Procedia manufacturing最新文献

{"title":"In-situ monitoring of Direct Energy Deposition via Structured Light System and its application in remanufacturing industry","authors":"Xiao Zhang ,&nbsp;Weijun Shen ,&nbsp;Vignesh Suresh ,&nbsp;Jakob Hamilton ,&nbsp;Li-Hsin Yeh ,&nbsp;Xuepeng Jiang ,&nbsp;Zhan Zhang ,&nbsp;Qing Li ,&nbsp;Beiwen Li ,&nbsp;Iris V. Rivero ,&nbsp;Hantang Qin","doi":"10.1016/j.promfg.2021.06.011","DOIUrl":"https://doi.org/10.1016/j.promfg.2021.06.011","url":null,"abstract":"<div><p>The Direct Energy Deposition (DED) process utilizes laser energy to melt metal powders and deposit them on the substrate layer to manufacture complex metal parts. This study was applied as a remanufacturing and repair process to fix used parts, which reduced unnecessary waste in the manufacturing industry. However, there could be defects generated during the repair, such as porosity or bumpy morphological defects. Traditionally, the operator would use a design of experiment (DOE) or simulation method to understand the printing parameters’ influence on the printed part. There are several influential factors: laser power, scanning speed, powder feeding rate, and standoff distance. Each DED machine has a different setup in practice, which results in some uncertainties for the printing results. For example, the nozzle diameter and laser type could be varied in different DED machines. Thus, it was hypothesized that a repair could be more effective if the printing process could be monitored in real-time. In this study, a structured light system (SLS) was used to capture the printing process’s layerwise information. The SLS system is capable of performing 3D surface scanning with a high-resolution of 10 µm. To determine how much material needs to be deposited, given the initial scanning of the part and allowing the real-time observation of each layer’s information. Once a defect was found <em>in-situ</em>, the DED machine (hybrid machine) would change the tool and remove the flawed layer. After the repair, the non-destructive approach computed tomography (CT) was applied to examine its interior features. In this research, a DED machine using 316L stainless steel was used to perform the repairing process to demonstrate its effectiveness. The lab-built SLS system was used to capture each layer’s information, and CT data was provided for the quality evaluation. The novel manufacturing approach could improve the DED repair quality, reduce the repair time, and promote repair automation. In the future, it has a great potential to be used in the manufacturing industry to repair used parts and avoid the extra cost involved in buying a new part.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.06.011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138427887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Balancing trade-offs in one-stage production with processing time uncertainty","authors":"Wei Li ,&nbsp;Barrie R. Nault ,&nbsp;Jingjing You ,&nbsp;Briscoe Bilderback","doi":"10.1016/j.promfg.2021.06.004","DOIUrl":"10.1016/j.promfg.2021.06.004","url":null,"abstract":"<div><p>Production scheduling faces three challenges, two of which are trade-offs and the third is processing time uncertainty. The two sources of trade-offs are between inconsistent key performance indicators (KPIs), and between the expected return and the risk of KPI portfolios. Given the KPIs of total completion time (<em>TCT</em>) and variance of completion times (<em>VCT</em>) are inconsistent for one-stage production, we propose our trade-off balancing (ToB) heuristics. Based on comprehensive case studies, we show that our ToB heuristics efficiently and effectively balance the trade-offs from these two sources. Daniels and Kouvelis (DK) proposed a scheduling scheme to optimize the worst-case scenarios against processing time uncertainty, and they designed the endpoint product (EP) and endpoint sum (ES) heuristics for robust scheduling accordingly. Using 5 levels of coefficients of variation (<em>CV</em>s) to represent processing time uncertainty, we show that our ToB heuristics are robust as well, and even better than the EP and ES heuristics at high levels of processing time uncertainty. In addition, our ToB heuristics generate undominated solution spaces of KPIs, which provides a solid base in deciding control and specification limits for stochastic process control (SPC). Moreover, based on the normalized deviations from optima, our trade-off balancing scheme can be generalized to balance any inconsistent KPIs.