Prediction and analysis of surface roughness in selective inhibition sintered high-density polyethylene parts: A parametric approach using response surface methodology–grey relational analysis
Selective inhibition sintering (SIS) process intends to produce near-net-shape components through sintering of specific region of powder particles. The prediction of surface quality in SIS parts is a challenging task due to its complex part building mechanism and influence of abundant process parame...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2018-12-01
|
| Series: | Advances in Mechanical Engineering |
| Online Access: | https://doi.org/10.1177/1687814018820994 |
| _version_ | 1818117925580570624 |
|---|---|
| author | D Rajamani Aiman Ziout E Balasubramanian R Velu Salunkhe Sachin Hussein Mohamed |
| author_facet | D Rajamani Aiman Ziout E Balasubramanian R Velu Salunkhe Sachin Hussein Mohamed |
| author_sort | D Rajamani |
| collection | DOAJ |
| description | Selective inhibition sintering (SIS) process intends to produce near-net-shape components through sintering of specific region of powder particles. The prediction of surface quality in SIS parts is a challenging task due to its complex part building mechanism and influence of abundant process parameters. Therefore, this study investigates the key contributing parameters such as layer thickness, heater energy, heater feedrate and printer feedrate on the surface quality characteristics ( R a , R z and R q ) of high-density polyethylene specimens fabricated through selective inhibition sintering process. The SIS system is custom built and experiments are conducted based on four-factor, three-level Box–Behnken design. The empirical models have been developed for predicting the influence of selected parameters on surface quality. The optimal process parameters such as the layer thickness of 0.1 mm, heater energy of 28.48 J/mm 2 , heater feedrate of 3.25 mm/s and printer feedrate of 110 mm/min are attained using grey relational multi-criteria decision-making approach. Furthermore, response surface analysis revealed that surface quality of sintered components is influenced significantly with heater energy and heater feedrate, followed by layer thickness. The confirmation experiments based on optimal process variables validate the developed grey relational analysis strategy. |
| first_indexed | 2024-12-11T04:46:09Z |
| format | Article |
| id | doaj.art-d876d7a802664984b63184c9c725fff3 |
| institution | Directory Open Access Journal |
| issn | 1687-8140 |
| language | English |
| last_indexed | 2024-12-11T04:46:09Z |
| publishDate | 2018-12-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Advances in Mechanical Engineering |
| spelling | doaj.art-d876d7a802664984b63184c9c725fff32022-12-22T01:20:31ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402018-12-011010.1177/1687814018820994Prediction and analysis of surface roughness in selective inhibition sintered high-density polyethylene parts: A parametric approach using response surface methodology–grey relational analysisD Rajamani0Aiman Ziout1E Balasubramanian2R Velu3Salunkhe Sachin4Hussein Mohamed5Centre for Autonomous System Research (CASR), Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, IndiaDepartment of Mechanical Engineering, College of Engineering, United Arab Emirates University, Al Ain, United Arab EmiratesCentre for Autonomous System Research (CASR), Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, IndiaCentre for Autonomous System Research (CASR), Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, IndiaCentre for Autonomous System Research (CASR), Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, IndiaDepartment of Mechanical Engineering, Helwan University, Cairo, EgyptSelective inhibition sintering (SIS) process intends to produce near-net-shape components through sintering of specific region of powder particles. The prediction of surface quality in SIS parts is a challenging task due to its complex part building mechanism and influence of abundant process parameters. Therefore, this study investigates the key contributing parameters such as layer thickness, heater energy, heater feedrate and printer feedrate on the surface quality characteristics ( R a , R z and R q ) of high-density polyethylene specimens fabricated through selective inhibition sintering process. The SIS system is custom built and experiments are conducted based on four-factor, three-level Box–Behnken design. The empirical models have been developed for predicting the influence of selected parameters on surface quality. The optimal process parameters such as the layer thickness of 0.1 mm, heater energy of 28.48 J/mm 2 , heater feedrate of 3.25 mm/s and printer feedrate of 110 mm/min are attained using grey relational multi-criteria decision-making approach. Furthermore, response surface analysis revealed that surface quality of sintered components is influenced significantly with heater energy and heater feedrate, followed by layer thickness. The confirmation experiments based on optimal process variables validate the developed grey relational analysis strategy.https://doi.org/10.1177/1687814018820994 |
| spellingShingle | D Rajamani Aiman Ziout E Balasubramanian R Velu Salunkhe Sachin Hussein Mohamed Prediction and analysis of surface roughness in selective inhibition sintered high-density polyethylene parts: A parametric approach using response surface methodology–grey relational analysis Advances in Mechanical Engineering |
| title | Prediction and analysis of surface roughness in selective inhibition sintered high-density polyethylene parts: A parametric approach using response surface methodology–grey relational analysis |
| title_full | Prediction and analysis of surface roughness in selective inhibition sintered high-density polyethylene parts: A parametric approach using response surface methodology–grey relational analysis |
| title_fullStr | Prediction and analysis of surface roughness in selective inhibition sintered high-density polyethylene parts: A parametric approach using response surface methodology–grey relational analysis |
| title_full_unstemmed | Prediction and analysis of surface roughness in selective inhibition sintered high-density polyethylene parts: A parametric approach using response surface methodology–grey relational analysis |
| title_short | Prediction and analysis of surface roughness in selective inhibition sintered high-density polyethylene parts: A parametric approach using response surface methodology–grey relational analysis |
| title_sort | prediction and analysis of surface roughness in selective inhibition sintered high density polyethylene parts a parametric approach using response surface methodology grey relational analysis |
| url | https://doi.org/10.1177/1687814018820994 |
| work_keys_str_mv | AT drajamani predictionandanalysisofsurfaceroughnessinselectiveinhibitionsinteredhighdensitypolyethylenepartsaparametricapproachusingresponsesurfacemethodologygreyrelationalanalysis AT aimanziout predictionandanalysisofsurfaceroughnessinselectiveinhibitionsinteredhighdensitypolyethylenepartsaparametricapproachusingresponsesurfacemethodologygreyrelationalanalysis AT ebalasubramanian predictionandanalysisofsurfaceroughnessinselectiveinhibitionsinteredhighdensitypolyethylenepartsaparametricapproachusingresponsesurfacemethodologygreyrelationalanalysis AT rvelu predictionandanalysisofsurfaceroughnessinselectiveinhibitionsinteredhighdensitypolyethylenepartsaparametricapproachusingresponsesurfacemethodologygreyrelationalanalysis AT salunkhesachin predictionandanalysisofsurfaceroughnessinselectiveinhibitionsinteredhighdensitypolyethylenepartsaparametricapproachusingresponsesurfacemethodologygreyrelationalanalysis AT husseinmohamed predictionandanalysisofsurfaceroughnessinselectiveinhibitionsinteredhighdensitypolyethylenepartsaparametricapproachusingresponsesurfacemethodologygreyrelationalanalysis |