The International Conference on Applied Mechanics and Mechanical Engineering, 2016
This paper presents the development and experimental validation of a modeling approach that was p... more This paper presents the development and experimental validation of a modeling approach that was proposed to predict the surface generation process during ultraprecision turning. In particular, in addition to the kinematic paramters, the proposed model takes into consideration the effects of the minimum chip thickness and elastic recovery along side their associated uncertainity attributable to the blend nature of the multi-phase materials. The model amis to eliminate the contribution of the uncertainty errors due to the stochastic behavior of the phases presents within the material microstructe. Thus, it allows predicting the achievable surface roughness more preciously under different cutting conditions. The developed model was experimentally validated by machining dual-phase material, Brass 6040, under a range of processing parameters. The roughness of the generated surface was measured and compared with those estimated by the model under similar conditions. Prelimenrary implementation of the model indicated that the model predictions relatively agreed with the experimental results. After conducting a calibration procedure, lower error was obtained 20.45%. However, by excluding the results at very low feed rates to duduct its erratic influence, the average error substantially reduced to 11.18% using cutting tools with nose radius of 200 µm.
Fused deposition modelling (FDM), one of the most commonly used additive manufacturing techniques... more Fused deposition modelling (FDM), one of the most commonly used additive manufacturing techniques in the industry, involves layer-by-layer deposition of melted material to create a 3D structure. The staircase and beading effect caused by the printing process and temperature variation cause delamination and poor surface finish in FDM-printed parts. This hinders the use of these specimens in various applications, which are then usually resolved using pre-processing and post-processing techniques. Higher surface finish in pre-processing is achieved by increasing the resolution, changing layer thickness and optimizing build orientation. However, this increases the processing time considerably. On the other hand, post-processing techniques involve different processes such as mechanical, chemical, thermal and hybrid methods but can affect the mechanical and structural properties of the printed components. This review paper analyses three different aspects in the area of improving the surf...
Its unexcelled mechanical and physical properties, in addition to its biocompatibility, have made... more Its unexcelled mechanical and physical properties, in addition to its biocompatibility, have made stainless steel 304 a prime candidate for a wide range of applications. Among different manufacturing techniques, electrical discharge machining (EDM) has shown high potential in processing stainless steel 304 in a controllable manner. This paper reports the results of an experimental investigation into the effect of the process parameters on the obtainable surface roughness and material removal rate of stainless steel 304, when slotted using wire EDM. A full factorial design of the experiment was followed when conducting experimental trials in which the effects of the different levels of the five process parameters; applied voltage, traverse feed, pulse-on time, pulse-off time, and current intensity were investigated. The geometry of the cut slots was characterized using the MATLAB image processing toolbox to detect the edge and precise width of the cut slot along its entire length to ...
In machining operations, minimizing the usage of resources such as energy, tools, costs, and prod... more In machining operations, minimizing the usage of resources such as energy, tools, costs, and production time, while maximizing process outputs such as surface quality and productivity, has a significant impact on the environment, process sustainability, and profit. In this context, this paper reports on the utilization of advanced multi-objective algorithms for the optimization of turning-process parameters, mainly cutting speed, feed rate, and depth of cut, in the dry machining of AISI 1045 steel for high-efficient process. Firstly, a number of experimental tests were conducted in which cutting forces and cutting temperatures are measured. Then the material removal rate and the obtainable surface roughness were determined for the examined range of cutting parameters. Next, regression models were developed to formulate the relationships between the process parameters and the four process responses. After that, four different multi-objective optimization algorithms, (1) Gray Wolf Opt...
