Application of Modified Similarity-Based Method for Cotton Fiber Selection

Application of Modified Similarity-Based Method for Cotton Fiber Selection

Kanika Prasad (National Institute of Technology Jamshedpur, India) and Rishi Dwivedi (Xavier Institute of Social Service, India)
DOI: 10.4018/978-1-5225-8579-4.ch007


In today's business environment, sustainability is one of the most significant issues that organizations needs to deal with. Fiber choice is often the initial stride that designers and product developers will consider in minimizing the ecological impact of a garment while achieving sustainability. Cotton fiber, whether alone or blended with some other fiber, is being extensively used in textile industries. However, the selection of optimal cotton fiber depends on its several properties like length, strength, fineness, length uniformity, short fiber content, etc., thus making this selection process s multi-criteria decision-making problem. Thus, for the first time, this chapter examines the applicability and feasibility of a modified similarity-based approach for selection of cotton fiber which in turn assists in achieving sustainable design characteristics. Two illustrative examples from past researches and one existing cotton fiber selection problem of a small textile organization are solved applying the adopted method to validate its veracity and robustness.
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Global trade in textiles and garments has played a vital role in the progress of numerous nations and has also assisted their assimilation in to the worldwide financial system. In the industrialized countries, the procedure of development and ensuing opulence in a way started with the automation of textile manufacturing in the early 19th Century. However, in the developing nations, the said industry has occupied an imperative position among all other sectors based on its contribution to national output, employment and exports. On the basis of a report published by India Brand Equity Foundation in the year 2018, Indian textiles industry is currently computed to be at around US$ 150 billion, and anticipated to touch US$ 250 billion by 2019. It added 7% of the industry output of India in 2017-18. India’s textiles industry contributed 2% to its national GDP and provided employment to more than 45 million people in 2017-18. Besides, in 2017-18, 15% of the export earnings of India are contributed through the said industry. With rapidly changing business ecosystem, the textile and clothing industry needs to undergo structural changes globally. Organisations in this sector need to adopt sustainable and flexible production systems for their production lines. Additionally, global sustainable structure is being characterized by higher potential for profit from innovation, marketing, and retailing rather than assembling, finishing and packaging alone. Moreover, with growing environmental consciousness in recent years, the application of renewable raw materials as well as eco-friendly and sustainable fibers has become very significant from the textile industry’s perspective. Hence, selection of long lasting fiber provides a sustainable approach to said sector. In addition, the manufacturing of numerous synthetic fibers contaminates the eco system. Thus, for managers of textile enterprises, it is indispensable to bestow importance to selection of fiber while achieving sustainability. Amongst all different types of fibers used in the textile industries, cotton fiber is the most widely used natural fiber. Its natural schema and features yield functional and marketable benefits for consumer, institutional and industrial products. Cotton fiber almost constitutes half of the textile and clothing materials. Since, the textile industries in India are predominantly cotton-based and cotton fiber is their mainstay/backbone, it is very important to acquire the best quality of fiber for manufacturing a specified product. Not only textiles, but industries as varied as consumer products, healthcare and automotive appreciate the favorable outcomes of including cotton fiber in their diverse product segments because of its dependability and adaptability for assorted applications. In different regions of India several varieties of cotton fibers are cultivated. These zones differ from each other in various aspects, like topography, type of soil and irrigation facilities that ultimately affect the quality and yield/productivity of cotton fibers. The quality of cotton bale is determined by its various physical properties, such as length, length uniformity, strength, amount of trash, color grade etc. Besides, the cotton fibers utilized for weaving/knitting the yarns greatly affect the value and utility of textile/cloth produced. Therefore, identification of the most appropriate cotton fiber from a vast variety of available options is essential for attaining sustainability and advanced quality control in textile production. However, many physical and chemical properties influence the selection of cotton fiber and there may exist complex interrelationship among these selection criteria. For example, longer fibers allow higher spinning speed and also yield quality end product by producing stronger yarns, but a higher value of micronaire fiber becomes a limiting factor in spinning fine yarn. Therefore, evaluation of available cotton fiber alternatives based on influencing criteria/properties makes the selection process a multi-criteria decision-making (MCDM) problem. Several MCDM methods which can deal with this type of selection problem have been discussed in past. The objective of this paper is to apply a distance-based approach modified similarity-based method for selection of the most suitable cotton fiber from various alternatives available. Options in this method are evaluated with respect to positive and negative ideal solutions on a comprehensive concept. The overall performance index of all choices across each criterion is estimated based on the combination of the degree of similarity to positive and negative ideal solutions employing alternative gradient and magnitude. Lastly, cotton fiber alternative with highest performance index is identified as best option on the basis of selected criteria.

Key Terms in this Chapter

Vector: It is characterized as a line section having an explicit direction and a definite length.

Negative Ideal Solution: It is the result that maximizes the cost criteria and minimizes the benefit criteria.

Positive Ideal Solution: It is the solution that maximizes the benefit criteria and minimizes the cost criteria.

Normalization: It is a technique used to minimize data redundancy and augment data integrity.

Criterion: It is the yardstick on which an item is evaluated.

Attributes: It is trait that an object possesses.

Multi-Criteria Decision Making: It is a valuable tool that is apt to solve problems that are characterized as a choice among alternatives based on conflicting criteria.

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