Indonesian Journal of Industrial Engineering & Management
Vol 5, No 1: February 2024

A Taguchi-Simplex Algorithm for the Optimization of Tapped Density for Particulate Orange Peels

Ajibade, Oluwaseyi Ayodele (Unknown)
Agunsoye, Johnson Olumuyiwa (Unknown)
Oke, Sunday Ayoola (Unknown)



Article Info

Publish Date
22 Jun 2024

Abstract

In the composite industry, green fillers transported between locations face undesirable impacts of road surface on powder loads but few methods accurately account for this challenge in tapped density measurements. The purpose of this paper is to introduce a methodology to help composite development engineers manage the transportation of orange particles in transit, on vehicles as they move from the particle production locations to the production process locations. In this paper, the Taguchi method-simplex algorithm (TM-SA) method is proposed for the tapped density optimization of orange peel particulates (OPPs). OPPs of 0.425 and 0.600mm for automobile applications are optimized using experimental data. Managing the transportation process of orange peel particulates and their outcomes needs managing substantial tapped density information. Taguchi method was integrated into the objective function of a simplex algorithm. The tapped density parameters were optimized at the lowest parametric values and the constraints were formulated. It was revealed that for the 0.425mm orange peel particulates, the optimal values and volumetric values were lower by 0.09% and lower by 4.06%, respectively. For the 0.600mm, the optimal values and volumetric values were higher by 0.005% and 6.91%, respectively, when the current method was compared with the literature values from the grey relational analysis. The results at optimality support the effectiveness of the method and were validated by the grey relational analysis results from the literature. The utility of our research is to help green filler powder manufacturers assure cost-effective decisions and logistics delivery optimization.

Copyrights © 2024






Journal Info

Abbrev

ijiem

Publisher

Subject

Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering

Description

The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on industrial engineering and management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise ...