Modern supply chains are vulnerable to high impact, low probability disruption risks. A supply chain usually operates in such a network of entities where the resilience of one supplier is critical to overall supply chain resilience. Therefore, resilient planning is a key strategic requirement in supplier selection decisions for a competitive supply chain. The aim of this research is to develop quantitative resilient criteria for supplier selection and order allocation in a fuzzy environment. To serve the purpose, a possibilistic fuzzy multi-objective approach was proposed and an interactive fuzzy optimization solution methodology was developed. Using the proposed approach, organizations can tradeoff between cost and resilience in supply networks. The approach is illustrated using a supply chain case from a garments manufacturing company.

Promotion of durable materials and products is a common approach to enhance sustainability. However, the effectiveness of such efforts lies on shifts in user behavior and consumption patterns, and these patterns are influenced not only by material aspects but also by social and experiential dimensions. It has been observed that the consumers’ consumption pattern, i.e., post-consumption behavior, is as harmful as production. However, this area remains largely unexplored. The primary purpose of this study is to explore sustainable garment design strategies to enhance emotional durability of garments and reduce pre-consumer and most importantly, the post-consumer waste. For this purpose, 18 garments were produced using ZWPC for pre-consumption waste reduction and DFD for post-consumption waste minimization. Three hypotheses were developed. Quantitative and qualitative data were collected through questionnaires and wear trials on the practicality of DFD implementation in garments. The results demonstrated that the combination of these strategies has the potential to curb both pre-consumer and post-consumer waste by designing garments that can enter the biological as well as technical cycle of circular fashion (CF). Furthermore, DFD is a success in increasing the use-life of a garment.

Intricacy of the supply chains for deteriorating products, involving multiple retailers with unequal lot sizes and multiple deliveries is simplified in this article by optimizing the replenishment cycle, investment in preservation technology, and number of deliveries. This study proposes a multi-tier supply chain model consisting of a single manufacturer and multiple retailers. A single-setup multiple deliveries (SSMD) policy is adopted considering the synchronized cycle time of manufacturers with that of retailers and the delivery of unequal lot size for each retailer. Preservation technology is used at retailers to minimize the effects of deterioration in a way that the magnitude of decrease in deterioration reduces for additional investment in preservation technology. A centralized supply chain model is proposed by defining a nonlinear mathematical model for maximizing total profit through an analytical optimization technique and an algorithm. Numerical experiments are exhibited to validate the applications of the provided model. The results exhibit that the proposed preservation policy increases the product’s lifetime and the total profit by reducing the number of shipments/transportation and increasing the lot size. The SSMD policy helps to reduce the preservation cost and increase the total profit. Some managerial insights are provided for the decision makers for applying the proposed model.

Sewing thread is one of the most important components of a sewn product that contributes significantly in the useful life of a product. Stitch class 504 is the one which is used in all types of sewn products. Its thread consumption is higher than class 300 and class 400. A mathematical model to predict the sewing thread consumption of stitch class 504 has been proposed in this paper. The model is based on the geometry of the stitch. The proposed model takes into account material thickness and stitch density. The model was validated by using 24 samples (with different material thickness and stitch densities). The accuracy of the model was found to be 99%. Sensitivity analysis revealed that stitch density has 62% effect and material thickness has 38% effect on thread consumption. The proposed model can predict the thread consumption accurately; therefore, it can be used for better estimation of required thread and encourage its better utilization in sewn product industry.

Purpose: In the field of knitwear, dimensional stability is assumed as a critical problem that affects the quality and salability of a product. Although much work has been done in this area with a focus on the factors affecting fabric shrinkage, however, there is a lack of work on knitwears with respect to their dimensional stability. The purpose of this paper is to investigate the impact of stitching parameters and wash types on the dimensional properties of knitwear. Design/methodology/approach: The crew-neck t-shirts were prepared by using pique knitted fabrics. Different sewing and finishing parameters were used that include stitch density, stitch type, stitching thread and wash type. The critical measurements of the selected garment are taken as output variables which are body width, sleeve length, body length and across shoulder. After laundering process, shrinkage percentage was calculated by using before-wash and after-wash measurements. Findings: This study shows that the stitching parameters affect significantly on knitwear’s shrinkage. Thus, when patterns are being developed for the cutting of fabric, expected shrinkage, known as residual shrinkage, must be considered to avoid unexpected changes in garment shape. Originality/value: This research will be useful for knitwear manufacturing industry.