt pool diameters computed in the present study were compared with melt pool dimensions measured using optical micrographs. The strategy developed in this study provides motivation for the extension of this simulation framework for future work on simulations of metals with temperature-dependent material properties during metal laser sintering.

Cloud Manufacturing: Current Trends and Future Implementations

Abstract: Manufacturing technology changes with the needs of consumers. The globalization of the world economy has helped to create the concept of cloud manufacturing (CM). The purpose of this paper is to provide both an overview and an update on the status of CM and define the key technologies that are being developed to make CM a dependable configuration in today's manufacturing industry. Topics covered include: cloud computing (CC), the role of small and medium enterprises (SMEs), pay-as-you-go, resource virtualization, interoperability, security, equipment control, and the future outlook of the development of CM.

A Line Heat Input Model for Additive Manufacturing

Abstract: A line input model has been developed which makes the accurate modeling of powder bed processes more computationally efficient. Goldak’s ellipsoidal model has been used extensively to model heat sources in additive manufacturing, including lasers and electron beams. To accurately model the motion of the heat source, the simulation time increments must be small enough such that the source moves a distance smaller than its radius over the course of each increment. When the source radius is small and its velocity is large, a strict condition is imposed on the size of time increments regardless of any stability criteria. In powder bed systems, where radii of 0.1 mm and velocities of 500 mm/s are typical, a significant computational burden can result. The line heat input model relieves this burden by averaging the heat source over its path. This model allows the simulation of an entire heat source scan in just one time increment. However, such large time increments can lead to inaccurate results. Instead, the scan is broken up into several linear segments, each of which is applied in one increment. In this work, time increments are found that yield accurate results (less than 10 % displacement error) and require less than 1/10 of the CPU time required by Goldak’s moving source model. A dimensionless correlation is given that can be used to determine the necessary time increment size that will greatly decrease the computational time required for any powder bed simulation while maintaining accuracy.Copyright © 2015 by ASME

Mask-Less Electrochemical Additive Manufacturing: A Feasibility Study

Abstract: Additive manufacturing (AM) of metallic structures by laser based layered manufacturing processes involve thermal damages. In this work, the feasibility of mask-less electrochemical deposition as a nonthermal metallic AM process has been studied. Layer by layer localized electrochemical deposition using a microtool tip has been performed to manufacture nickel microstructures. Three-dimensional free hanging structures with about 600 μm height and 600 μm overhang are manufactured to establish the process capability. An inhouse built CNC system was integrated in this study with an electrochemical cell to achieve 30 layers thick microparts in about 5 h by AM directly from STL files generated from corresponding CAD models. The layer thickness achieved in this process was about 10 μm and the minimum feature size depends on the tool width. Simulation studies of electrochemical deposition performed to understand the pulse wave characteristics and their effects on the localization of the deposits.

Analysis of Weld Formation in Multilayer Ultrasonic Metal Welding Using High-Speed Images

Abstract: One of the major challenges in manufacturing automotive lithium-ion batteries and battery packs is to achieve consistent weld quality in joining multiple layers of dissimilar materials. While most fusion welding processes face difficulties in such joining, ultrasonic welding stands out as the ideal method. However, inconsistency of weld quality still exists because of limited knowledge on the weld formation through the multiple interfaces. This study aims to establish real-time phenomenological observation on the multilayer ultrasonic welding process by analyzing the vibration behavior of metal layers. Such behavior is characterized by a direct measurement of the lateral displacement of each metal layer using high-speed images. Two different weld tools are used in order to investigate the effect of tool geometry on the weld formation mechanism and the overall joint quality. A series of microscopies and bond density measurements is carried out to validate the observations and hypotheses of those phenomena in multilayer ultrasonic welding. The results of this study enhance the understanding of the ultrasonic welding process of multiple metal sheets and provide insights for optimum tool design to improve the quality of multilayer joints.Copyright © 2015 by ASME and General Motors

A selective multiclass support vector machine ensemble classifier for engineering surface classification using high definition metrology

Abstract: The surface appearance is sensitive to change in the manufacturing process and is one of the most important product quality characteristics The classification of workpiece surface patterns is critical for quality control, because it can provide feedback on the manufacturing process In this study, a novel classification approach for engineering surfaces is proposed by combining dual-tree complex wavelet transform (DT-CWT) and selective ensemble classifiers called modified matching pursuit optimization with multiclass support vector machines ensemble (MPO-SVME), which adopts support vector machine (SVM) as basic classifiers The dual-tree wavelet transform is used to decompose three-dimensional (3D) workpiece surfaces, and the features of workpiece surface are extracted from wavelet sub-bands of each level Then MPO-SVME is developed to classify different workpiece surfaces based on the extracted features and the performance of the proposed approach is evaluated by computing its classification accuracy The performance of MPO-SVME is validated in case study, and the results demonstrate that MPO-SVME can increase the classification accuracy with only a handful of selected classifiers

