Investigation, sensitivity analysis, and multi-objective optimization of effective parameters on temperature and force in robotic drilling cortical bone
The bone drilling process is very prominent in orthopedic surgeries and in the repair of bone fractures. It is also very common in dentistry and bone sampling operations. Due to the complexity of bone and the sensitivity of the process, bone drilling is one of the most important and sensitive proces...
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| Veröffentlicht in: | Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine Journal of engineering in medicine, 2017-11, Vol.231 (11), p.1012-1024 |
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| description | The bone drilling process is very prominent in orthopedic surgeries and in the repair of bone fractures. It is also very common in dentistry and bone sampling operations. Due to the complexity of bone and the sensitivity of the process, bone drilling is one of the most important and sensitive processes in biomedical engineering. Orthopedic surgeries can be improved using robotic systems and mechatronic tools. The most crucial problem during drilling is an unwanted increase in process temperature (higher than 47 °C), which causes thermal osteonecrosis or cell death and local burning of the bone tissue. Moreover, imposing higher forces to the bone may lead to breaking or cracking and consequently cause serious damage. In this study, a mathematical second-order linear regression model as a function of tool drilling speed, feed rate, tool diameter, and their effective interactions is introduced to predict temperature and force during the bone drilling process. This model can determine the maximum speed of surgery that remains within an acceptable temperature range. Moreover, for the first time, using designed experiments, the bone drilling process was modeled, and the drilling speed, feed rate, and tool diameter were optimized. Then, using response surface methodology and applying a multi-objective optimization, drilling force was minimized to sustain an acceptable temperature range without damaging the bone or the surrounding tissue. In addition, for the first time, Sobol statistical sensitivity analysis is used to ascertain the effect of process input parameters on process temperature and force. The results show that among all effective input parameters, tool rotational speed, feed rate, and tool diameter have the highest influence on process temperature and force, respectively. The behavior of each output parameters with variation in each input parameter is further investigated. Finally, a multi-objective optimization has been performed considering all the aforementioned parameters. This optimization yielded a set of data that can considerably improve orthopedic osteosynthesis outcomes. |
| doi_str_mv | 10.1177/0954411917726098 |
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It is also very common in dentistry and bone sampling operations. Due to the complexity of bone and the sensitivity of the process, bone drilling is one of the most important and sensitive processes in biomedical engineering. Orthopedic surgeries can be improved using robotic systems and mechatronic tools. The most crucial problem during drilling is an unwanted increase in process temperature (higher than 47 °C), which causes thermal osteonecrosis or cell death and local burning of the bone tissue. Moreover, imposing higher forces to the bone may lead to breaking or cracking and consequently cause serious damage. In this study, a mathematical second-order linear regression model as a function of tool drilling speed, feed rate, tool diameter, and their effective interactions is introduced to predict temperature and force during the bone drilling process. This model can determine the maximum speed of surgery that remains within an acceptable temperature range. Moreover, for the first time, using designed experiments, the bone drilling process was modeled, and the drilling speed, feed rate, and tool diameter were optimized. Then, using response surface methodology and applying a multi-objective optimization, drilling force was minimized to sustain an acceptable temperature range without damaging the bone or the surrounding tissue. In addition, for the first time, Sobol statistical sensitivity analysis is used to ascertain the effect of process input parameters on process temperature and force. The results show that among all effective input parameters, tool rotational speed, feed rate, and tool diameter have the highest influence on process temperature and force, respectively. The behavior of each output parameters with variation in each input parameter is further investigated. Finally, a multi-objective optimization has been performed considering all the aforementioned parameters. This optimization yielded a set of data that can considerably improve orthopedic osteosynthesis outcomes.</description><identifier>ISSN: 0954-4119</identifier><identifier>EISSN: 2041-3033</identifier><identifier>DOI: 10.1177/0954411917726098</identifier><identifier>PMID: 28803514</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Animals ; Biocompatibility ; Biomedical engineering ; Biomedical materials ; Bone surgery ; Burning ; Cattle ; Cell death ; Cortical bone ; Cortical Bone - surgery ; Cracking (fracturing) ; Dentistry ; Drilling ; Feed rate ; Femur - surgery ; Fracture mechanics ; Fractures ; Mathematical models ; Mechanical Phenomena ; Multiple objective analysis ; Optimization ; Osteonecrosis ; Osteosynthesis ; Parameter sensitivity ; Process parameters ; Regression analysis ; Regression models ; Response surface methodology ; Robotic surgery ; Robotic Surgical Procedures - methods ; Sensitivity analysis ; Statistical analysis ; Temperature ; Temperature effects</subject><ispartof>Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine, 2017-11, Vol.231 (11), p.1012-1024</ispartof><rights>IMechE 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c365t-b55d88d47717ed6aa9feabdb5b2ee87f5fa4588e7d9b67f39f4c070cd9f665d33</citedby><cites>FETCH-LOGICAL-c365t-b55d88d47717ed6aa9feabdb5b2ee87f5fa4588e7d9b67f39f4c070cd9f665d33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/0954411917726098$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/0954411917726098$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,780,784,21819,27924,27925,43621,43622</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28803514$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Tahmasbi, Vahid</creatorcontrib><creatorcontrib>Ghoreishi, Majid</creatorcontrib><creatorcontrib>Zolfaghari, Mojtaba</creatorcontrib><title>Investigation, sensitivity analysis, and multi-objective optimization of effective parameters on temperature and force in robotic drilling cortical bone</title><title>Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine</title><addtitle>Proc Inst Mech Eng H</addtitle><description>The bone drilling process is very prominent in orthopedic surgeries and in the repair of bone fractures. It is also very common in dentistry and bone sampling operations. Due to the complexity of bone and the sensitivity of the process, bone drilling is one of the most important and sensitive processes in biomedical engineering. Orthopedic surgeries can be improved using robotic systems and mechatronic tools. The most crucial problem during drilling is an unwanted increase in process temperature (higher than 47 °C), which causes thermal osteonecrosis or cell death and local burning of the bone tissue. Moreover, imposing higher forces to the bone may lead to breaking or cracking and consequently cause serious damage. In this study, a mathematical second-order linear regression model as a function of tool drilling speed, feed rate, tool diameter, and their effective interactions is introduced to predict temperature and force during the bone drilling process. This model can determine the maximum speed of surgery that remains within an acceptable temperature range. Moreover, for the first time, using designed experiments, the bone drilling process was modeled, and the drilling speed, feed rate, and tool diameter were optimized. Then, using response surface methodology and applying a multi-objective optimization, drilling force was minimized to sustain an acceptable temperature range without damaging the bone or the surrounding tissue. In addition, for the first time, Sobol statistical sensitivity analysis is used to ascertain the effect of process input parameters on process temperature and force. The results show that among all effective input parameters, tool rotational speed, feed rate, and tool diameter have the highest influence on process temperature and force, respectively. The behavior of each output parameters with variation in each input parameter is further investigated. Finally, a multi-objective optimization has been performed considering all the aforementioned parameters. This optimization yielded a set of data that can considerably improve orthopedic osteosynthesis outcomes.</description><subject>Animals</subject><subject>Biocompatibility</subject><subject>Biomedical engineering</subject><subject>Biomedical materials</subject><subject>Bone surgery</subject><subject>Burning</subject><subject>Cattle</subject><subject>Cell death</subject><subject>Cortical bone</subject><subject>Cortical Bone - surgery</subject><subject>Cracking (fracturing)</subject><subject>Dentistry</subject><subject>Drilling</subject><subject>Feed rate</subject><subject>Femur - surgery</subject><subject>Fracture mechanics</subject><subject>Fractures</subject><subject>Mathematical models</subject><subject>Mechanical Phenomena</subject><subject>Multiple objective analysis</subject><subject>Optimization</subject><subject>Osteonecrosis</subject><subject>Osteosynthesis</subject><subject>Parameter sensitivity</subject><subject>Process parameters</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Response surface methodology</subject><subject>Robotic surgery</subject><subject>Robotic Surgical Procedures - methods</subject><subject>Sensitivity analysis</subject><subject>Statistical analysis</subject><subject>Temperature</subject><subject>Temperature effects</subject><issn>0954-4119</issn><issn>2041-3033</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kc1rFTEUxYNY7LO6dyUBNy46mkwmH7OUUrVQcFPXQz5uHnnMTMYkU3j9S_rnmtf3FCm4yg3nd86FexB6R8knSqX8THredZT2dW4F6dULtGlJRxtGGHuJNge5Oejn6HXOO0IIpUS8QuetUoRx2m3Q4818D7mErS4hzpc4w5xDCfeh7LGe9bjPIV_WyeFpHUtootmBrTrguJQwhYcnH44eg_cnZdFJT1AgZVylAtMCSZc1wVOOj8kCDjNO0cQSLHYpjGOYt9jGVP96xCbO8AadeT1meHt6L9DPr9d3V9-b2x_fbq6-3DaWCV4aw7lTynVSUglOaN170MYZbloAJT33uuNKgXS9EdKz3neWSGJd74XgjrEL9PGYu6T4a62nGKaQLYyjniGueaB9q6RqqaAV_fAM3cU11SMdqE4ySZVQlSJHyqaYcwI_LClMOu0HSoZDa8Pz1qrl_Sl4NRO4v4Y_NVWgOQJZb-Gfrf8L_A1VyKM5</recordid><startdate>201711</startdate><enddate>201711</enddate><creator>Tahmasbi, Vahid</creator><creator>Ghoreishi, Majid</creator><creator>Zolfaghari, Mojtaba</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>K9.