Material Microstructure Effect-Based Simulation Model for the Surface Generation Process in Micro-milling
This paper presents a proposed model to simulate the surface generation process during micro-mill... more This paper presents a proposed model to simulate the surface generation process during micro-milling of multi-phase materials. The proposed model considers the effects of the following factors: the geometry of the cutting tool, the cutting parameters, and the workpiece material microstructure in terms of the variations of the minimum chip thickness for each phase within the material microstructure. In particular, the model can take into account the drastic changes of the minimum chip thickness at the phase boundaries that alter the machining conditions from a proper cutting to ploughing and from ploughing to cutting. Such alterations of the cutting mechanisms are considered as the main cause of micro-burr formation. By applying the proposed model when processing multi-phase materials at micro scale, it is possible to estimate more accurately the resulting roughness owing to the dominance of the micro-burrs formation during the surface generation process in micro milling.
Metal parts produced by additive manufacturing often require postprocessing to meet the specifica... more Metal parts produced by additive manufacturing often require postprocessing to meet the specifications of the final product, which can make the process chain long and complex. Laser post-processes can be a valuable addition to conventional finishing methods. Laser polishing, specifically, is proving to be a great asset in improving the surface quality of parts in a relatively short time. For process development, experimental analysis can be extensive and expensive regarding the time requirement and laboratory facilities, while computational simulations demand the development of numerical models that, once validated, provide valuable tools for parameter optimization. In this work, experiments and simulations are performed based on the design of experiments to assess the effects of the parametric inputs on the resulting surface roughness and heat-affected zone depths. The data obtained are used to create both linear regression and artificial neural network models for each variable. Th...
Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2016
This article presents an investigation of the machining response of metallurgically and mechanica... more This article presents an investigation of the machining response of metallurgically and mechanically modified materials at the micro-scale. Tests were conducted that involved micro-milling slots in coarse-grained Cu99.9E with an average grain size of 30 µm and ultrafine-grained Cu99.9E with an average grain size of 200 nm, produced by equal channel angular pressing. A new method based on atomic force microscope measurements is proposed for assessing the effects of material homogeneity changes on the minimum chip thickness required for a robust micro-cutting process with a minimum surface roughness. The investigation has shown that by refining the material microstructure the minimum chip thickness can be reduced and a high surface finish can be obtained. Also, it was concluded that material homogeneity improvements lead to a reduction in surface roughness and surface defects in micro-cutting.
The aim of this project is to demonstrate a proof of concept by using Additive Manufacturing (AM)... more The aim of this project is to demonstrate a proof of concept by using Additive Manufacturing (AM) technology in order to demonstrate its viability for the production of tailor-made components with regions of varying (higher and lower) hardness and surface roughness within a single part. In order to do this, first a test piece is designed and printed following a full factorial design of the experiment with eight runs with varying process parameters set within different regions of one part. The structure is printed several times with the laser-powder-bed-fusion-based metal-additive-manufacturing system “Sodick LPM 325” using AISI 420 in order to test and validate the change in the achievable mechanical property and surface roughness. The above-mentioned quality marks are characterized using a tactile profilometer, Rockwell test and part density, and the results are statistically analyzed using MATLAB. The results show that the linear energy density plays a significant role in controll...
This article reports an extended investigation into the precision hard turning of AISI 4340 alloy... more This article reports an extended investigation into the precision hard turning of AISI 4340 alloy steel when machined by two different types of inserts: wiper nose and conventional round nose. It provides a closer look at previously published work and aims at determining the optimal process parameters for simultaneously minimizing surface roughness and maximizing productivity. In the mathematical models developed by the authors, surface roughness at different cutting speeds, depths of cut and feed rates is treated as the objective function. Three robust multi-objective techniques, (1) multi-objective genetic algorithm (MOGA), (2) multi-objective Pareto search algorithm (MOPSA) and (3) multi-objective emperor penguin colony algorithm (MOEPCA), were used to determine the optimal turning parameters when either the wiper or the conventional insert is used, and the results were experimentally validated. To investigate the practicality of the optimization algorithms, two turning scenarios...
This paper presents an experimental study into the comparative response of wiper and round-nose c... more This paper presents an experimental study into the comparative response of wiper and round-nose conventional carbide inserts coated with TiCN + AL2O3 + TiN when turning an AISI 4340 steel alloy. The optimal process parameters, as identified by pre-experiments, were used for both types of inserts to determine the machined surface quality, tool wear, and specific cutting energy for different cutting lengths. The wiper inserts provided a substantial improvement in the attainable surface quality compared with the results obtained using conventional inserts under optimal cutting conditions for the entire range of the machined lengths. In addition, the conventional inserts showed a dramatic increase in roughness with an increased length of the cut, while the wiper inserts showed only a minor increase for the same length of cut. A scanning electron microscope was used to examine the wear for both types of inserts. Conventional inserts showed higher trends for both the average and maximum f...
This paper reports a fundamental investigation consisting of systematic trials into the response ... more This paper reports a fundamental investigation consisting of systematic trials into the response of Ti6Al4V alloy to high-speed machining using carbide inserts. It is a useful extension to work previously published, and aims at assessing the impact of the process parameters, depth of cut, cutting speed and feed rate in addition to cutting length, and their interrelations, on observed crater and flank wear and roughness of the machined surface. The results showed that abrasion was the most important flank wear mechanism at high speed. It also showed that increased cutting length accelerated crater wear more than exhibited flank wear and had considerable effect on surface roughness. In particular, crater wear increased by over 150% (on average), and flank wear increased by 40% (on average) when increasing cutting length from 40 to 120 mm. However, cutting the same length increased surface roughness by 50%, which helps explain how progression of tool wear leads to deteriorated surface ...
The arrival of Industry 4.0 has popularised the concept of smart interactions between humans and ... more The arrival of Industry 4.0 has popularised the concept of smart interactions between humans and the physical world that could realise the synergistic integration of intelligent manufacturing assets. However, a systematic and cogent approach to the practical and profitable application of Industry 4.0 is still missing. This paper presents practical approaches to the application of Industry 4.0 to manufacture with the aim of strengthening its competitiveness and meeting the growing serious challenges that threaten its profitability and survival. Precision Additive Metal Manufacturing is utilised in this study for demonstration purposes. A conceptual framework combined with two practical modules available in the market, a "native-design" and "Plug and Play", is proposed. These approaches offer flexible prototypes with sequential procedures that ultimately would allow for easy employment of Industry 4.0, and will help remove technical barriers to the development of m...
On the Assessment of Thermo-mechanical Degradability of Multi-recycled ABS Polymer for 3D Printing Applications
Sustainable Design and Manufacturing 2019, 2019
Although additive manufacturing (AM) has offered proven ability to reduce waste when compared wit... more Although additive manufacturing (AM) has offered proven ability to reduce waste when compared with traditional manufacturing techniques, however, AM processes such as fused filament fabrication (FFF) still poses some negative environmental and economic aspects in terms of generated waste. This waste comes from rafts, supports, or bases that are parts of the supporting structure necessary in the construction of proper 3D-printed parts. In addition, another source of waste comes from jobs that failed due to a variety of reasons as is common with 3D printing. One possible way to minimize the negative effect is to recycle this waste material. Through the usage of commercially available cutting mills and extruder equipment that are easily procurable, it is possible to recycle the waste and reuse it as a filament. In this context, this paper aims to experimentally investigate the feasibility of recycling 3D printing waste material, namely of ABS material which is a popular 3D printing material and to evaluate changes in the mechanical behaviour after each recycling cycle, while taking the performance of the virgin material as a reference point. The mechanical behaviour of the recycled materials was assessed as a function of obtainable tensile strength, toughness and thermal transition. The results show that the ABS filament shows great promise for recycling at least once and could lead to significant material and cost savings. In this work, it is possible to observe how many times ABS can be recycled and used as filament, without adding virgin material.
