Selection of optimal processing condition during WEDM of compocasted AA6061/cenosphere AMCs based on grey-based hybrid approach

2018 ◽  
Vol 33 (14) ◽  
pp. 1549-1558 ◽  
Author(s):  
A. Dey ◽  
K. M. Pandey
Keyword(s):  
Hybrid Approach ◽  
Processing Condition ◽  
Optimal Processing ◽  
Optimal Processing Condition ◽  
Selection Of

Optimum performance evaluation during machining of Al6061/cenosphere AMCs using TOPSIS and VIKOR based multi-criteria approach

2021 ◽  
pp. 095440542095877
Author(s):  
Abhijit Dey ◽  
Mrinal Shrivastav ◽  
Pawan Kumar
Keyword(s):  
Decision Making ◽  
Processing Condition ◽  
Optimal Solution ◽  
Machining Process ◽  
Matrix Composites ◽  
Optimal Processing ◽  
Optimal Value ◽  
Vikor Technique ◽  
Pulse On Time ◽  
Selection Of

Selection of optimal processing condition is an issue associate with multi-criteria decision making (MCDM) which can be influenced by several conflicting processing variables. The present study have been devoted to the implementation of TOPSIS algorithm in coordination with the VIKOR technique to yield an optimistic processing criteria while machining of metal matrix composites under electro-discharge machining process. A decision-making module has been developed for selection of optimum processing conditions under specified machining conditions. An experimental investigation was performed based on Taguchi’s orthogonal array on the newly prepared AA6061-cenosphere MMCs to analyze the sensitivity of EDM attributes to the process parameters such as peak current, pulse on time, the percentage of reinforcement, and flushing pressure. The weighing factors for the criteria were determined using AHP method. The results concluded that both the applied MCDM approaches, TOPSIS and VIKOR accrue the similar possible optimal solution having optimal value of pulse current 10 A, pulse on time 1010 µs, percentage of reinforcement as 2% and flushing pressure as 0.6 MPa.

A Hybrid Approach for Data Warehouse View Selection

2008 ◽  
pp. 3085-3115
Author(s):  
Biren Shah ◽  
Karthik Ramachandran ◽  
Vijay Raghavan
Keyword(s):  
Data Warehouse ◽  
Hybrid Approach ◽  
Greedy Heuristic ◽  
Materialized Views ◽  
View Selection ◽  
Materialized View Selection ◽  
Optimal Efficiency ◽  
Access Patterns ◽  
Multiple Query ◽  
Selection Of

Materialized view selection is one of the crucial decisions in designing a data warehouse for optimal efficiency. Static selection of views may materialize certain views that are not beneficial as the data and usage trends change over time. On the contrary, dynamic selection of views works better only for queries demanding a high degree of aggregation. These facts point to the need for a technique that combines the improved response time of the static approach and the automated tuning capability of the dynamic approach. In this article, we propose a hybrid approach for the selection of materialized views. The idea is to partition the collection of all views into a static and dynamic set such that views selected for materialization from the static set are persistent over multiple query (and maintenance) windows, whereas views selected from the dynamic set can be queried and/or replaced on the fly. Highly aggregated views are selected on the fly based on the query access patterns of users, whereas the more detailed static set of views plays a significant role in the efficient maintenance of the dynamic set of views and in answering certain detailed view queries. We prove that our proposed strategy satisfies the monotonicity requirements, which is essential in order for the greedy heuristic to deliver competitive solutions. Experimental results show that our approach outperforms Dynamat, a well-known dynamic view management system that is known to outperform optimal static view selection.

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