Multi-objective performance investigation of orthopaedic bone drilling using Taguchi membership function

2017 ◽  
Vol 231 (12) ◽  
pp. 1133-1139 ◽  
Author(s):  
Gurmeet Singh ◽  
Vivek Jain ◽  
Dheeraj Gupta
Keyword(s):  
Membership Function ◽  
Bone Cells ◽  
Optimization Technique ◽  
Real Life ◽  
Multiple Response ◽  
Bone Drilling ◽  
Taguchi Optimization ◽  
Response Characteristics ◽  
Response Optimization ◽  
Single Response

Orthopaedic bone drilling attacks the surrounded bone cells and tissues in terms of thermal and mechanical in such a way that these cells can get damaged permanently. This damage to the surrounding of drill point upsurges the rehabilitation time of injury and in some cases leads to the failure of the bone screw joint. This study is based on the optimization of multiple response characteristics to minimize the damage during the bone drilling. All real-life problems, including bone drilling, require the multiple response optimization for getting a combined optimization result for all countable response characteristics. The Taguchi optimization technique is observed as a highly recommended tool for single response optimization. This article uses the Taguchi technique with little modification of membership function that will help to convert the multiple response characteristics into single response and further optimize it as a single function of performance. Rotational speed, feed rate of tool at three different levels with three different kinds of drilling tools are the drilling parameters selected for the study. The objective of this study is to minimize the surface roughness and thrust force simultaneously. Analysis of variance helps to find the percentage contribution and significance of each parameter on the performance.

Multiple-Response Surface Approach: Modeling and Optimization

2011 ◽  
Vol 339 ◽  
pp. 321-325
Author(s):  
Bin Nie ◽  
Dan Liao ◽  
Jing Ding ◽  
Yao Dong He
Keyword(s):  
Operating Conditions ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Multiple Response ◽  
Response Models ◽  
Modeling And Optimization ◽  
Response Data ◽  
Model Average ◽  
Response Optimization ◽  
Single Response

Many products and processes have multidimensional characteristics and criteria. As these responses involve common parameters and processes, the response data are correlated. The quality and reliability improvement of such products and processes will typically involve multiple-response optimizations to find optimal operating conditions. Many of the current multiple-response optimization approaches assume a single-response uncertainty in the response models, and the uncertainty in the parameter estimates of the models. In this paper, we consider a Bayesian Model Average (BMA) approach to the modeling and optimization of variability of the predictions and the uncertainty of the model parameters. We further propose a Mahalanobis distance (MD) approach to account for the correlations among the response and the variation in the estimation of the response model.

Parametric effect of vibrational drilling on osteonecrosis and comparative histopathology study with conventional drilling of cortical bone

2018 ◽  
Vol 232 (10) ◽  
pp. 975-986 ◽  
Author(s):  
Gurmeet Singh ◽  
Vivek Jain ◽  
Dheeraj Gupta ◽  
Abhimanyu Sharma
Keyword(s):  
Healing Process ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Influential Factor ◽  
Bone Drilling ◽  
Taguchi Optimization ◽  
Morphological Comparison ◽  
Drilling Parameters ◽  
Drilling Technique ◽  
Conventional Drilling

Drilling to the bones is required to re-fix them at their appropriate location using the implants. During drilling some thermal and mechanical losses may be faced by the bone and surrounding tissues which may lead to the serious issue in terms of osteonecrosis. Osteonecrosis is one of the reasons for impaired healing process for the fractured bone and causes further complications like low pullout strength of cortical screws and bone crush. In order to maintain the low temperature during bone drilling, this study focused the thermal damages observed by the bone and its surrounding during bone drilling and compared the results of conventional and vibrational drilling techniques. Parametric optimization under the influence of vibrations was also studied. Drilling has been done with the both drilling technique, and results were recorded in terms of temperature raise. Optimal solution for drilling the bone has been accessed using Taguchi optimization technique. The morphological comparison has been done for conventional and vibrational drilled holes using histopathology of drilled bones sections. From Taguchi optimization, it was observed that R1F1A1 is the parametric combination which gives minimum thermal injury to the bone in case of vibrational bone drilling. Analysis of variance cleared that the all parameters involved significantly affect the results (P ≤ 0.05). Rotational speed was found to be the most influential factor among the all with 80.53%. Histopathology studies of bone specimens help to understand how heat generation affects the bone morphology during drilling. The specimens drilled with vibrational drilling show less damage in terms of osteonecrosis near the drill site which shows the significance of vibrational drilling in case of orthopedic surgeries. The raise in temperature during drilling is collective result of different drilling parameters. Vibrational drilling was observed a helping tool to control the thermal damage in bone drilling.

