Tool condition monitoring of machine is the prognostic maintenance process of machinery which deals with the determination of a condition of machinery and its change with respect to time. The overall trend in various industries is to reduce the human resources by various automated types of machinery so as to have betterment in the accuracy of the system by reducing the human errors. A condition of the machine tool may be determined by measuring various physical parameters like vibration, temperature, wear, surface roughness, acoustic emissions etc. This paper presents a review of tool condition monitoring systems (TCMS) with an application of vibration signals in the hard turning machining process. The analysis using vibration signals will help in predicting and preventing the failure of the tool which will avoid the downtime of a production system and will also increase the safety of operation.
{"title":"Tool Condition Monitoring Using Vibration Signals During Hard Turning: A Review","authors":"Govind S. Ghule, N. Ambhore, S. Chinchanikar","doi":"10.2139/ssrn.3101977","DOIUrl":"https://doi.org/10.2139/ssrn.3101977","url":null,"abstract":"Tool condition monitoring of machine is the prognostic maintenance process of machinery which deals with the determination of a condition of machinery and its change with respect to time. The overall trend in various industries is to reduce the human resources by various automated types of machinery so as to have betterment in the accuracy of the system by reducing the human errors. A condition of the machine tool may be determined by measuring various physical parameters like vibration, temperature, wear, surface roughness, acoustic emissions etc. This paper presents a review of tool condition monitoring systems (TCMS) with an application of vibration signals in the hard turning machining process. The analysis using vibration signals will help in predicting and preventing the failure of the tool which will avoid the downtime of a production system and will also increase the safety of operation.","PeriodicalId":202570,"journal":{"name":"ATSMDE 2017: Materials Engineering","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124150140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thin film-based second and third generation photovoltaics (PVs) are avidly investigated for their potential for utility scale applications. Organic thin film (PEDOT) and silicon-based PVs are shown to have moderate device efficiency. To further improve efficiency, silicon is sandwiched between thin films of PEDOT and TiO2. Thin films of TiO2 synthesized at 100°C have been shown to make efficient (~12%) PEDOT/Si/TiO2-based PVs; TiO2 functions as a holeblocker. Lower efficiencies of the PVs than predicted by theory is attributed to poor passivation of the Si/TiO2 interface. To improve the interface passivation, the Si/TiO2 interface is treated under various chemical conditions. One such treatment yielded very high level of passivation (SRV ~ 15 cm/s).
{"title":"Low Temperature Solution-Based Treatment for Highly Passivated Si/TiO2 Heterojunction","authors":"G. Sahasrabudhe","doi":"10.2139/ssrn.3101591","DOIUrl":"https://doi.org/10.2139/ssrn.3101591","url":null,"abstract":"Thin film-based second and third generation photovoltaics (PVs) are avidly investigated for their potential for utility scale applications. Organic thin film (PEDOT) and silicon-based PVs are shown to have moderate device efficiency. To further improve efficiency, silicon is sandwiched between thin films of PEDOT and TiO<sub>2</sub>. Thin films of TiO<sub>2</sub> synthesized at 100°C have been shown to make efficient (~12%) PEDOT/Si/TiO<sub>2</sub>-based PVs; TiO<sub>2</sub> functions as a holeblocker. Lower efficiencies of the PVs than predicted by theory is attributed to poor passivation of the Si/TiO<sub>2</sub> interface. To improve the interface passivation, the Si/TiO<sub>2</sub> interface is treated under various chemical conditions. One such treatment yielded very high level of passivation (SRV ~ 15 cm/s).","PeriodicalId":202570,"journal":{"name":"ATSMDE 2017: Materials Engineering","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115091410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper focuses on the investigation of the effect of process parameters on the responses such as material removal rate and surface roughness of Ti49.4Ni50.6 shape memory alloy machined by WEDM using Taguchi technique to obtain optimum machining process parameters. Whenever conventional machining process gets drossy, it becomes inevitable to use nonconventional machining processes like Wire-Electro Discharge Machining (WEDM). Considering the development of mechanical industry, the demands for alloy materials having high hardness and toughness are increasing. Machine tool industry has also made exponential growth in its manufacturing capabilities but still, machine tools are not used to their fullest potential. This limitation is a result of the failure to run machine tools at their optimum operating conditions. A number of experiments were conducted using the L18 orthogonal array on Electronica WEDM. A combined technique using orthogonal array and analysis of variance was used to investigate the contribution and effects of a pulse on time, pulse off time, spark gape set voltage, wire feed and wire tension on the MRR and surface roughness. It is observed that pulse on time is the most significant parameter for MRR and surface roughness with a percentage contribution of 35.69% and 59.02% respectively. Along with this pulse off time was observed to be the next significant parameter for MRR with percentage contribution of 34.47%. Thereafter, optimal machining parameters were obtained by analysis of mean.
{"title":"Analysis and Optimization of Wire Electro Discharge Machining Parameters of TiNi Shape Memory Alloy Using Taguchi Technique","authors":"A. Takale, N. Chougule, R. Patil, A. S. Awate","doi":"10.2139/ssrn.3101586","DOIUrl":"https://doi.org/10.2139/ssrn.3101586","url":null,"abstract":"This paper focuses on the investigation of the effect of process parameters on the responses such as material removal rate and surface roughness of Ti<sub>49.4</sub>Ni<sub>50.6</sub> shape memory alloy machined by WEDM using Taguchi technique to obtain optimum machining process parameters. Whenever conventional machining process gets drossy, it becomes inevitable to use nonconventional machining processes like Wire-Electro Discharge Machining (WEDM). Considering the development of mechanical industry, the demands for alloy materials having high hardness and toughness are increasing. Machine tool industry has also made exponential growth in its manufacturing capabilities but still, machine tools are not used to their fullest potential. This limitation is a result of the failure to run machine tools at their optimum operating conditions. A number of experiments were conducted using the L18 orthogonal array on Electronica WEDM. A combined technique using orthogonal array and analysis of variance was used to investigate the contribution and effects of a pulse on time, pulse off time, spark gape set voltage, wire feed and wire tension on the MRR and surface roughness. It is observed that pulse on time is the most significant parameter for MRR and surface roughness with a percentage contribution of 35.69% and 59.02% respectively. Along with this pulse off time was observed to be the next significant parameter for MRR with percentage contribution of 34.47%. Thereafter, optimal machining parameters were obtained by analysis of mean.","PeriodicalId":202570,"journal":{"name":"ATSMDE 2017: Materials Engineering","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133390106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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