Environmental impacts and hazards associated with metal working fluids and recent advances in the sustainable systems: A review

Najiha, M. S.; Rahman, M. M.; Yusoff, Ahmad Razlan

doi:10.1016/j.rser.2016.01.065

Cited by 112 publications

(36 citation statements)

References 251 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…RSM is a statistical method of three types of modeling: mathematical model, predictive model and optimization model. It works in six functions-(1) input and output variables of a system are to be defined, (2) appropriate experimental design is performed, (3) required regression model development, (4) (3) identification of significant parameters by using analysis of variance, (5) validation of the models by confirmation test and (6) finalization of accept or reject decision. For this study, (1) inputs are v c , f, ϕ, NF, while outputs are F c , θ, R a , (2) Box-Behnken DOE-29 experimental runs, (3) second-order polynomial regression model was developed, (4) ANOVA allows detecting the input parameters that influence the output responses, (5) using explored data, models were validated, and (6) depending on the percentage error the decision was made about acceptance.…”

Section: Response Surface Methodology (Rsm)mentioning

confidence: 99%

See 1 more Smart Citation

Modeling and performance evaluation of Al2O3, MoS2 and graphite nanoparticle-assisted MQL in turning titanium alloy: an intelligent approach

Gupta

Mia

Pruncu

et al. 2020

J Braz. Soc. Mech. Sci. Eng.

View full text Add to dashboard Cite

Recently, the urgency of improved machining performance and environmental sustainability has forced the manufacturer to seek for alternative cooling and lubricating agent/technique such as nano-fluid (NF)-assisted minimum quantity lubrication (MQL). In this context, the performances of aluminum oxide (Al 2 O 3), molybdenum disulfide (MoS 2) and graphite (C) NF-impinged MQL in turning of Ti alloy (grade II) using CBN tool were evaluated regarding the cutting force, cutting temperature and surface roughness. The cutting speed, feed rate, approaching angle and cutting conditions (i.e., NFs) were oriented following the Box-Behnken design-of-experiment. The experimental results showed that the graphite NF, compared to Al 2 O 3 and MoS 2 , revealed the lowest cutting force, temperature and roughness. Moreover, it is evident from SEM images that graphite NF revealed a smoother machined surface and tool profile. This smooth tool and workpiece surface profile can be accredited to graphite's role as a nano-lubricant and its breaking ability into smaller NFs under pressure. To make the study complete, the adaptive neuro-fuzzy inference system (ANFIS) was employed to predict, the response surface methodology (RSM) was used to mathematically model, and the composite desirability approach (CDA) was used to optimize the responses. A good agreement between the experimental and modeled observations was found; however, the ANFIS outperformed the RSM. Moreover, the analysis of variance exhibited that the cutting force and temperature were primarily influenced by the cutting speed and the surface roughness was afflicted mostly by the feed.

show abstract

Section: Response Surface Methodology (Rsm)mentioning

confidence: 99%

“…The above strategies have their limitation or benefits; the novel solution made of nano-fluid imported in MQL was studied as an alternative in machining [4,5]. The nanofluids are reported to increase the thermal conductivity and heat carrying capacity of MWFs.…”

Section: Introductionmentioning

confidence: 99%

Modeling and performance evaluation of Al2O3, MoS2 and graphite nanoparticle-assisted MQL in turning titanium alloy: an intelligent approach

Gupta

Mia

Pruncu

et al. 2020

J Braz. Soc. Mech. Sci. Eng.

View full text Add to dashboard Cite

show abstract

“…Therefore, when magnesium-containing hybrid components are going to be mechanized, it is necessary to take certain security measures regarding the lubricants or coolant systems employed. Depending on the material or materials with which magnesium is combined, different lubrication/cooling techniques can be used [17,18] both individually (dry machining [19][20][21][22][23][24][25][26][27][28][29][30][31], minimum quantity lubrication (MQL) [30][31][32][33][34][35][36][37][38][39][40][41][42], solid lubrication [43][44][45][46][47], cryogenic cooling [48][49][50][51][52][53][54][55], gaseous cooling [56][57][58][59][60][61], nanofluids …”

Section: Introductionmentioning

confidence: 99%

Repairing Hybrid Mg–Al–Mg Components Using Sustainable Cooling Systems

et al. 2020

View full text Add to dashboard Cite

This paper focused on the maintenance or repair of holes made using hybrid Mg–Al–Mg components by drilling, using two sustainable cooling techniques (dry machining and cold compressed air) and taking surface roughness on the inside of the holes as the response variable. The novelty of the work is in proving that the repair operations of the multi-material components (magnesium–aluminum–magnesium) and the parts made of aluminum and magnesium (separately) but assembled to form a higher component can be done simultaneously, thus reducing the time and cost of the assembly and disassembly of this type of component. The study is based on a design of experiments (DOE) defined as a product of a full factorial 23 and a block of two factors (3 × 2). Based on our findings, we propose that the analyzed operations are feasible under sustainable conditions and, in particular, under dry machining. Also, the results depend on the machining order.

show abstract

“…Since businesses must be competitive in the market, when choosing the right MWF, economic aspects also play a very important role. Since according to several literary sources such as (3)(4)(5), the costs related to using MWFs, may achieve about 15 % of the total cost. It is very important to monitor the ratio of price and the declared lifetime of the MWF and, of course, the costs for the disposal of the fluid.…”

Section: Selection Use and Disposal Of Metalworking Fluidsmentioning

confidence: 99%