The copyright release is a transfer of publication rights, which allows IARIA and its partners to... more The copyright release is a transfer of publication rights, which allows IARIA and its partners to drive the dissemination of the published material. This allows IARIA to give articles increased visibility via distribution, inclusion in libraries, and arrangements for submission to indexes. I, the undersigned, declare that the article is original, and that I represent the authors of this article in the copyright release matters. If this work has been done as work-for-hire, I have obtained all necessary clearances to execute a copyright release. I hereby irrevocably transfer exclusive copyright for this material to IARIA. I give IARIA permission or reproduce the work in any media format such as, but not limited to, print, digital, or electronic. I give IARIA permission to distribute the materials without restriction to any institutions or individuals. I give IARIA permission to submit the work for inclusion in article repositories as IARIA sees fit. I, the undersigned, declare that to the best of my knowledge, the article is does not contain libelous or otherwise unlawful contents or invading the right of privacy or infringing on a proprietary right.
One of the problems encountered in the design and implementation of a serial production line (SPL... more One of the problems encountered in the design and implementation of a serial production line (SPL) is the buffer size between the machine tools. The buffer size of the SPL has an important impact on the productivity of the whole production system. The machine tools' characteristics including their uptimes and downtimes and the process parameters are the main factors that affect the decision regarding the buffer size, and thus the productivity of the SPL. Due to the dynamic nature of this problem, it is complex to find the optimal buffer size in SPL. Thus, in this paper, an Efficient Prediction Model (EPM) is developed using Artificial Neural Network (ANN). The purpose of the developed EPM is to find the buffer size between each succeeding pair of machine tools in SPL at any given uptimes and downtimes of machine tools. An optimization model based on genetic algorithms (GA) is used to generate the learning data for the prediction model to find the optimal or near optimal buffer size of the bay of each machine tool in SPL. The proposed approach integrates the optimization and prediction methodologies to evaluate, and predict the optimal buffer sizes for maximum productivity. Including uptime and downtime parameters enable the proposed method to be used to improve the design of running SPL as well as to design a new SPL. Numerical examples for five and fifteen machine tools were conducted independently in this research and the results show the ability of the proposed method to determine the optimal buffer sizes in a reasonable amount of time. In particular, the results of case studies show that the developed model accurately predict the optimal buffer size, especially for the case of five machines and even for a higher number of machine tools yet with acceptable but less accuracy. Finally, the performance of the proposed approach was compared with some results of the state of the art methods reported in the literature. The comparison shows the superiority of the present approach to identify buffer sizes for higher throughput under the same uptimes and downtimes. INDEX TERMS Flexible manufacturing system, serial production line, optimization, prediction model, buffer size, productivity. NOTATION Abbreviations Descriptions N Number of buffers in the main production line B i Buffer size in front of the machine tool i+1 F(i) Fitness of individual i The associate editor coordinating the review of this manuscript and approving it for publication was Baoping Cai .
Smart modular reconfigurable fully-digital manufacturing system with a knowledge-based framework: example of a fabrication of microfluidic chips
2018 IEEE 14th International Conference on Automation Science and Engineering (CASE), 2018
This paper presents an innovative approach to the development of a smart fully-digital manufactur... more This paper presents an innovative approach to the development of a smart fully-digital manufacturing system based on a modular and reconfigurable production concept. In particular, multiple “plug and play” manufacturing modules, i.e. functional printing, laser processing and welding, in addition to a positioning control unit and quality inspection system, are exploited in an agile manufacturing platform combined with a knowledge-based framework, termed “3D-I”. This enables the production of tailored laminated parts, made up of stacks of functionalised layers of polymer films, with intricate 3D micro features. However, since no tool or mask making is needed, a medium to small lot-size and even one-off parts can be produced in a cost-effective manner. For the evaluation of the “3D-I” approach, a case study of micro-fluidic chips, exemplifying functional parts, are fabricated. The results prove the feasibility of the developed smart system to produce micro-devices with pre-defined specifications. In addition, the knowledge-based manufacturing system demonstrates its potential to offer profitable production scenarios of microdevices, with high flexibility and scalability, outside the area of mass production.