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>201711</creationdate><title>Investigation, sensitivity analysis, and multi-objective optimization of effective parameters on temperature and force in robotic drilling cortical bone</title><author>Tahmasbi, Vahid ; Ghoreishi, Majid ; Zolfaghari, Mojtaba</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c365t-b55d88d47717ed6aa9feabdb5b2ee87f5fa4588e7d9b67f39f4c070cd9f665d33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Animals</topic><topic>Biocompatibility</topic><topic>Biomedical engineering</topic><topic>Biomedical materials</topic><topic>Bone surgery</topic><topic>Burning</topic><topic>Cattle</topic><topic>Cell death</topic><topic>Cortical bone</topic><topic>Cortical Bone - surgery</topic><topic>Cracking (fracturing)</topic><topic>Dentistry</topic><topic>Drilling</topic><topic>Feed rate</topic><topic>Femur - surgery</topic><topic>Fracture mechanics</topic><topic>Fractures</topic><topic>Mathematical models</topic><topic>Mechanical Phenomena</topic><topic>Multiple objective analysis</topic><topic>Optimization</topic><topic>Osteonecrosis</topic><topic>Osteosynthesis</topic><topic>Parameter sensitivity</topic><topic>Process parameters</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Response surface methodology</topic><topic>Robotic surgery</topic><topic>Robotic Surgical Procedures - methods</topic><topic>Sensitivity analysis</topic><topic>Statistical analysis</topic><topic>Temperature</topic><topic>Temperature effects</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tahmasbi, Vahid</creatorcontrib><creatorcontrib>Ghoreishi, Majid</creatorcontrib><creatorcontrib>Zolfaghari, Mojtaba</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tahmasbi, Vahid</au><au>Ghoreishi, Majid</au><au>Zolfaghari, Mojtaba</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Investigation, sensitivity analysis, and multi-objective optimization of effective parameters on temperature and force in robotic drilling cortical bone</atitle><jtitle>Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine</jtitle><addtitle>Proc Inst Mech Eng H</addtitle><date>2017-11</date><risdate>2017</risdate><volume>231</volume><issue>11</issue><spage>1012</spage><epage>1024</epage><pages>1012-1024</pages><issn>0954-4119</issn><eissn>2041-3033</eissn><abstract>The bone drilling process is very prominent in orthopedic surgeries and in the repair of bone fractures. It is also very common in dentistry and bone sampling operations. Due to the complexity of bone and the sensitivity of the process, bone drilling is one of the most important and sensitive processes in biomedical engineering. Orthopedic surgeries can be improved using robotic systems and mechatronic tools. The most crucial problem during drilling is an unwanted increase in process temperature (higher than 47 °C), which causes thermal osteonecrosis or cell death and local burning of the bone tissue. Moreover, imposing higher forces to the bone may lead to breaking or cracking and consequently cause serious damage. In this study, a mathematical second-order linear regression model as a function of tool drilling speed, feed rate, tool diameter, and their effective interactions is introduced to predict temperature and force during the bone drilling process. This model can determine the maximum speed of surgery that remains within an acceptable temperature range. Moreover, for the first time, using designed experiments, the bone drilling process was modeled, and the drilling speed, feed rate, and tool diameter were optimized. Then, using response surface methodology and applying a multi-objective optimization, drilling force was minimized to sustain an acceptable temperature range without damaging the bone or the surrounding tissue. In addition, for the first time, Sobol statistical sensitivity analysis is used to ascertain the effect of process input parameters on process temperature and force. The results show that among all effective input parameters, tool rotational speed, feed rate, and tool diameter have the highest influence on process temperature and force, respectively. The behavior of each output parameters with variation in each input parameter is further investigated. Finally, a multi-objective optimization has been performed considering all the aforementioned parameters. This optimization yielded a set of data that can considerably improve orthopedic osteosynthesis outcomes.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><pmid>28803514</pmid><doi>10.1177/0954411917726098</doi><tpages>13</tpages></addata></record> |
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| subjects | Animals Biocompatibility Biomedical engineering Biomedical materials Bone surgery Burning Cattle Cell death Cortical bone Cortical Bone - surgery Cracking (fracturing) Dentistry Drilling Feed rate Femur - surgery Fracture mechanics Fractures Mathematical models Mechanical Phenomena Multiple objective analysis Optimization Osteonecrosis Osteosynthesis Parameter sensitivity Process parameters Regression analysis Regression models Response surface methodology Robotic surgery Robotic Surgical Procedures - methods Sensitivity analysis Statistical analysis Temperature Temperature effects |
| title | Investigation, sensitivity analysis, and multi-objective optimization of effective parameters on temperature and force in robotic drilling cortical bone |
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