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.06.004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54982997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Manufacturing Plant Layout Improvement: Case study of a High-Temperature Heat Treatment Tooling Manufacturer in Northeast Indiana","authors":"Behin Elahi","doi":"10.1016/j.promfg.2021.06.006","DOIUrl":"10.1016/j.promfg.2021.06.006","url":null,"abstract":"<div><p>As the number of competitors in the global marketplace is increasing very fast, it is essential for companies to reduce their lead-time to be sustainable game players. The objectives of this research are to a) improve the layout of a job shop production plant and b) enhance the flow of material from one station to another station to reduce lead times and enhance energy management. This paper focuses on a high-temperature heat treatment tooling manufacturer located in Northeast Indiana, USA. It found that the facility layout at the company was not optimal and over the past several decades, machines and equipment have been purchased and placed wherever there was room to place them. There was a significant amount of materials that are being back-tracked and moved by personnel, ultimately taking longer to produce the parts. The overall aspect of this research was to come up with an efficient robust system to improve the material flow throughout the manufacturing process and to ultimately reduce lead times to improve customers’ satisfaction and enhance energy management. For this purpose, the collective system design methodology integrated with systematic layout planning technique is applied to recognize systems’ needs and find possible scenarios based on activity relationships analysis, adjacency of operations, and total closeness ratings. Through the relationship activity diagram, the importance of adjacency among operations was assessed. Analysis on minimizing the travel distance and material handling along with conducted energy assessments verified that there are significant reductions in feet travelled per day and substantial increases in energy savings. Implementing such a layout improvement project resulted in a 16.66 % up to 33% reduction in lead-time of products (heat treating baskets), significant decreases in weekly overtime hours, and considerable enhancements in energy usage.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.06.006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54983024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of aluminum flow during friction element welding","authors":"Tyler J. Grimm ,&nbsp;Ankit Varma ,&nbsp;Amit B. Deshpande ,&nbsp;Laine Mears ,&nbsp;Xin Zhao","doi":"10.1016/j.promfg.2021.06.016","DOIUrl":"10.1016/j.promfg.2021.06.016","url":null,"abstract":"<div><p>Multimaterial use in automotive body structures has become essential for continuing vehicle mass reduction. This has created challenges in joining of these materials. Friction element welding (FEW) is a joining process capable of joining aluminum to high strength steels. In this process, the element is driven through the aluminum sheet and friction welded to the steel, securing the aluminum under the head of the fastener.</p><p>The flow of aluminum during the FEW process is a critical parameter. Poor aluminum flow conditions can result in the protrusions of aluminum chips from the underhead of the fastener. These chips can accelerate corrosion and generate contamination. The flow of aluminum material was observed experimentally and modeled in order to better understand the FEW process and guide parameter selection. Two aluminum alloys, 6061 and 7075, were selected for this study due to their differences in ductility and strength and for their widespread use in the automotive industry. Various experimental methods were explored for revealing the flow of aluminum during processing and validating simulations. The results of this testing reveal that there is minimal radial and vertical mixing within the aluminum substrate. It was also found that the 6061 material exhibits much greater upwards flow of aluminum, while the 7075 alloy experiences more outward flow.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.06.016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54983400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fabrication of drug-loaded ultrafine polymer fibers via solution blowing and their drug release kinetics","authors":"Karl Schuchard ,&nbsp;Abhay Joijode ,&nbsp;Vincent P. Willard ,&nbsp;Bruce Anderson ,&nbsp;Pierre Grondin ,&nbsp;Behnam Pourdeyhimi ,&nbsp;Rohan Shirwaiker","doi":"10.1016/j.promfg.2021.06.017","DOIUrl":"10.1016/j.promfg.2021.06.017","url":null,"abstract":"<div><p>Biocompatible polymer fibers have garnered significant interest due to their unique properties. Applications range from absorbent media to tissue engineering and drug delivery products. Many manufacturing processes produce such fibers, but a gap exists in highly scalable processes for fibers loaded with thermolabile additives like pharmaceuticals. This study investigates preliminary process-structure-function relationships of solution blown poly(ethylene oxide) fibers loaded with doxycycline, a drug that has demonstrated antibiotic, anti-inflammatory, and anti-tumoral properties. After parameter screening, a factorial experiment mapped the solution blowing design space with a multi-nozzle apparatus. A 1 mm-thick mat was fabricated comprising doxycycline loaded polymer fibers with a mean diameter of 552 ± 200 nm. Study of release kinetics showed the doxycycline released with a significant burst effect over approximately 1 minute. This study highlights solution blowing as a scalable manufacturing platform for fabricating poly(ethylene oxide) fibers loaded with this impactful drug.