The International Conference on Applied Mechanics and Mechanical Engineering, 2016
This paper presents the development and experimental validation of a modeling approach that was p... more This paper presents the development and experimental validation of a modeling approach that was proposed to predict the surface generation process during ultraprecision turning. In particular, in addition to the kinematic paramters, the proposed model takes into consideration the effects of the minimum chip thickness and elastic recovery along side their associated uncertainity attributable to the blend nature of the multi-phase materials. The model amis to eliminate the contribution of the uncertainty errors due to the stochastic behavior of the phases presents within the material microstructe. Thus, it allows predicting the achievable surface roughness more preciously under different cutting conditions. The developed model was experimentally validated by machining dual-phase material, Brass 6040, under a range of processing parameters. The roughness of the generated surface was measured and compared with those estimated by the model under similar conditions. Prelimenrary implementation of the model indicated that the model predictions relatively agreed with the experimental results. After conducting a calibration procedure, lower error was obtained 20.45%. However, by excluding the results at very low feed rates to duduct its erratic influence, the average error substantially reduced to 11.18% using cutting tools with nose radius of 200 µm.
Fused deposition modelling (FDM), one of the most commonly used additive manufacturing techniques... more Fused deposition modelling (FDM), one of the most commonly used additive manufacturing techniques in the industry, involves layer-by-layer deposition of melted material to create a 3D structure. The staircase and beading effect caused by the printing process and temperature variation cause delamination and poor surface finish in FDM-printed parts. This hinders the use of these specimens in various applications, which are then usually resolved using pre-processing and post-processing techniques. Higher surface finish in pre-processing is achieved by increasing the resolution, changing layer thickness and optimizing build orientation. However, this increases the processing time considerably. On the other hand, post-processing techniques involve different processes such as mechanical, chemical, thermal and hybrid methods but can affect the mechanical and structural properties of the printed components. This review paper analyses three different aspects in the area of improving the surf...
Its unexcelled mechanical and physical properties, in addition to its biocompatibility, have made... more Its unexcelled mechanical and physical properties, in addition to its biocompatibility, have made stainless steel 304 a prime candidate for a wide range of applications. Among different manufacturing techniques, electrical discharge machining (EDM) has shown high potential in processing stainless steel 304 in a controllable manner. This paper reports the results of an experimental investigation into the effect of the process parameters on the obtainable surface roughness and material removal rate of stainless steel 304, when slotted using wire EDM. A full factorial design of the experiment was followed when conducting experimental trials in which the effects of the different levels of the five process parameters; applied voltage, traverse feed, pulse-on time, pulse-off time, and current intensity were investigated. The geometry of the cut slots was characterized using the MATLAB image processing toolbox to detect the edge and precise width of the cut slot along its entire length to ...
In machining operations, minimizing the usage of resources such as energy, tools, costs, and prod... more In machining operations, minimizing the usage of resources such as energy, tools, costs, and production time, while maximizing process outputs such as surface quality and productivity, has a significant impact on the environment, process sustainability, and profit. In this context, this paper reports on the utilization of advanced multi-objective algorithms for the optimization of turning-process parameters, mainly cutting speed, feed rate, and depth of cut, in the dry machining of AISI 1045 steel for high-efficient process. Firstly, a number of experimental tests were conducted in which cutting forces and cutting temperatures are measured. Then the material removal rate and the obtainable surface roughness were determined for the examined range of cutting parameters. Next, regression models were developed to formulate the relationships between the process parameters and the four process responses. After that, four different multi-objective optimization algorithms, (1) Gray Wolf Opt...
