Optimising Parameters for Expanded Polystyrene Based Pod Production Using Taguchi Method

Abstract

Expanded polystyrene (EPS) is used in the building and construction industry for insulation and under flooring purposes. The objective of the study is to investigate the impact of the application of the total quality management (TQM) technique on the significant parameters of the pod production process in a New Zealand based EPS manufacturing facility. In this work, Taguchi’s L27 orthogonal array (OA) is considered for conducting experiments through three input parameters i.e., weight of untreated beads, batch duration, and temperature is investigated. Based on the results, the analyses are carried out while using statistical approaches, such as analysis of the means (ANOM) and analysis of variance (ANOVA). The results from confirmatory experiment indicate that, at optimal parameters setting (17 kg of untreated bead, 130 s of batch duration and 155 °F of temperature), a reasonably streamlined pod manufacturing process can be achieved for sustainable operations.

Full Optimization of an Electroless Nickel Solution: Boosting the Performance of Low-Phosphorous Coatings

“…Careful positioning of the factors in the L 8 OA needs to be done beforehand in order to anticipate possible interactions between factors [ 19 ]. An interaction between two factors occurs when the effect of a factor on the considered feature or property depends on the level at which the other factor is operating, thereby hiding or polluting the real effect of the former.…”

Comparative analysis of environment losses in steel manufacturing supply chain using Taguchi loss function and design of experiments

“…Evaluation of environmental loss scores for each factor using appropriate TLF: TLF for each environmental loss factor for measuring its score should be selected using the standard functions such as cubic ["Smaller the better" LðyÞ ¼ k 1 3ðy − TÞ 3 ; "Larger the better" LðyÞ ¼ k 2 3ðT − yÞ 3 and "Nominal the better" LðyÞ ¼ k 1 3ðjy − TjÞ 3 þ k 2 3ðjT − yjÞ 3 Where L(y) 5 loss at the particular current value of the attribute; k 1 and k 2 are the constants; T 5 Target value of the attribute and y 5 current value of the attribute], exponential ["Smaller the better" LðyÞ ¼ exp½ðk 1 3yÞ − 1; "Larger the better" LðyÞ ¼ exp½ðk 2 3ðT − yÞÞ − 1 and "Nominal the better" LðyÞ ¼ exp½ðk 1 3yÞ − 1 þ exp½ðk 2 3ðT − yÞÞ − 1] and quadratic ["Smaller the better" LðyÞ ¼ k 1 3ðy − TÞ 2 ; "Larger the better" LðyÞ ¼ k 2 3ðT − yÞ 2 ; "Nominal the better" Develop green closed-loop supply chain model under the demand uncertainty aiming at minimizing total cost and total CO2 emission across the supply chain and maximizing the product' s market share in the presence of a competitor Khan (2019) Develop a production system of closed-loop supply chain in which both forward and reverse production systems are active Ishrat et al (2019) Investigate the impact of the application of the total quality management technique on the significant parameters of the pod production process in a New Zealand based EPS manufacturing facility Lin et al (2019) Develop an integrated approach for a green product cradle-to-cradle (C2C) fuzzy recycling production planning model using appropriate function related to each environmental loss factor. The L (loss) score for every factor should be evaluated using particular y value from the specification limit by the expert's opinion.…”

Methyl red biodegradation based on Taguchi method by two novel bacteria

“…The S/N ratio is calculated using Eq. ( 2) and decibel (dB) is the unit of the S/N ratio (Ishrat et al 2019). In Eq.…”

“…Taguchi method introduces orthogonal array design, which enables researchers to reduce the number of experiments based on the trials considering effective factors. Moreover, the Taguchi method uses the signal-to-noise (S/N) ratio to analyze the variances obtained from the results of a design experiment, which helps researchers select the optimal combinations of factors to gain the desired result with low cost, timesaving, high accuracy and also enables them to investigate the interactions of factors, the contribution of each factor in the experiment and predicts the result of experiment in optimal conditions (Athreya and Venkatesh 2012;Ishrat et al 2019).…”