Influence of the Viscosity of Nanofluids on Surface Roughness in End Milling of Nickel Alloys with Minimum Quantity Lubrication

Minimum Quantity Lubrication (MQL) using vegetable oils is considered a sustainable lubrication method, particularly for machining difficult-to-machine materials like nickel and titanium alloys. Although a significant influence of nanofluid viscosity on lubrication has been observed in MQL machining, as evidenced by limited literature, the influence of viscosity on MQL machining of difficult-to-machine materials like nickel alloys is yet to be established. This research aimed to study the influence of viscosity on the MQL end milling machining performance of Inconel 718 alloy. Three representative nanofluids were prepared using metallic (Cu), ceramic (Al2O3), and non-metallic (CNT) nanoparticles and palm oil. It was found that the CNT had a significant influence on viscosity at the same concentration, resulting in the highest viscosity of 433.2cP at 30oC. When the machining performance was investigated under different lubricating conditions (dry machining, flood cooling, and MQL), the viscosity of the nanofluids was observed to have a substantial influence on the machining performance. The CNT nanofluid with the highest viscosity penetrated the machining zone producing the lowest surface roughness with improved lubrication by 65.4% and 30.18% when compared with dry machining and flood cooling, respectively. The surface topography study confirmed the superior lubrication performance of CNT nanofluid. Overall, MQL milling with 0.5wt% nanoparticle concentration demonstrated effective machining performance when compared with dry machining and flood cooling

Management of Intra-Articular Distal Radius Fractures by Open Reduction Internal Fixation and Plate Osteosynthesis Vs Ligamentotaxis : A Comparative Study

AIM: To analyze and compare the functional and radiological outcome of different methods of surgical management of intra-articular distal radius fractures in 50 patients treated by either open reduction, internal fixation and plate osteosynthesis using distal radius volar locking plate or by closed reduction and ligamentotaxis using external fixator with the addition of k wires. MATERIALS AND METHODS: This prospective interventional study was conducted among 50 patients with distal radius intra-articular fracture, treated by either  open reduction internal fixation and plate osteosynthesis using distal radius volar locking plate or by closed reduction and ligamentotaxis using external fixator with the addition of k wires if needed in our institute between July 2020 and November 2022 over a period of 2 years and 5 months. RESULTS: In our study, there were 43 male and 7 female patients, most of whom were in the age group 30-50 years (48%). The mode of injury in most cases was RTA (Road traffic accident).Out of 50 patients, 25 were treated by Open reduction, internal fixation with Volar locking compression plate and 24 were treated by Closed reduction and external fixation augmented by K wire fixation (Ligamentotaxis). There was also found to be no significant difference in the radiological outcome in both groups of patients, i.e Radial length (p=0.253), Palmar tilt (p=0.08), Radial inclination (p=0.075) and articular step-off (p=0.207). In terms of functional outcome of both procedures, only significant difference was found to in palmar flexion of the wrist joint (p=0.003) with better range of palmar flexion seen in the Open reduction and internal fixation with volar locking compression plate group. There was no significant difference seen in dorsiflexion, ulnar and radial deviation, supination and pronation between both surgical techniques. We had a few complications such as malunion, pin loosening and wrist stiffness in our study, majority of which was seen in the Ligamentotaxis group, but it had no statistical significance. A mean DASH score of 11.788 was seen in the VLCP group and 15.192 was seen in the Ligamentotaxis group, the difference was not statistically significant

Influence of the Viscosity of Nanofluids on Surface Roughness in End Milling of Nickel Alloys with Minimum Quantity Lubrication

Minimum Quantity Lubrication (MQL) using vegetable oils is considered a sustainable lubrication method, particularly for machining difficult-to-machine materials like nickel and titanium alloys. Although a significant influence of nanofluid viscosity on lubrication has been observed in MQL machining, as evidenced by limited literature, the influence of viscosity on MQL machining of difficult-to-machine materials like nickel alloys is yet to be established. This research aimed to study the influence of viscosity on the MQL end milling machining performance of Inconel 718 alloy. Three representative nanofluids were prepared using metallic (Cu), ceramic (Al2O3), and non-metallic (CNT) nanoparticles and palm oil. It was found that the CNT had a significant influence on viscosity at the same concentration, resulting in the highest viscosity of 433.2cP at 30oC. When the machining performance was investigated under different lubricating conditions (dry machining, flood cooling, and MQL), the viscosity of the nanofluids was observed to have a substantial influence on the machining performance. The CNT nanofluid with the highest viscosity penetrated the machining zone producing the lowest surface roughness with improved lubrication by 65.4% and 30.18% when compared with dry machining and flood cooling, respectively. The surface topography study confirmed the superior lubrication performance of CNT nanofluid. Overall, MQL milling with 0.5wt% nanoparticle concentration demonstrated effective machining performance when compared with dry machining and flood cooling

Towards Hybrid Automation by Bootstrapping Conversational Interfaces for IT Operation Tasks

Process automation has evolved from end-to-end automation of repetitive process branches to hybrid automation where bots perform some activities and humans serve other activities. In the context of knowledge-intensive processes such as IT operations, implementing hybrid automation is a natural choice where robots can perform certain mundane functions, with humans taking over the decision of when and which IT systems need to act. Recently, ChatOps, which refers to conversation-driven collaboration for IT operations, has rapidly accelerated efficiency by providing a cross-organization and cross-domain platform to resolve and manage issues as soon as possible. Hence, providing a natural language interface to bots is a logical progression to enable collaboration between humans and bots. This work presents a no-code approach to provide a conversational interface that enables human workers to collaborate with bots executing automation scripts. The bots identify the intent of users' requests and automatically orchestrate one or more relevant automation tasks to serve the request. We further detail our process of mining the conversations between humans and bots to monitor performance and identify the scope for improvement in service quality