Material Microstructure Effect-Based Simulation Model for the Surface Generation Process in Micro-milling
This paper presents a proposed model to simulate the surface generation process during micro-mill... more This paper presents a proposed model to simulate the surface generation process during micro-milling of multi-phase materials. The proposed model considers the effects of the following factors: the geometry of the cutting tool, the cutting parameters, and the workpiece material microstructure in terms of the variations of the minimum chip thickness for each phase within the material microstructure. In particular, the model can take into account the drastic changes of the minimum chip thickness at the phase boundaries that alter the machining conditions from a proper cutting to ploughing and from ploughing to cutting. Such alterations of the cutting mechanisms are considered as the main cause of micro-burr formation. By applying the proposed model when processing multi-phase materials at micro scale, it is possible to estimate more accurately the resulting roughness owing to the dominance of the micro-burrs formation during the surface generation process in micro milling.
Metal parts produced by additive manufacturing often require postprocessing to meet the specifica... more Metal parts produced by additive manufacturing often require postprocessing to meet the specifications of the final product, which can make the process chain long and complex. Laser post-processes can be a valuable addition to conventional finishing methods. Laser polishing, specifically, is proving to be a great asset in improving the surface quality of parts in a relatively short time. For process development, experimental analysis can be extensive and expensive regarding the time requirement and laboratory facilities, while computational simulations demand the development of numerical models that, once validated, provide valuable tools for parameter optimization. In this work, experiments and simulations are performed based on the design of experiments to assess the effects of the parametric inputs on the resulting surface roughness and heat-affected zone depths. The data obtained are used to create both linear regression and artificial neural network models for each variable. Th...
Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2016
This article presents an investigation of the machining response of metallurgically and mechanica... more This article presents an investigation of the machining response of metallurgically and mechanically modified materials at the micro-scale. Tests were conducted that involved micro-milling slots in coarse-grained Cu99.9E with an average grain size of 30 µm and ultrafine-grained Cu99.9E with an average grain size of 200 nm, produced by equal channel angular pressing. A new method based on atomic force microscope measurements is proposed for assessing the effects of material homogeneity changes on the minimum chip thickness required for a robust micro-cutting process with a minimum surface roughness. The investigation has shown that by refining the material microstructure the minimum chip thickness can be reduced and a high surface finish can be obtained. Also, it was concluded that material homogeneity improvements lead to a reduction in surface roughness and surface defects in micro-cutting.
The aim of this project is to demonstrate a proof of concept by using Additive Manufacturing (AM)... more The aim of this project is to demonstrate a proof of concept by using Additive Manufacturing (AM) technology in order to demonstrate its viability for the production of tailor-made components with regions of varying (higher and lower) hardness and surface roughness within a single part. In order to do this, first a test piece is designed and printed following a full factorial design of the experiment with eight runs with varying process parameters set within different regions of one part. The structure is printed several times with the laser-powder-bed-fusion-based metal-additive-manufacturing system “Sodick LPM 325” using AISI 420 in order to test and validate the change in the achievable mechanical property and surface roughness. The above-mentioned quality marks are characterized using a tactile profilometer, Rockwell test and part density, and the results are statistically analyzed using MATLAB. The results show that the linear energy density plays a significant role in controll...
This article reports an extended investigation into the precision hard turning of AISI 4340 alloy... more This article reports an extended investigation into the precision hard turning of AISI 4340 alloy steel when machined by two different types of inserts: wiper nose and conventional round nose. It provides a closer look at previously published work and aims at determining the optimal process parameters for simultaneously minimizing surface roughness and maximizing productivity. In the mathematical models developed by the authors, surface roughness at different cutting speeds, depths of cut and feed rates is treated as the objective function. Three robust multi-objective techniques, (1) multi-objective genetic algorithm (MOGA), (2) multi-objective Pareto search algorithm (MOPSA) and (3) multi-objective emperor penguin colony algorithm (MOEPCA), were used to determine the optimal turning parameters when either the wiper or the conventional insert is used, and the results were experimentally validated. To investigate the practicality of the optimization algorithms, two turning scenarios...
