Manufacturing processes in the textile industry. Expert Systems for fabrics production

Bullon, Juan; Arrieta, Angélica González; Encinas, Ascensión Hernández; Dios, Araceli Queiruga

doi:10.14201/adcaij2017641523

Cited by 34 publications

(29 citation statements)

References 10 publications

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“…The unit selling price of i by-product e 1 The input-output coefficient from POY to drawn textured yarn and scrap yarn e 2 The input-output coefficient from textured yarn to greige fabric and scrap fabric e 3 The input-output coefficient of Eco-Brick C 1 , C 2 , C 3 , C 4 The unit material cost of M, m 22d , m 22c and m 22m C 5 , C 6 The unit recycle saving cost of heat and water M The material quantities of POY m 22d The material quantities of dye m 22c The material quantities of cinder m 22m The material quantities of cement L 0…”

Section: Objective Functionmentioning

confidence: 99%

“…The wage rate of the total direct labor hours in overtime work situations Q 1 The overtime working hours (extend working hours to 2 hours per worker) G 0 The limit of the normal direct labor hour δ 0 , δ 1 , δ 2 Special ordered sets of type 1 (SOS1) of 0/1 variables, where only one variable will be 1 r c1…”

Section: Objective Functionmentioning

confidence: 99%

“…The carbon tax rate of available normal CO 2 emission quantities r c2 The carbon tax rate that produces excessive CO 2 emission quantities TC 1 The total CO 2 emission quantities in normal production TC 2 The total CO 2 emission quantities that produces excessive CO 2 emission quantities GC 0 No charge for CO 2 emission quantities RE h , RE w Green energy recycling saving quantities of heat and water F Fixed cost…”

Section: Objective Functionmentioning

confidence: 99%

“…The direct labor hours required by M l 2 The direct labor hours required by X l 3 The direct labor hours required by X µ s,e…”

Section: Unit-level Direct Labor Cost Functionmentioning

confidence: 99%

“…In the past, the textile industry production process was very complicated. Many detailed actions needed to be executed; this caused a production trend of large volume but less variety [2]. Now people are paying more attention to product quality and unique requirements due to technology and people's living habits change.…”

Section: Introductionmentioning

confidence: 99%

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Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

Tsai

2018

Energies

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Abstract:The textile industry is one of the world's major sources of industrial pollution, and related environmental issues are becoming an ever greater concern. This paper considers the environmental issues of carbon emissions, energy recycling, and waste reuse, and uses a mathematical programming model with Activity-Based Costing (ABC) and the Theory of Constraints (TOC) to achieve profit maximization. This paper discusses the combination of mathematical programming and Industry 4.0 techniques to achieve the purpose of green production planning and control for the textile industry in the new era. The mathematical programming model is used to determine the optimal product mix under various production constraints, while Industry 4.0 techniques are used to control the production progress to achieve the planning targets. With the help of an Industry 4.0 real-time sensor and detection system, it can achieve the purposes of recycling waste, reducing carbon emission, saving energy and cost, and finally achieving a maximization of profit. The main contributions of this research are using mathematical programming approach to formulate the decision model with ABC cost data and TOC constraints for the textile companies and clarifying the relation between mathematical programming models and Industry 4.0 techniques. Managers in the textile companies can apply this decision model to achieve the optimal product-mix under various constraints and to evaluate the effect on profit of carbon emissions, energy recycling, waste reuse, and material quantity discount.

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Section: Objective Functionmentioning

confidence: 99%

Section: Objective Functionmentioning

confidence: 99%

Section: Objective Functionmentioning

confidence: 99%

“…The direct labor hours required by M l 2 The direct labor hours required by X l 3 The direct labor hours required by X µ s,e…”

Section: Unit-level Direct Labor Cost Functionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

Tsai

2018

Energies

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Optimizing yarn properties through response surface methodology: Finding the ideal flax and cotton fiber proportion in blended yarns by using design‐expert software

Islam,

‐Karim,

Uddin

2024

SPE Polymers

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The textile industries are looking forward to sustainable textile products. The bio‐based products are very important for protecting the environment, reducing carbon emissions, eliminating chemical pollution, and preserving the resources. These products provide economic advantages and strengthen communities with customer expectations for environmentally friendly items. In addition, sustainable practices encourage innovation and contribute to a healthier and adaptable environment, making them an essential textile product. Here the natural flax fiber plays a vital role due to its eco‐friendly behavior. Cotton‐flax blended yarns are manufacturing for perfect use of natural fibers and getting the better quality yarn than single product yarn. Here in this work it was trying to find out the perfect blending ratio by using Design‐Expert software. Because different blended ratio contain different characteristics. So it was trying to find out a perfect blending solution from the thirteen different ratios by using Design‐Expert software. This software analyses the blended ratios through statistical analysis. This study focuses on the unevenness (U%), imperfection index (IPI), hairiness (H%), tenacity (cN/tex) and elongation at break of the blended yarn. During the analysis the actual and predicted values were checked and it shows good significance, the correlation and regression analysis highlight the results of the samples summary. The findings of the study have great impact on the quality of cotton‐flax blended yarn, which impact on the quality of textile products. This work not only helps to understand cotton‐flax blending using Design‐Expert software, but it also highlights the possibility of using the perfect blended ratio by giving a solution.Highlights To identify the perfect blended ratio of flax and cotton fiber for producing blended yarn. Design‐Expert software has been used to find out the perfect response through yarn properties surface methodology. Thirteen experimental runs were trailed to find the perfect result.

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RETRACTED CHAPTER: Edge Computing: A Review of Application Scenarios

Sittón-Candanedo

2020

Advances in Intelligent Systems and Computing

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Manufacturing processes in the textile industry. Expert Systems for fabrics production

Cited by 34 publications

References 10 publications

Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

Optimizing yarn properties through response surface methodology: Finding the ideal flax and cotton fiber proportion in blended yarns by using design‐expert software

RETRACTED CHAPTER: Edge Computing: A Review of Application Scenarios

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