Application of Factorial Design in Selective Laser Sintering

Selective Laser Sintering (SLS) is a complex process involving many process parameters. These parameters are not all independent. A factorial design technique is utilized to study the effects of three main process parameters, laser power, laser beam scanning speed, and powder packing density as well as their interactions on the sintering depth and fractional density. The results of this investigation provide useful information for the further experimental analysis of the process parameters and for selecting suitable parameters for SLS process.Mechanical Engineerin

Factorial Design Applied to Waste Immobilisation in Geopolymer-based Systems

Concentrated alkali, ground glass and air pollution control residues were mixed in various proportions and cured for up to 28 days. These blocks were tested in strength and analysed by thermal gravimetric analysis to assess the success of the geopolymerisation process. A Taguchi factorial design approach was then adopted to investigate the effects of different variables upon the strength development of these blocks

A Study For Efficiently Solving Optimisation Problems With An Increasing Number Of Design Variables

Coupling optimisation algorithms to Finite Element Methods (FEM) is a very promising way to achieve optimal metal forming processes. However, many optimisation algorithms exist and it is not clear which of these algorithms to use. This paper investigates the sensitivity of a Sequential Approximate Optimisation algorithm (SAO) proposed in [1-4] to an increasing number of design variables and compares it with two other algorithms: an Evolutionary Strategy (ES) and an Evolutionary version of the SAO (ESAO). In addition, it observes the influence of different Designs Of Experiments used with the SAO. It is concluded that the SAO is very capable and efficient and its combination with an ES is not beneficial. Moreover, the use of SAO with Fractional Factorial Design is the most efficient method, rather than Full Factorial Design as proposed in [1-4]

FRACTIONAL FACTORIAL DESIGN AND ORTHOGONAL ARRAYS

This study aims to conduct statistical analysis of various types of FRACTIONAL FACTORIAL DESIGN (orthogonal arrays), comparisons between various types of orthogonal arrays with and without replication for the determination of the precision with which factor effects and interactions are estimated Keywords: FRACTIONAL FACTORIAL DESIGN, orthogonal array