Two-by-Two Factorial Design

Modeling and optimization of precipitation hardening heat treatment factors of Al2024 alloy using a two-level full factorial design

In the current study, the sources of variation in the mean hardness value of heat treated aluminum 2024 samples were identified by using metallurgical study and design of experiment methodology (full factorial method). Hardness measurements and microstructural investigations of the samples were carried out using Brinell hardness test and optical microscopy, respectively. The effects of several ...

Factorial Design

Design and Analysis of Two-Level Factorial Experiments With Partial Replication

In a two-level factorial experiment, we consider construction of parallel-flats designs with two identical parallel flats that allow estimation of a set of specified possibly active effects and the pure error variance. A set of sufficient conditions is presented for the designs to be D-optimal for the specified effects, assuming that the other effects are negligible, over the class of competing...

Distribution Design of Two Rival Decenteralized Supply Chains: a Two-person Nonzero Sum Game Theory Approach

We consider competition between two decentralized supply chains network under demand uncertainty. Each chain consists of one risk-averse manufacturer and a group of risk-averse retailers. These two chains present substitutable products to the geographical dispensed markets. The markets’ demands are contingent upon prices, service levels, and advertising efforts of two supply chains. We formulat...

Analytical Enantio-Separation of Linagliptin in Linagliptin and Metformin HCl Dosage Forms by Applying Two-Level Factorial Design

A novel, stability indicating, reverse phase high-performance liquid chromatography (RP-HPLC) method was developed to determine the S-isomer of linagliptin (LGP) in linagliptin and metformin hydrochloride (MET HCl) tablets (LGP-MET HCl) by implementing design of experiment (DoE), i.e., two-level, full factorial design (2³ + 3 centre points = 11 experiments) to understand the critical method par...