Methodology selecting packaging materials combined multi‐sensory experience and fuzzy three‐stage network DEA model

Abstract

Materials selection involves thousands of material types and evaluation parameters.Considering multisensory experience for packaging materials selection is an important trend but a difficult duty that involves uncertainty due to the subjectivity of humans. The main aim of this study is to establish a model to determine the consumer sensory experience of packaging materials as a function supporting packaging material selection development. When the consumer interacts before and after opening the packaging, vision and tactility are the foremost sensory feedback types, which are difficult to measure for fuzziness and uncertainty. Thus, given the consumer senses of vision and tactility, this paper addresses the relationship between sensory experience and packaging material properties. This is creatively formulated in three stages from the physical properties and the psycho-physical to the affective levels.The proposed approach that combines fuzzy theory and three-stage network data envelopment analysis (DEA) is used to rank 12 toning lotion bottle packaging materials. It is validated that this model allows a clear decision-making basis for material selection in packaging design, and physiological signal tests provided key data to support material selection. Moreover, it realized the function of predicting physiological signal according to material properties by backpropagation neural network (BPNN).

Promoting Green Supply Chain Management With Optimal Selection Of Packaging Materials Using Integrated Fuzzy MCDM and Rl Model

“…Mahajan et al [8] applied integrated MCDM in selecting sustainable materials. Xie et al [9] employed a three stage fuzzy network and DEA method. Different combinations of MCDM methods are used in selecting optimal packaging materials based on different criterion weights.…”

Corrugated Box Damage Classification Using Artificial Neural Network Image Training

“…While the functionality of ANN has been studied extensively, this application has not yet been widely brought to the packaging industry. There have been instances of this tool being utilized in terms of analysis of packaging [20][21][22], but little has been done in terms of visual analysis of a package. In this paper, a method for utilizing the image capabilities of ANN for corrugated regular slotted container (RSC) evaluation will be introduced.…”