Solution of Correlated Multi-Response Optimization Problem

2012 ◽  
pp. 61-79
Author(s):  
Saurav Datta ◽  
Goutam Nandi ◽  
Asish Bandyopadhyay ◽  
Pradip Kumar Pal
Keyword(s):  
Objective Function ◽  
Optimization Problem ◽  
Desirability Function ◽  
Optimization Technique ◽  
Principal Component ◽  
Integrated Approach ◽  
Bead Geometry ◽  
Taguchi Optimization ◽  
Entropy Measurement ◽  
Response Optimization

This paper highlights an integrated approach to solve the correlated multi-response optimization problem through a case study in submerged arc welding (SAW). The proposed approach has been presented to overcome different limitations and drawbacks of existing optimization techniques available in literature. Traditional Taguchi optimization technique is based under the assumption that quality responses are independent to each other; however, this assumption may not always be valid. A common trend in the solution of a multi-objective optimization problem is to convert these multi-objectives into an equivalent single objective function. While deriving this equivalent objective function, different weightage are assigned to different responses according to their relative priority. In this regard, it seems that no specific guideline is available for assigning individual response weighs. To avoid this, Principal Component Analysis (PCA) has been adopted to eliminate correlation among individual desirability values and to calculate uncorrelated quality indices that have been aggregated to calculate overall grey relational grade. This study combines PCA, Desirability Function (DF) approach, and grey relation theory to the entropy measurement technique. Finally, the Taguchi method has been used to derive optimal process environment capable of producing desired weld quality related to bead geometry.

Solution of Correlated Multi-Response Optimization Problem

2010 ◽  
Vol 1 (4) ◽  
pp. 22-46 ◽  
Author(s):  
Saurav Datta ◽  
Goutam Nandi ◽  
Asish Bandyopadhyay ◽  
Pradip Kumar Pal
Keyword(s):  
Objective Function ◽  
Optimization Problem ◽  
Desirability Function ◽  
Optimization Technique ◽  
Principal Component ◽  
Optimization Techniques ◽  
Individual Response ◽  
Bead Geometry ◽  
Taguchi Optimization ◽  
Response Optimization

This paper highlights an integrated approach to solve the correlated multi-response optimization problem through a case study in submerged arc welding (SAW). The proposed approach has been presented to overcome different limitations and drawbacks of existing optimization techniques available in literature. Traditional Taguchi optimization technique is based under the assumption that quality responses are independent to each other; however, this assumption may not always be valid. A common trend in the solution of a multi-objective optimization problem is to convert these multi-objectives into an equivalent single objective function. While deriving this equivalent objective function, different weightage are assigned to different responses according to their relative priority. In this regard, it seems that no specific guideline is available for assigning individual response weighs. To avoid this, Principal Component Analysis (PCA) has been adopted to eliminate correlation among individual desirability values and to calculate uncorrelated quality indices that have been aggregated to calculate overall grey relational grade. This study combines PCA, Desirability Function (DF) approach, and grey relation theory to the entropy measurement technique. Finally, the Taguchi method has been used to derive optimal process environment capable of producing desired weld quality related to bead geometry.

A Combinational Approach for Experts of Committee Machine in Wire Bonding Problem Solving

2013 ◽  
Vol 465-466 ◽  
pp. 751-755
Author(s):  
Seyed Jafar Golestaneh ◽  
Ismail Napsiah ◽  
Mohd Khairol Anuar Bin Mohd Ariffin ◽  
Say Hong Tang ◽  
Hassan Moslemi Naeini ◽  
...  
Keyword(s):  
Problem Solving ◽  
Experiment Design ◽  
Wire Bonding ◽  
Multiple Response ◽  
Committee Machine ◽  
Initial Approach ◽  
Multiple Response Optimization ◽  
Response Optimization ◽  
Modelling And Optimization ◽  
Three Phases

There are three phases to solve multiple response optimization (MRO) problems. They are experiment design, modelling and optimization. Different committee machines (CMs) are applied for modeling of MRO problem. Two kinds of CM introduced by current authors in recent works. Initial approach includs utilization of all experts in CM and finally sequentilal combinational model (SCM) is created. Current study proposes a combinational approach to filter and select the best experts to create CM which yields optimum combinational model (OCM). Also , there was another modeling with name point approach model (PAM). This study investigated two different features of different SCMs, PAM and OCM in a famous MRO problem with name wire-bonding. This problem was defined in 1997 and then, several researchers solved it in next years. The results show PAM has minimum RMSE but its global desirability is low. Also overall RMSE has a slightly fall from SCMs to OCM , whereas, there is gently rise in global desirability from SCMs to OCM and consequently proposed approach or OCM provides superior results.

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