Comparative evaluations of machining performance during turning of 17-4 PH stainless steel under cryogenic and wet machining conditions

Sivaiah, P.; Chakradhar, D.

doi:10.1080/10910344.2017.1337129

Cited by 39 publications

(17 citation statements)

References 31 publications

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“…Conformation experimental results showed good agreement with predicted results. In the literature, few studies have been carried out to select the optimum process parameters and cooling type during turning of PH SS grade material under different sustainable machining techniques [24][25][26][27][28][29][30]. Sampaio et al [31] performed comparative studies in turning of SAE1045 steel under dry and MQL cutting condition respectively.…”

Section: Introductionmentioning

confidence: 99%

Experimental investigation and modelling of MQL assisted turning process during machining of 15-5 PH stainless steel using response surface methodology

Sivaiah¹

2019

SN Appl. Sci.

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Built-up-edge formation is one of the problems in conventional (flood) machining of 15-5 precipitated hardened stainless steel (PH SS) which results in poor product quality. Further, concentration on stringent environmental conscious regulations has been increasing in metal cutting industries due to environmental pollution. The present work target is to address these problems using minimum quantity lubrication (MQL) machining technique. MQL machining technique is one of the promising techniques for the metal cutting industries because it satisfies the stringent environmental conscious regulations set for metal cutting industries in terms of usage and disposal of chemically contaminated emulsion based coolants. In the present work, studied the effect of MQL cooling, process parameters on turning performance characteristics and also established a relationship between the turning controllable process parameters and responses in the machining of 15-5 PH SS using response surface methodology (RSM) under MQL environment with tungsten carbide cutting insert. Spindle speed (v), feed rate (f), depth of cut (d) and MQL flow rate (Q) have been taken as MQL machining process parameters. Output turning performances considered were surface roughness (R a), tool flank wear (T w) and material removal rate respectively. Experiments were done based on the central composite design of RSM. From RSM analysis, it was noticed that developed mathematical models predicted the performance results close to the experimental results. Further, it was observed that surface roughness and tool wear reduced significantly with an increase in MQL flow rate respectively.

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Section: Introductionmentioning

confidence: 99%

Experimental investigation and modelling of MQL assisted turning process during machining of 15-5 PH stainless steel using response surface methodology

Sivaiah¹

2019

SN Appl. Sci.

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“…Several studies investigated their proposed SM technologies through application case studies. Automotive [109,138,139], machinery [133,136,140], food [113,127], and medical [114] sectors were noted as the application sectors in the latest SM technology research.…”

Section: Thematic Map Of Sustainable Manufacturing Technology Researchmentioning

confidence: 99%

“…The sustainability indicators studied in the articles were codified and extracted, and key indicators were identified for each TBL sustainability dimension, as presented in Fig- Cutting environment was evidenced as the key theme of the latest sustainable machining body of knowledge (70% of articles categorised under sustainable machining), with SM technology studies studying the elimination of lubrication substances through cryogenic [138,139], dry machining [128,140] and indirect cooling [141], or their reduction/optimisation through minimum quantity lubrication (MQL) techniques [142,143].…”

Section: Sustainability Indicators Studiedmentioning

confidence: 99%

Sustainable Manufacturing Technologies: A Systematic Review of Latest Trends and Themes

Bastas

2021

Sustainability

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Meeting current needs while not sacrificing the future ability to do so as a key sustainability concept is becoming more challenging than ever, with the increasing population rate, energy poverty, global warming, and surging demand for products and services. Manufacturing is in a prime position to address this challenge, with its significant economic contribution to the global GDP and its high influence over the environment and humanity. Sustainable manufacturing technologies research is growing to support our journey towards sustainable development. This article undertook the systematic review of state-of-the-art sustainable manufacturing technologies literature, evidencing the latest themes and trends in this important research avenue. Descriptive and thematic analyses were performed, synthesising the latest advancements in the field. Sustainable manufacturing processes, especially sustainable machining, was established as a key theme, including research endeavours of elimination of lubricants. Various manufacturing systems and process sustainability assessment technologies were noted. Sustainability indicators addressed were critically evaluated. As an outcome, a conceptual framework of sustainable manufacturing technology research was constructed to structure the knowledge acquired and to provoke future thinking. Finally, challenges and future directions were provided for both industrial and academic reader base, stimulating growth in this fruitful research stream.

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“…Cutting force is one of the main machining parameters which play an important role during the machining process. In fact, cutting force needs to be better understood and its measurement should be accurate to improve machinability of alloys [2,3]. Aluminum-silicon alloys are extensively used in automobile, aerospace, and general engineering industries due to the low expansion coefficient mechanical properties, weldability, and machinability [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Neuro-fuzzy based predictive model for cutting force in CNC turning process of Al–Si–Cu cast alloy using modifier elements

et al. 2021

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This study investigated the predicted cutting force model of a turning operation for Al–Si–Cu cast alloy modified with modifiers based on adaptive neuro-fuzzy inference system (ANFIS) approach. Feed rate, cutting speed and Silicon spacing were considered as the input parameters. A series of turning experiments were conducted at various feed rates and cutting speeds. The prediction result showed that the ANFIS model successfully predicted the cutting force value in terms of cutting speed, feed rate and Si spacing. A mathematical model was proposed to describe the cutting force changes during the machining of Al–Si–Cu cast alloy. Moreover, the addition of Bismuth into the base alloy decreased the cutting force compared to other refinement elements.

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Comparative evaluations of machining performance during turning of 17-4 PH stainless steel under cryogenic and wet machining conditions

Cited by 39 publications

References 31 publications

Experimental investigation and modelling of MQL assisted turning process during machining of 15-5 PH stainless steel using response surface methodology

Experimental investigation and modelling of MQL assisted turning process during machining of 15-5 PH stainless steel using response surface methodology

Sustainable Manufacturing Technologies: A Systematic Review of Latest Trends and Themes

Neuro-fuzzy based predictive model for cutting force in CNC turning process of Al–Si–Cu cast alloy using modifier elements

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