A Semantic Information Services Framework for Sustainable WEEE Management Toward Cloud-Based Remanufacturing

Abstract: Sustainable management ofWaste Electrical and Electronic Equipment (WEEE) has attracted escalating concerns of researchers and industries. Closer information linking among the participants in the products’ lifecycle should take place. How to interoperate among the distributed and heterogeneous information systems of various participants is a challenge faced. Targeting thecloud-based remanufacturing, this article aims to develop a semantic information services framework for sustainable WEEE management. In the proposed framework, an ontology-based approach is developed to integrate and represent the lifecycle information from multiple local data sources within an information services provider. Meanwhile, a semantic information services management platform is introduced for the advertisement, matchmaking, and retrieval of semantic information services. Some relevant techniques used to build the framework are introduced extensively. A demonstration case study on waste LCD TV is used to illustrate the effectiveness and significance of the proposed framework.

Prediction of Passive Maintenance Opportunity Windows on Bottleneck Machines in Complex Manufacturing Systems

Abstract: In this paper, we investigate hidden opportunities for performing proper maintenance tasks during production time without causing production losses. One of the maintenance opportunities on a machine is when the machine is starved or blocked due to the occurrence of random failures on its upstream or downstream machines. Such failure-induced starvation or blockage time is defined as a passive maintenance opportunity window (PMOW), and is predicted on the bottleneck machines in manufacturing systems with different configurations. The effectiveness of the PMOW prediction algorithm is validated through case studies in both simulations and an automotive assembly plant.

A General Method for the Dynamic Modeling of Ball Bearing–Rotor Systems

Abstract: A general dynamic modeling method of ball bearing–rotor systems is proposed. Gupta’s bearing model is applied to predict the rigid body motion of the system considering the three-dimensional motions of each part (i.e., outer ring, inner ring, ball, and rotor), lubrication tractions, and bearing clearances. The finite element method is used to model the elastic deformation of the rotor. The dynamic model of the whole ball bearing–rotor system is proposed by integrating the rigid body motion and the elastic vibration of the rotor. An experiment is conducted on a test rig of rotor supported by two angular contact ball bearings. The simulation results are compared with the measured vibration responses to validate the proposed model. Good agreements show the accuracy of the proposed model and its ability to predict the dynamic behavior of ball bearing–rotor systems. Based on the proposed model, vibration responses of a two bearing–rotor system under different bearing clearances were simulated and their characteristics were discussed. The proposed model may provide guidance for structural optimization, fault diagnosis, dynamic balancing, and other applications. [DOI: 10.1115/1.4029312]

Assessment of Microgrooved Cutting Tool in Dry Machining of AISI 1045 Steel

Abstract: This paper studies the performance of microgrooved cutting tool in dry orthogonal machining of mild steel (AISI 1045 steel) using advantedge finite element simulation. Microgrooves are designed on the rake face of cemented carbide (WC/Co) cutting inserts. The purpose is to examine the effect of microgroove textured tools on machining performance and to compare it with nontextured cutting tools. Specifically, the following groove parameters are examined: groove width, groove depth, and edge distance (the distance from cutting edge to the first groove). Their effects are assessed in terms of the main force, thrust force, and chip–tool contact length. It is found that microgrooved cutting tools generate lower cutting force and thrust force, and consequently lower the energy necessary for machining. The groove width, groove depth, and edge distance all have influence on cutting force in their own ways.

Review on Grinding Tool Wear With Regard to Sustainability

Abstract: Manufacturing processes have to become more sustainable. For grinding processes, this means that tool wear and performance need to be critically evaluated in their economic, environmental, and social impact. Tool wear affects several stakeholders. Different wear mechanisms on the grit and bond level lead to a change in tool profile and sharpness. For the user, wear changes tool costs, process stability, and maybe worker safety. Tool manufacturers need tool wear to sell replacements, whereas tool users might not like the higher waste and costs from tool wear but need tool self-sharpening.

