bluuebunny/crossref_metadata_2025_split huggingface dataset:
A New Joint Data-Model Driven Dynamic Scheduling Architecture for Intelligent Workshop
Authors: Peng Kunkun , Li Xinyu , Gao Liang , Wang Xi (Vincent) , Gao Yiping 
Published: November 2019

Abstract
Intelligent manufacturing plays a significant role in Industry 4.0. Dynamic shop scheduling is a key problem and hot research topic in the intelligent manufacturing systems, which is NP-hard. However, traditional shop scheduling mode, dynamic event prediction approach, scheduling model and scheduling algorithm, cannot cope with increasingly complicated problems under kinds of scales production disruptions in the real-world production. To deal with these problems, this paper proposes a new joint data-model driven dynamic scheduling architecture for intelligent workshop. The architecture includes four new and key characteristics in the aspects of scheduling mode, dynamic event prediction, scheduling model and algorithm. More specifically, the new scheduling mode introduces data analytics methods to quickly and accurately deal with the dynamic events encountered in the production process. The new prediction model improves the deep learning method, and further applies it predict the dynamic events accurately to provide reliable input to the dynamic scheduling. The new scheduling model proposes a new hybrid rescheduling and inverse scheduling model, which can cope with almost scales of abnormal production problems. The new scheduling algorithm hybridizes dynamic programming and intelligent optimization algorithm, which can overcome the disadvantages of the two methods based on the analysis of solution space. The dynamic programming is employed to provide high-quality initial solutions for the intelligent optimization algorithm by reducing the computation time greatly. To sum up, the presented architecture is a new attempt to understand the problem domain knowledge and broaden the solving idea, which can also provide new theories and technologies to manufacturing system optimization and promote the applications of the theoretical results.
Study of Effect of Teeth Number on Cutting Force for Cutter Selection in the End Milling of TC4
Authors: Shi Kaining , Liu Ning , Wang Sibao , Ma Chi , Yang Bo , Yi Lili , Kang Ling 
Published: November 2019

Abstract
Cutting force is a very important factor in machining processes for predicting chatter, surface roughness and machining efficiency. For a given cutter, cutting force is determined by cutting force coefficients and uncut chip thickness. Once a new cutter is adopted, repeated experiments are carried out to calibrate its cutting force coefficients. To reduce the high cost and longtime experiments, theoretical analysis of the effect of cutter parameters on cutting force is required. In current literatures, some cutter parameters, such as helix angle and pitch angle, have been studied to explore their effects on cutting force. However, there is little research about the effect of teeth number on the cutting force. To fill up this gap, the effect of teeth number on cutting force is studied in the paper. Firstly, it is derived and experimentally verified that the cutting force coefficients are unchanged for cutters with different teeth number but the same teeth parameters, e.g., rake angle, shear angle, etc. Secondly, by matching the measured cutting force point with the cutter rotation angle, the cutting force coefficients can be calibrated by only one experiment when we assume that the material of the cutter is the same. Therefore, the cutting forces generated by cutters with different teeth numbers can be predicted based on only one experiment. Thirdly, from the various comparisons, it is concluded that cutter with 2 teeth number is suggested for side milling and cutter with 3 teeth number is suggested for slotting when surface roughness is considered. The cutter with 5 teeth number is suggested when only the machining efficiency is concerned. Finally, various experiments are carried out to verify the proposed study in milling of titanium alloy Ti6Al4V (TC4), and the comparison results show a good agreement.
Friction Torque and Leakage Based Data-Driven Approach for Rotary Seal Prognostics in Manufacturing Industry
Authors: Ramachandran Madhumitha , Siddique Zahed 
Published: November 2019

Abstract
Rotary seals are found in many manufacturing equipment and machines used for various applications under a wide range of operating conditions. Rotary seal failure can be catastrophic and can lead to costly downtime and large expenses; so it is extremely important to assess the degradation of rotary seal to avoid fatal breakdown of machineries. Physics-based rotary seal prognostics require direct estimation of different physical parameters to assess the degradation of seals. Data-driven prognostics utilizing sensor technology and computational capabilities can aid in the in-direct estimation of rotary seals’ running condition unlike the physics-based approach. An important aspect of data-driven prognostics is to collect appropriate data in order to reduce the cost and time associated with the data collection, storage and computation. Seals in machineries operate in harsh conditions, especially in the oil field, seals are exposed to harsh environment and aggressive fluids which gradually reduces the elastic modulus and hardness of seals, resulting in lower friction torque and excessive leakage. Therefore, in this study we implement a data-driven prognostics approach which utilizes friction torque and leakage signals along with Multilayer Perceptron as a classifier to compare the performance of the two metrics in classifying the running condition of rotary seals. Friction torque was found to have a better performance than leakage in terms of differentiating the running condition of rotary seals throughout its service life. Although this approach was designed for seals in oil and gas industry, this approach can be implemented in any manufacturing industry with similar applications.
Experimental Study on the Warpage and Tensile Strength of Additively Manufactured Semi-Crystalline Polyamide 6
Authors: Struebig Konstantin , Schröffer Andreas , Lueth Tim C. 
Published: November 2019

