Manufacturing Strategies for an Optimal Pull-Type Production Control System. Case Study in a Textile Industry

Aldas, Darwin; Reyes, John; Morales, Luis; Alvarez, Kevin; Portalanza, Narcisa de J.; Aman, Ricardo J.

doi:10.1109/coniiti.2018.8587109

Cited by 6 publications

(2 citation statements)

References 14 publications

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“…This is thanks to the fact that letters can be used that detail pending activities and have relevant information that the operator should know. (Mohan, 2020) (Aldas et al 2018). In case studies such as Sosa's (2020), it could be seen that applying these tools in a textile factory generated a good impact, thus increasing efficiency from 55.88% to 76.79%.…”

Section: Kanban Applicationmentioning

confidence: 99%

Optimization of Lot-Sizing, Scheduling and Storage Capacity Decisions Considering Quality Costs

García,

Covarrubias,

González

2023

Proceedings of the International Conference on Industrial Engineering and Operations Management

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The textile industry in the last decade has considerably increased its competitiveness worldwide, being one of the most influential in the Peruvian economy. For this reason, it is necessary for textile workshops to maintain high productivity, and to be more efficient, making the most of resources in their production. Therefore, the objective of this research is to improve productivity and have better results with little investment, since the textile sector mainly has micro and small companies (SMEs) that occupy a large part of the market, as the company in the present case study. To do this, through the tools of Kanban, 5S and Systematic Layout Planning (SLP), they were implemented in the company to achieve the established objective. Thus, when implementing the 5S, it was possible to obtain better results in terms of a more orderly and clean work area, which allows workers to be more productive and have a better work environment. In the case of SLP, the relational diagram method was carried out and a simulation was carried out using the ARENA software, which had an increase in productivity by reducing the time to carry out a work order of 1400 T-shirts.

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Section: Kanban Applicationmentioning

confidence: 99%

Optimization of Lot-Sizing, Scheduling and Storage Capacity Decisions Considering Quality Costs

García,

Covarrubias,

González

2023

Proceedings of the International Conference on Industrial Engineering and Operations Management

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“…They have developed a method for assessment of pull production system according to twenty-three parameters divided in three groups: design, stability, and control [51]. In addition, Aldas et al have investigated Kanban, Conwip and DBR by simulating production process in the textile industry and concluded with the preference of Kanban over Conwip and DBR [52]. Piplani and Ang, [53], compared Base Stock, Traditional Kanban Control System and Extended Kanban Control System (both dedicated and shared type) by simulation using common total cost measure as a performance measure for comparison.…”

Section: Pull Control Mechanismsmentioning

confidence: 99%

Influence of Bottleneck on Productivity of Production Processes Controlled by Different Pull Control Mechanisms

Tošanović

Štefanić

2022

Applied Sciences

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The goal of any lean implementation in production process is achieving better production performances and one of them is productivity. Among many lean principles, pull principle is the most complex to achieve. There are different production control mechanisms for achieving pull and making decision which one to apply can be demanding because sometimes it is not obvious which is the best for specific situation. Many different production parameters influence production process and for one production setting, one control mechanism is the best choice, but for another production setting it might not be. One goal of this study was to research the influence of bottleneck in the production process in regard to achieving better productivity by applying pull principle. Some of the literature considered deals with the topic of bottleneck and pull but focuses only on bottleneck or in addition on one another production parameter and most of the literature studies up to three different pull control mechanisms. One of the objectives of this study was also to fill the research gap in a way to investigate more mechanisms, particularly, according to the literature, those most widely used in various production conditions with emphasis on bottleneck. The advantage of this research is that in addition to the bottleneck, other parameters, namely the number of control cards, variations and processing time are considered. For that reason, simulation experimentation was conducted and as a result regression functions modelling the relationship between productivity and mentioned parameters for four different pull control mechanisms are gained. The analysis showed that the existence of a bottleneck affects the effectiveness of pull mechanisms in terms of productivity.

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A Study on Modeling and Simulation of Automobile Painting Process Based on Flexsim

Reyes

Aldas

Castelo

et al. 2019

Advances and Applications in Computer Science, Electronics and Industrial Engineering

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Manufacturing Strategies for an Optimal Pull-Type Production Control System. Case Study in a Textile Industry

Cited by 6 publications

References 14 publications

Optimization of Lot-Sizing, Scheduling and Storage Capacity Decisions Considering Quality Costs

Optimization of Lot-Sizing, Scheduling and Storage Capacity Decisions Considering Quality Costs

Influence of Bottleneck on Productivity of Production Processes Controlled by Different Pull Control Mechanisms

A Study on Modeling and Simulation of Automobile Painting Process Based on Flexsim

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