Dye Schedule Optimization: A Case Study in a Textile Industry

Gomes, Uiraquitan Tadeu; Pinheiro, Plácido Rogério; Saraiva, Rommel Dias

doi:10.3390/app11146467

Cited by 5 publications

(5 citation statements)

References 20 publications

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“…. [18], [20], [21], [17]. Downtime in production flows in SMEs in the textile sector is a very recurrent problem that is mainly due to the absence of standardized production systems and inadequate resource planning.…”

Section: State Of Artmentioning

confidence: 99%

Production Model to Increase the Rate of Order Fulfillment through the Implementation of Lean and MRP Tools in Dyeing in the Textile Sector

2022

Proceedings of WCSE 2022 Spring Event: 2022 9th International Conference on Industrial Engineering and Applications

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The textile sector is one of the industries with the greatest relevance and development of the Peruvian economy, however, currently customers are characterized by being increasingly demanding, which forces organizations to be more flexible to change, these changes have a great impact on small and mediumsized companies as it causes problems of non-fulfillment of orders making service levels very low. It should also be noted that it is these companies that are unaware of the importance of using continuous improvement tools, as well as those that provide little or no training to their staff as a strategy to mitigate the problem. Consequently, a literature review was carried out in order to compile production models of the textile sector to solve the problem of non-fulfillment of orders. The proposed model includes Lean Manufacturing tools, as well as the use of MRP. The present design is focused on the implementation of models executed in other companies without the need for a very large investment, or the use of the most advanced technology of today.

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Section: State Of Artmentioning

confidence: 99%

Production Model to Increase the Rate of Order Fulfillment through the Implementation of Lean and MRP Tools in Dyeing in the Textile Sector

2022

Proceedings of WCSE 2022 Spring Event: 2022 9th International Conference on Industrial Engineering and Applications

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“…where U is the global best solution. Now, the index vector with the minimum B value categorizes the elements based on family { [1], [7], [4], [8,6], [2], [5,3]} and decomposes the resultant vector based on the machine capacity by ( 1) and ( 2) Machine 1 (M1): {[1], [7], [4], [5,3]} and Machine 2 (M2): { [8,6], [2]} As another example, for the index vector [6, 1,…”

Section: Solution Initializationmentioning

confidence: 99%

“…Moreover, Gendreau et al 3 suggest that the setup times are significant and need to be considered during optimization. Also, Gomes et al 4 suggest that the reduction of operational costs and proper management of production needs to be done to face competitiveness. Thus, proper scheduling can be a more effective way to reduce wastewater and curb the related pollution.…”

mentioning

confidence: 99%

Achieving sustainability through improvement in the textile wet process using particle swarm optimization and the tabu search algorithm

Hiremath

Bansode²,

Kumar

2022

Textile Research Journal

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As far as cloth production is concerned, the dyeing process in textiles forms a bottleneck procedure, as this process consumes a great deal of time and high volumes of water per unit of fabric for processing, which causes depletion of groundwater levels at a high rate. Besides, textile effluents are discharged into rivers or wetlands without proper treatment in many cases. Untreated textile effluent can contaminate groundwater and water bodies, reduce dissolved oxygen in the water, and affect aquatic ecosystems, which may indirectly cause climate change. The waste generated in dyeing is mainly due to the cleaning process. Thus, the dyeing process needs to be improved and optimized to solve the problem and reduce delay. To take effective measures for future improvement, it is essential to develop a nature-inspired tracking system. The amount of emission and the performance can be improved by utilizing scheduling as a tool. In this view, the dyeing process is formulated as a bi-objective optimization model to reduce the tardiness cost and minimize the emission of wastewater during the cleaning process of the dyeing vat. The current problem is of a difficult nature; thus, multi-objective particle swarm optimization in collaboration with the tabu search algorithm has been used to attain good and nondominant results. The tabu search algorithm is used along with ejection chains to focus on the objectives of emission reduction and increase the number of desired solutions. It was found that the total processing time was reduced by 4–5 hours and water was reduced by 500 liters for dyeing 200 kg of yarn daily.

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“…Resources are the foundation of strategy, and distinct collections of resources produce competitive advantages that contribute to the production of wealth [1,2].…”

Section: Introductionmentioning

confidence: 99%

“…Maintenance has evolved into a critical sector for the survival and growth of any firm, since its effects directly influence the environment, performance, and safety of industrial activities [8]. Failure analysis has also evolved into a sophisticated approach for enhancing the system, the tools, and, eventually, the business [2].…”

Section: Introductionmentioning

confidence: 99%

Prioritising Maintenance Work Orders in a Thermal Power Plant: A Multicriteria Model Application

Andrade¹,

Pinheiro

Narciso³

et al. 2022

Sustainability

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Maintenance is one of the most rapidly expanding activities in the industrial environment, since its application is no longer limited to simple, regular fixes. In the case of thermal power plants maintenance is essential, since they only operate when the National Electric System Operator wants them to complement the production from renewable sources such as hydro, wind, and solar. To limit the frequency of failures that result in generation unavailability, the operation team performs daily inspections to evaluate the equipment’s condition and the risks to the generating process. If an anomaly is found, the maintenance team will create service notes to address it. This research aims to demonstrate how the method Measuring Attractiveness by a Category-Based Evaluation Technique (Macbeth) can be applied to the development of a multiple-criterion model to support decision making in ordering the criticality of systems in thermal plant operational inspection routes to propose new methodologies for routine execution to increase the operation team’s productivity. According to the results of the judgement matrix, the recommended ordering enabled a strategy for the performance of the current operational routes by redefining the criticality, periodicity, routing, and resources utilised, hence preserving the plant’s reliability. According to the results, the proposed ranking will enable a new strategy for integrated maintenance planning, redefining the criticality of service orders according to the judgement based on criteria and subcriteria, thereby allowing the application of resources appropriately and focusing on what is more important to maintain the thermal power plant’s continuity and operational safety.

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Dye Schedule Optimization: A Case Study in a Textile Industry

Cited by 5 publications

References 20 publications

Production Model to Increase the Rate of Order Fulfillment through the Implementation of Lean and MRP Tools in Dyeing in the Textile Sector

Production Model to Increase the Rate of Order Fulfillment through the Implementation of Lean and MRP Tools in Dyeing in the Textile Sector

Achieving sustainability through improvement in the textile wet process using particle swarm optimization and the tabu search algorithm

Prioritising Maintenance Work Orders in a Thermal Power Plant: A Multicriteria Model Application

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