@article{MAKHILLJEAS2019141017831,
    title = {Optimization of Surface Roughness and Machining Time of Manufacturing for
Ankle Foot Orthosis (AFO) with Subtractive Manufacturing using the
Taguchi Method and Fuzzy Logic},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {14},
    number = {10},
    pages = {3179-3193},
    year = {2019},
    issn = {1816-949x},
    doi = {jeasci.2019.3179.3193},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2019.3179.3193},
    author = {B.,P.W.,M.,J.,A.P. and},
    keywords = {EVA rubber foam,custom orthosis,grey fuzzy logic,surface roughness,parameters,diabetes
mellitus},
    abstract = {This research is applied to optimize the manufacturing process of insoles made from EVA foam. This
manufacturing process usually produces a molded system insole with the end result typically impersonal and
according to the needs of normal users. However, this system is not suitable if applied to people who suffer
from foot deformities. An engineering approach is needed to achieve optimization in the process of
manufacturing an insole with a subtractive manufacturing technology. This technology requires a lot of data
and precision. Of the data required to process the appropriate methods, one that was applied was fuzzy logic
to determine the cutting parameters corresponding to the measured responses. A patient with Diabetes Mellitus
(DM) had a complaint on the use of footwear. The Taguchi methodology approach was applied to find the lay
out parameter (L<sub>27</sub> ). The results of the application of the optimum machining parameter indicate the conditions of the fuzzy level at 0.44 and 0.6 on the left and right legs, respectively of the patient. The optimum combination
of this experiment found: raster tool path strategy with 45&deg;, spindle speed at 14,000-14,500 rpm, feed
rate at 800-850 mm/min, step over at 0.30 mm, the type of material was EVA rubber foam as AFO, application of
setting these parameters yields optimum surface roughness for the second leg of 7.9059 and 7.0082 &#956;m. The
optimal machining times were 210.033 and 214.3167 min. The Taguchi methodology and approach to fuzzy logic
were very effective to improve the performance and quality of the product that generated the insole.}
    }