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.06.017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54983417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental investigation into tool wear, cutting forces, and resulting surface finish during dry and flood coolant slot milling of Inconel 718","authors":"M. Gueli ,&nbsp;J. Ma ,&nbsp;N. Cococcetta ,&nbsp;D. Pearl ,&nbsp;M.P. Jahan","doi":"10.1016/j.promfg.2021.06.026","DOIUrl":"10.1016/j.promfg.2021.06.026","url":null,"abstract":"<div><p>Inconel 718 superalloy is a widely used material in aerospace due to its high strength, corrosion resistance, and high resistance to thermal fatigue. Excellent mechanical and thermal properties also make Inconel 718 one of the most difficult-to-machine alloys. This study aims to take a different approach of analyzing tool wear during machining of Inconel 718 by measuring worn-out area on each flute from three different faces of flute. This paper also includes analysis of cumulative tool wear, cutting forces, surface roughness, topography, burr formation, and chip morphology at various machining parameters and cooling conditions. The cutting speed was kept constant at 60 m/min due to the goal of machining at highest possible speed and the limitation in maximum spindle speed of the machine tool. Experiments were carried out in dry and flood coolant machining using uncoated carbide tools by varying depth of cut and feed rate for four different settings each. It was found that the amount of tool wear varied for different flutes when measured from top, rake, and back faces of each flute, even for the same tool. The back and rake faces exhibit more chipping wear when machining is carried out at higher depth of cut, irrespective of the cooling conditions. At the same machining conditions for the range of parameters selected in this study, flood coolant machining resulted in slightly higher tool wear at the back and rake faces of cutting flutes and generated higher cutting speed, which may be interrelated. The gradual increase in tool wear over time resulted in an increase in surface roughness from entry to exit of a 76.2 mm machined slot. Flood coolant machining resulted in slightly smoother surface finish at the lower settings of depth of cut and feed rate, while the burr formation was marginally higher in flood coolant machining during machining at higher feed rate and depth of cut. The amount of serration was found to increase specifically with the increase of feed rate and was found to be higher for dry machining compared to flood coolant machining at the same parameter settings. Finally, the new approach of tool wear analysis from different faces of individual cutting flute could provide important guidelines for predicting tool life or potential catastrophic tool failure during machining of Inconel 718.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.06.026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54983536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sharpening of the diamond tool edge by the Ar ion beam machine tool","authors":"Takenori ONO","doi":"10.1016/j.promfg.2021.06.027","DOIUrl":"10.1016/j.promfg.2021.06.027","url":null,"abstract":"<div><p>Sharpening of the edge on the single crystal diamond cutting tool by Ar ion beam machine tool is discussed. The cutting edge of the diamond tool can be sharpened by the ion plasma because an etching rate is changed by changing the beam irradiation angle on the machining surface. Machining experiments were carried out to observe the effect of the beam irradiation direction on etching characteristics. In these experiments, a single point flat tool is fabricated to the micro scale structure by Focused Ion Beam (FIB) machine tool on its cutting edge to make the edge roundness artificially. Then, the argon ion beam produced by the penning ion sources irradiated on the rounded edge in various direction. In machining tests, it was observed that the shape of edge was not only sharpened, but also made to be the flat as the new rake face on its rounded face by specific inclination of the beam irradiation. Based on this result, the machining was performed by changing the beam irradiation direction additionally. As the result, it is observed that the new flat face is fabricated according to the intended direction.