Abstract
Semi-crystalline polymers offer great mechanical properties and are ubiquitously found in everyday life. Despite of this, they are not yet widespread among additive manufacturing processes, due to their high tendency to warp. This leads to unstable build processes and dimensionally inaccurate parts, which greatly reduces their usability. This paper describes the findings of an experimental study designed to identify relevant parameters that affect the warpage and investigate the influence of the manufacturing method on the mechanical properties of semi-crystalline PA6.
The first experiment investigates the effect of water absorption over time, measuring weight and curling of 64 specimens over three weeks. The second part of this study focuses on the changes in geometry caused by the warpage by evaluating a basic model for simple part geometries. At last, a tension test was conducted and the results were compared to injection molded parts of the same material.
The results indicate, that while the absorption of water plays an important role in the warpage of hydrophilic polymers like PA6, other environmental factors also have a significant influence. The model evaluation showed, that the warpage geometry of the tested parts can be approximated with only three parameters for very simple parts, if there are no irregularities in the manufacturing process. The tensile tests revealed, that the additively manufactured specimens reach up to 85.9% of the strength of the injection molded reference parts, most likely due to imperfect filling and reduced density.
Overall, this study provides an insight into the challenges of additively manufacturing semi-crystalline polymers and the potential of PA6 as a tougher alternative to the common materials.
Magnetorheological Nano-Surface-Finishing of Tapered Cavity of Chrome Steel Punch
Authors: Thomas Arpit , Singh Anant Kumar 
Published: November 2019

Abstract
The need for finishing chrome steel punch has drastically increased in order to obtain products with high quality and productivity. Chrome steel finds its application in manufacturing of punch and dies because of its higher hardness as varies up to 62 HRC. The paper is focused on improving the productivity of chrome steel punch through improving the surface finish using magnetorheological finishing process with a solid rotating tool core. The traditional method used for finishing of the chrome steel punch involves diamond lapping where machining marks and surface micro cracks are observed. In punching operation, the punch undergoes adhesive wear which can be controlled if the surface finish of the punch is improved. The surface finish obtained after diamond lapping process is up to 408 nm range. In present work, the further finishing of the tapered cavity of chrome steel punch is carried out. The chrome steel punch workpiece is rotated in a direction opposite to the rotation of the tapered tool tip surface in order to efficiently perform the finishing operation. The final surface roughness value of the flat surface of circular tapered punch is obtained as 26 nm from 420nm while the roughness value of the tapered surface is obtained as 22 nm from 408 nm in 90 minutes of finishing.
Improving Room Temperature-Stretch Formability of Magnesium Alloys by Laser Shock Peening
Authors: Mao Bo , Zhang Xing , Liao Yiliang , Li Bin 
Published: November 2019

Abstract
The applications of magnesium (Mg) and their alloys are often restricted by their poor formability at room temperature. Several strategies have been developed in recent years to enhance the formability of Mg alloys, such as grain refinement and texture weakening, either by alloying or processing. Laser shock peening (LSP) is an advanced laser-based surface processing method which has been utilized improve the surface hardness, fatigue performance, and corrosion resistance of Mg alloys. Recent studies show that LSP can bring significant texture weakening and grain refinement effect in Mg alloy, indicating its potential capability of enhancing the formability of Mg alloys. This research is to explore the applicability of LSP to improve the room temperature-stretch formability of Mg alloys. LSP experiments are carried out on an AZ31B Mg alloys. The microstructure before and after LSP are characterized by optical microscopy (OM) and electron backscattered diffraction (EBSD) microscopy. Erichsen tests are carried out to evaluate the stretch formability of Mg alloys. The results show that LSP can bring texture weakening and grain refinement effect simultaneously, resulting in the improved room temperature-stretch formability of Mg alloys.
Effects Analysis of Internal Buffers in Serial Manufacturing Systems for Optimal Throughput
Authors: Imseitif Jad , Tang Herman 
Published: November 2019

Abstract
Buffers can improve the efficiency of manufacturing systems by accommodating the negative impacts of machine stoppage and maximize the system throughput. Buffers are often designed and integrated into manufacturing systems.
This study investigates the effects of small internal buffers on the throughput of serial manufacturing systems using discrete-event simulation (DES). For a serial manufacturing system, its internal buffer can be designed as an idle station or a small conveyor. In the study, typical automotive assembly lines are used as serial manufacturing systems. In addition, the capacity of a small internal buffer and two small buffers are studied for optimal throughput. The study results provide a general approach on where to assign small internal buffers in serial manufacturing systems and what the effects of such buffers and their configurations are.
Phase Diagram of Pinch-Off Behaviors During Drop-on-Demand Inkjetting of Alginate Solutions
Authors: Xu Changxue , Zhang Zhengyi , Huang Yong , Xu Heqi 
Published: November 2019