This paper presents an experimental study into the comparative response of wiper and round-nose c... more This paper presents an experimental study into the comparative response of wiper and round-nose conventional carbide inserts coated with TiCN + AL2O3 + TiN when turning an AISI 4340 steel alloy. The optimal process parameters, as identified by pre-experiments, were used for both types of inserts to determine the machined surface quality, tool wear, and specific cutting energy for different cutting lengths. The wiper inserts provided a substantial improvement in the attainable surface quality compared with the results obtained using conventional inserts under optimal cutting conditions for the entire range of the machined lengths. In addition, the conventional inserts showed a dramatic increase in roughness with an increased length of the cut, while the wiper inserts showed only a minor increase for the same length of cut. A scanning electron microscope was used to examine the wear for both types of inserts. Conventional inserts showed higher trends for both the average and maximum f...
This paper reports a fundamental investigation consisting of systematic trials into the response ... more This paper reports a fundamental investigation consisting of systematic trials into the response of Ti6Al4V alloy to high-speed machining using carbide inserts. It is a useful extension to work previously published, and aims at assessing the impact of the process parameters, depth of cut, cutting speed and feed rate in addition to cutting length, and their interrelations, on observed crater and flank wear and roughness of the machined surface. The results showed that abrasion was the most important flank wear mechanism at high speed. It also showed that increased cutting length accelerated crater wear more than exhibited flank wear and had considerable effect on surface roughness. In particular, crater wear increased by over 150% (on average), and flank wear increased by 40% (on average) when increasing cutting length from 40 to 120 mm. However, cutting the same length increased surface roughness by 50%, which helps explain how progression of tool wear leads to deteriorated surface ...
The arrival of Industry 4.0 has popularised the concept of smart interactions between humans and ... more The arrival of Industry 4.0 has popularised the concept of smart interactions between humans and the physical world that could realise the synergistic integration of intelligent manufacturing assets. However, a systematic and cogent approach to the practical and profitable application of Industry 4.0 is still missing. This paper presents practical approaches to the application of Industry 4.0 to manufacture with the aim of strengthening its competitiveness and meeting the growing serious challenges that threaten its profitability and survival. Precision Additive Metal Manufacturing is utilised in this study for demonstration purposes. A conceptual framework combined with two practical modules available in the market, a "native-design" and "Plug and Play", is proposed. These approaches offer flexible prototypes with sequential procedures that ultimately would allow for easy employment of Industry 4.0, and will help remove technical barriers to the development of m...
On the Assessment of Thermo-mechanical Degradability of Multi-recycled ABS Polymer for 3D Printing Applications
Sustainable Design and Manufacturing 2019, 2019
Although additive manufacturing (AM) has offered proven ability to reduce waste when compared wit... more Although additive manufacturing (AM) has offered proven ability to reduce waste when compared with traditional manufacturing techniques, however, AM processes such as fused filament fabrication (FFF) still poses some negative environmental and economic aspects in terms of generated waste. This waste comes from rafts, supports, or bases that are parts of the supporting structure necessary in the construction of proper 3D-printed parts. In addition, another source of waste comes from jobs that failed due to a variety of reasons as is common with 3D printing. One possible way to minimize the negative effect is to recycle this waste material. Through the usage of commercially available cutting mills and extruder equipment that are easily procurable, it is possible to recycle the waste and reuse it as a filament. In this context, this paper aims to experimentally investigate the feasibility of recycling 3D printing waste material, namely of ABS material which is a popular 3D printing material and to evaluate changes in the mechanical behaviour after each recycling cycle, while taking the performance of the virgin material as a reference point. The mechanical behaviour of the recycled materials was assessed as a function of obtainable tensile strength, toughness and thermal transition. The results show that the ABS filament shows great promise for recycling at least once and could lead to significant material and cost savings. In this work, it is possible to observe how many times ABS can be recycled and used as filament, without adding virgin material.