On Cutting Temperature Measurement During Titanium Machining With an Atomization-Based Cutting Fluid Spray System

Abstract: The poor thermal conductivity and low elongation-to-break ratio of titanium lead to the development of extreme temperatures (in excess of 550 °C) localized in the tool–chip interface during machining of its alloys At such temperature level, titanium becomes highly reactive with most tool materials resulting in accelerated tool wear The atomization-based cutting fluid (ACF) spray system has recently been demonstrated to improve tool life in titanium machining due to good cutting fluid penetration causing the temperature to be reduced in the cutting zone In this study, the cutting temperatures are measured both by inserting thermocouples at various locations of the tool–chip interface and the tool–work thermocouple technique Cutting temperatures for dry machining and machining with flood cooling are also characterized for comparison with the ACF spray system temperature data Findings reveal that the ACF spray system more effectively reduces cutting temperatures over flood cooling and dry conditions The tool–chip friction coefficient indicates that the fluid film created by the ACF spray system also actively penetrates the tool–chip interface to enhance lubrication during titanium machining

Scalability Planning for Cloud-Based Manufacturing Systems

Abstract: Cloud-based manufacturing (CBM) has recently been proposed as an emerging manufacturing paradigm that may potentially change the way manufacturing services are provided and accessed. In the context of CBM, companies may opt to crowdsource part of their manufacturing tasks that are beyond their existing in-house manufacturing capacity to third-party CBM service providers by renting their manufacturing equipment instead of purchasing additional machines. To plan manufacturing scalability for CBM systems, it is crucial to identify potential manufacturing bottlenecks where the entire manufacturing system capacity is limited. Because of the complexity of manufacturing resource sharing behaviors, it is challenging to model and analyze the material flow of CBM systems in which sequential, concurrent, conflicting, cyclic, and mutually exclusive manufacturing processes typically occur. To address and further study this issue, we develop a stochastic Petri nets (SPNs) model to formally represent a CBM system, model and analyze the uncertainties in the complex material flow of the CBM system, evaluate manufacturing performance, and plan manufacturing scalability. We validate this approach by means of a delivery drone example that is used to demonstrate how manufacturers can indeed achieve rapid and cost-effective manufacturing scalability in practice by combining inhouse manufacturing and crowdsourcing in a CBM setting.

Microstructure Effects on Cutting Forces and Flow Stress in Ultra-Precision Machining of Polycrystalline Brittle Materials

Abstract: This paper presents a physics-based analysis to quantitatively describe the effects of grain size, grain boundaries, and crystallographic orientation on the flow stress of the polycrystalline material and thereby on the cutting and thrust forces. The model has been experimentally validated, in terms of the force intensities and sensitivities to microstructure attributes such as the grain size and the misorientation by comparing the forces to measured data in micromachining of polycrystalline silicon carbide (p-SiC). Molecular dynamics (MD) simulations are performed to explore the effects of grain boundaries and misorientation and to validate the modeling analysis in the context of resulting force ratios. [DOI: 10.1115/1.4029648]

Tool Wear Monitoring for Ultrasonic Metal Welding of Lithium-Ion Batteries

Abstract: This paper presents a tool wear monitoring framework for ultrasonic metal welding which has been used for lithium-ion battery manufacturing. Tool wear has a significant impact on joining quality. In addition, tool replacement, including horns and anvils, constitutes an important part of production costs. Therefore, a tool condition monitoring (TCM) system is highly desirable for ultrasonic metal welding. However, it is very challenging to develop a TCM system due to the complexity of tool surface geometry and a lack of thorough understanding on the wear mechanism. Here, we first characterize tool wear progression by comparing surface measurements obtained at different stages of tool wear, and then develop a tool condition classification algorithm to identify the state of wear. The developed algorithm is validated using tool measurement data from a battery plant.Copyright © 2015 by ASME and General Motors

Mechanics and Dynamics of Multifunctional Tools

Abstract: The mechanics and dynamics of the combined processes are presented for multifunctional tools, which can drill, bore, and chamfer holes in one operation. The oblique cutting forces on each cutting edge with varying geometry are modeled first, followed by their transformations to tangential, radial, and axial directions of the cutter. The regenerative effect of lateral and torsional/axial vibrations is considered in predicting the dynamic chip thickness with multiple delays due to distribution of cutting edges on the cutter body. The lateral and torsional/axial chatter stability of the complete hole making operation is predicted in semidiscrete time domain. The proposed static cutting force and chatter stability prediction models are experimentally proven for two different multifunctional tools in drilling Aluminum Al7050 and Steel AISI1045.