Abstract
Viscoelastic polymer solutions have been extensively utilized in drop-wise manufacturing (such as inkjet printing) for a variety of biomedical applications. The pinch-off of viscoelastic jets is a key step towards generation of droplets in inkjet printing. This complex process is governed by interplay of four stresses including inertial stress, capillary stress, viscous stress, and elastic stress. Depending on polymer solution properties and process conditions, four types of pinch-off phenomenon were observed during inkjetting of viscoelastic alginate solutions. In this study, material properties of alginate solutions with different concentrations have been characterized, and three dimensionless numbers (Ohnesorge number Oh, Deborah number De and Weber number We) have been proposed to analyze different pinch-off behaviors. Phase diagram in terms of these three dimensionless numbers has been constructed to classify the regimes for different pinch-off types during inkjetting of viscoelastic alginate solutions. It is found that: 1) At low De and Oh, the viscoelastic effect is small. The capillary stress is mainly balanced by the inertial stress, resulting in front pinching. 2) At medium De and low Oh, the capillary stress is still mainly balanced by the inertial stress, but the elastic effect starts to show its effect by delaying the ligament thinning near the front-pinching location. With the increase of We, the pinch-off type may change from front pinching to hybrid pinching to exit pinching. 3) At low Oh and high De, the viscous and inertial effects are small. The capillary stress is mainly balanced by the elastic stress, resulting in exit pinching. 4) At high Oh and De, the viscoelastic effect is dominant. The capillary stress is mainly balanced by the viscous and elastic stresses. With the increase of We, middle pinching turns to be exit pinching due to the increase of the initial ligament diameter near the forming droplet.
Where Do We Start? Guidance for Technology Implementation in Maintenance Management for Manufacturing
Authors: Brundage Michael P. , Sexton Thurston , Hodkiewicz Melinda , Morris KC , Arinez Jorge , Ameri Farhad , Ni Jun , Xiao Guoxian 
Published: November 2019

Abstract
Recent efforts in Smart Manufacturing (SM) have proven quite effective at elucidating system behavior using sensing systems, communications and computational platforms, along with statistical methods to collect and analyze real-time performance data. However, how do you effectively select where and when to implement these technology solutions within manufacturing operations? Furthermore, how do you account for the human-driven activities in manufacturing when inserting new technologies? Due to a reliance on human problem solving skills, today’s maintenance operations are largely manual processes without wide-spread automation. The current state-of-the-art maintenance management systems and out-of-the-box solutions do not directly provide necessary synergy between human and technology, and many paradigms ultimately keep the human and digital knowledge systems separate. Decision makers are using one or the other on a case-by-case basis, causing both human and machine to cannibalize each other’s function, leaving both disadvantaged despite ultimately having common goals.
A new paradigm can be achieved through a hybridized systems approach — where human intelligence is effectively augmented with sensing technology and decision support tools, including analytics, diagnostics, or prognostic tools. While these tools promise more efficient, cost-effective maintenance decisions, and improved system productivity, their use is hindered when it is unclear what core organizational or cultural problems they are being implemented to solve. To explicitly frame our discussion about implementation of new technologies in maintenance management around these problems, we adopt well established error mitigation frameworks from human factors experts — who have promoted human-systems integration for decades — to maintenance in manufacturing. Our resulting tiered mitigation strategy guides where and how to insert SM technologies into a human-dominated maintenance management process.
Binder Jetting Additive Manufacturing of Ceramics: Analytical and Numerical Models for Powder Spreading Process
Authors: Miao Guanxiong , Du Wenchao , Pei Zhijian , Ma Chao 
Published: November 2019

Abstract
Binder jetting additive manufacturing is a promising way to process ceramic materials which are hard to be manufactured into complex shapes using conventional methods. However, the application of binder jetting is limited by the relatively low density of manufactured parts. Powder bed forming process is a critical step that determines the powder bed density and consequently the part density. Thus, investigating and understanding the power spreading process is necessary to improve the part density. A numerical model is developed to predict the powder bed density under different spreading conditions using the discrete element method (DEM). The predicted DEM results are compared with the prediction of an analytical model. The results show that under different layer thicknesses (50 μm, 70 μm, 100 μm) and roller diameters (12 mm, 14 mm, and 16 mm), the predicted maximum powder bed density by these two models has nearly the same value and the predicted maximum packing stress has the same trend.
Performance Metrics for Product Flow Configuration in a Reconfigurable Manufacturing System (RMS)
Authors: Singh Prince Pal , Madan Jatinder , Singh Harwinder 
Published: November 2019