The copyright release is a transfer of publication rights, which allows IARIA and its partners to... more The copyright release is a transfer of publication rights, which allows IARIA and its partners to drive the dissemination of the published material. This allows IARIA to give articles increased visibility via distribution, inclusion in libraries, and arrangements for submission to indexes. I, the undersigned, declare that the article is original, and that I represent the authors of this article in the copyright release matters. If this work has been done as work-for-hire, I have obtained all necessary clearances to execute a copyright release. I hereby irrevocably transfer exclusive copyright for this material to IARIA. I give IARIA permission or reproduce the work in any media format such as, but not limited to, print, digital, or electronic. I give IARIA permission to distribute the materials without restriction to any institutions or individuals. I give IARIA permission to submit the work for inclusion in article repositories as IARIA sees fit. I, the undersigned, declare that to the best of my knowledge, the article is does not contain libelous or otherwise unlawful contents or invading the right of privacy or infringing on a proprietary right.
One of the problems encountered in the design and implementation of a serial production line (SPL... more One of the problems encountered in the design and implementation of a serial production line (SPL) is the buffer size between the machine tools. The buffer size of the SPL has an important impact on the productivity of the whole production system. The machine tools' characteristics including their uptimes and downtimes and the process parameters are the main factors that affect the decision regarding the buffer size, and thus the productivity of the SPL. Due to the dynamic nature of this problem, it is complex to find the optimal buffer size in SPL. Thus, in this paper, an Efficient Prediction Model (EPM) is developed using Artificial Neural Network (ANN). The purpose of the developed EPM is to find the buffer size between each succeeding pair of machine tools in SPL at any given uptimes and downtimes of machine tools. An optimization model based on genetic algorithms (GA) is used to generate the learning data for the prediction model to find the optimal or near optimal buffer size of the bay of each machine tool in SPL. The proposed approach integrates the optimization and prediction methodologies to evaluate, and predict the optimal buffer sizes for maximum productivity. Including uptime and downtime parameters enable the proposed method to be used to improve the design of running SPL as well as to design a new SPL. Numerical examples for five and fifteen machine tools were conducted independently in this research and the results show the ability of the proposed method to determine the optimal buffer sizes in a reasonable amount of time. In particular, the results of case studies show that the developed model accurately predict the optimal buffer size, especially for the case of five machines and even for a higher number of machine tools yet with acceptable but less accuracy. Finally, the performance of the proposed approach was compared with some results of the state of the art methods reported in the literature. The comparison shows the superiority of the present approach to identify buffer sizes for higher throughput under the same uptimes and downtimes. INDEX TERMS Flexible manufacturing system, serial production line, optimization, prediction model, buffer size, productivity. NOTATION Abbreviations Descriptions N Number of buffers in the main production line B i Buffer size in front of the machine tool i+1 F(i) Fitness of individual i The associate editor coordinating the review of this manuscript and approving it for publication was Baoping Cai .
Smart modular reconfigurable fully-digital manufacturing system with a knowledge-based framework: example of a fabrication of microfluidic chips
2018 IEEE 14th International Conference on Automation Science and Engineering (CASE), 2018
This paper presents an innovative approach to the development of a smart fully-digital manufactur... more This paper presents an innovative approach to the development of a smart fully-digital manufacturing system based on a modular and reconfigurable production concept. In particular, multiple “plug and play” manufacturing modules, i.e. functional printing, laser processing and welding, in addition to a positioning control unit and quality inspection system, are exploited in an agile manufacturing platform combined with a knowledge-based framework, termed “3D-I”. This enables the production of tailored laminated parts, made up of stacks of functionalised layers of polymer films, with intricate 3D micro features. However, since no tool or mask making is needed, a medium to small lot-size and even one-off parts can be produced in a cost-effective manner. For the evaluation of the “3D-I” approach, a case study of micro-fluidic chips, exemplifying functional parts, are fabricated. The results prove the feasibility of the developed smart system to produce micro-devices with pre-defined specifications. In addition, the knowledge-based manufacturing system demonstrates its potential to offer profitable production scenarios of microdevices, with high flexibility and scalability, outside the area of mass production.
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