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.06.027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54983551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Artificial Intelligence in Incremental Sheet Metal Forming: A Review","authors":"Asmaa Harfoush ,&nbsp;Karl R. Haapala ,&nbsp;Ali Tabei","doi":"10.1016/j.promfg.2021.06.061","DOIUrl":"10.1016/j.promfg.2021.06.061","url":null,"abstract":"<div><p>Artificial Intelligence (AI) has been widely used in manufacturing, healthcare, sports, finance, and other areas to model nonlinearities and make reliable predictions. In manufacturing, AI has been applied to improve processes, reduce costs, and increase reliability. A novel manufacturing process that has been augmented with AI is Incremental Sheet Forming (ISF), a technology that applies a step-by-step incremental feed to a sheet metal or polymer blank using a CNC machine. The quality of the produced part is affected by parameters related to four process elements: the blank, the blank holder, the forming tool, and the CNC machine (applied force). The ISF process is greatly affected by forming process parameters, material property parameters, and geometric parameters. Numerous research efforts have correlated the relationship between the ISF parameters to final product attributes using analytical, experimental, and numerical techniques. However, these techniques are not efficient due to the nonlinearities and complexities of the relationships, the time-consuming nature of the process, and extensive computational time needed to simulate the process. To compensate for these shortcomings, researchers have started to apply AI techniques in analysis of ISF. The aim of this paper is to review the application of AI in the ISF process in forming of metal sheets in order to summarize the contributions of prior research efforts and identify potential opportunities for future research.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.06.061","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54984152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Random forest regression for predicting an anomalous condition on a UR10 cobot end-effector from purposeful failure data","authors":"Ethan Wescoat,&nbsp;Matthew Krugh,&nbsp;Laine Mears","doi":"10.1016/j.promfg.2021.06.064","DOIUrl":"10.1016/j.promfg.2021.06.064","url":null,"abstract":"<div><p>Unexpected downtime from equipment failure has increased due to a production line’s mechanization to meet production throughput requirements. Manufacturing equipment requires accurate prediction models for determining future failure probability in maintenance scheduling. This paper explores using generated failure data under contrived failure scenarios in training a model for a robot with different combinations of data features. Failure data are generated by inducing an anomalous state in the robot arm. The anomalous state is created by attaching weights at the robot end-effector. A random forest regression model diagnoses the anomalous state and determines the anomalous state progression after gathering data. Three different regression models were trained to test accuracy based on different feature selections. The random forest regression predicted 92% of the robot joint operations through five-fold cross-validation, an anomaly in a robot joint 99% of the time, and the correct anomaly state-based on the confusion matrix, 85% of the time. In future research, the anomalous state will represent more targeted component failures on the system through purposeful permanent damage of the robots’ components. Future datasets generated will train other machine health algorithms for estimating component and system damage.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.06.064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54984193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterisation of drilling-induced damage in GFRP Honeycomb Sandwich Composites using Acoustic Emission","authors":"Rishikesan V ,&nbsp;Bhagyesh Chaturvedi ,&nbsp;Arunachalam N","doi":"10.1016/j.promfg.2021.06.066","DOIUrl":"10.1016/j.promfg.2021.06.066","url":null,"abstract":"<div><p>Glass Fiber-reinforced plastic (GFRP) sandwich composites are extensively used in various engineering applications owing to their advantageous structural properties such as high specific strength to weight ratio, resistance to shear and compressive forces as well as their cost-effectiveness and manufacturing ease. Machining these composites however is a difficult task. The durability of the material deteriorates due to machining induced meso-damage that accumulate over time, creating the motivation to study what the damage mechanisms depend on. Many Non-Destructive Testing (NDT) techniques are often used to characterize such damages. Acoustic Emissions (AE) has emerged as an important non-destructive method for real-time examination of damage evolution. This study aims to investigate the effects of various acoustic emission features along with force, torque and tool wear on the delamination caused on the GFRP sandwich honeycomb composite during the drilling process. Experiments were conducted and delamination for each hole was measured. Consequently, data-driven models were used to characterize damage in the material.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.06.066","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54984216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}