Abstract
We propose a systematic approach for product flow configuration selection for reconfigurable manufacturing system (RMS) that considers ten industrially relevant most important factors. The paper first defines performance metrics for the identified factors. A composite performance metric (CPM) has been proposed, which accounts for all ten-performance metrics to assess the performance of RMS with the help of a combined score. The methodology of developing CPM applies analytical hierarchy process (AHP) approach where weightage to each of the performance metric is also considered. To showcase the usefulness and feasibility of the CPM, it has been applied in an industrial environment with the help of an industrial case study. Both the CPM and other metric scores were found to be quite useful to identify a suitable configuration out of the available alternatives.
Mechanical Finishing of 3D Printed Continuous Carbon Fiber Reinforced Polymer Composites via CNC Machining
Authors: Parandoush Pedram , Deines Timothy , Lin Dong , Zhang Hao , Ye Chang 
Published: November 2019

Abstract
3D printing technology could be extremely beneficial for increasing the flexibly and reducing the cost of carbon fiber reinforced polymer composite (CFRP) production. However, this technology suffers from poor surface quality and uncertain engineering quality. Mechanical finishing processes could concurrently solve these surface issues with the 3D printed composites components. Herein, a mechanical finishing process for 3D printed CFRP composites via CNC milling is proposed to improve the surface quality of two 3D printing methods, namely fused deposition modeling (FDM) and laser assisted-laminated object manufacturing (LA-LOM). The 3D printed CFRP structures fabricated via both methods comprise of continuous carbon fiber reinforcement. The surface roughness and surface morphology of the original unfinished and finished surfaces with various cutting depths are extensively studied to investigate the feasibility of the proposed finishing technique. The surface morphology of the surfaces parallel and perpendicular to the 3D printed layers is the main focus of this work. After the CNC finishing process, the surface roughness of the 3D printed CFRP composites is improved by 70% and 60% for FDM and LA-LOM components, respectively. A smooth, consistent, and predictable surface morphology is achieved for various cutting depths demonstrating a substantial improvement over the original 3D printed surfaces.
Study on Formation and Performance of Electric-Aided Self-Piercing Riveted Aluminum Alloy and Dual-Phase Steels With Different Strength Grades
Authors: Lou Ming , Ma Yunwu , Li Yongbing 
Published: November 2019

Abstract
To improve the joint quality by reducing the deformation resistance of dual-phase (DP) steels, electric-aided self-piercing riveting (EA-SPR) was conducted in this paper. The effect of current density on the joint forming process, geometry characteristics and mechanical properties of EA-SPR for both combinations of aluminum to steel and steel to aluminum were investigated and compared with the traditional SPR joints. It was found that the riveting force decreased for all the DP steels with different strength grades. The increase amplitude of undercut increased with the elevated strength grades of DP steels. When riveting from aluminum to steel, the tensile-shear and cross-tension strengths of EA-SPR joints could improve up to 13.3% and 15.7% respectively, compared with the traditional SPR joints. For joints riveted from steel to aluminum, the current showed less effect on the tensile-shear strength due to the rivet shank fracture. Nevertheless, the cross-tension strength could still improve by 13.04%.
Laser Deposition-Additive Manufacturing of Graphene Oxide Reinforced IN718 Alloys: Effects on Surface Quality, Microstructure, and Mechanical Properties
Authors: Hu Yingbin , Wang Hui , Cong Weilong 
Published: November 2019

Abstract
Owing to its high stiffness and strength, low density, and excellent flexibility, nano-sized graphene oxide (GO) is considered as a competitive material to reinforce metallic materials. Conventional manufacturing methods for GO reinforced metal matrix fabrication include casting and powder metallurgy, both of which demonstrate disadvantages of high reinforcement agglomeration, high cost, and difficulty in fabrication of complex structures. To reduce these problems, it is important to investigate a finely-controlled, cost-saving, and near-net-shaping process for GO reinforced metal matrix manufacturing. Laser additive manufacturing is such a process that mainly includes selective laser sintering / melting (SLS / M) and laser deposition-additive manufacturing (LD-AM). Compared with SLS / M, LD-AM demonstrates parts remanufacturing capability and is capable of fabricating functionally gradient materials. In this investigation, GO reinforced Inconel 718 (IN718) parts, for the first time, are fabricated using LD-AM processes. The effects of GO on flatness, surface roughness, microstructure, microhardness, and wear resistance of LD-AM fabricated GO reinforced IN718 parts are studied. Experimental results show that the introduction of GO is beneficial for enhancing both microhardness and wear resistance but harmful to surface quality of fabricated parts. In addition, the presence of GO has little influence on microstructures.