Abstract

Keywords

1. Introduction

2. Existing work – wind-induced movement as a design variable

3. Methods

4. Investigations of knitting techniques, resultant textile expressions and affordances

5. Digitally simulating textile behaviour in wind

6. Conclusion and discussion

Declaration of competing interest

Acknowledgements

Appendix A. Pattern for drop-stitch knits

References

Abstract

This study explores the design possibilities with knitted architectural textiles subjected to wind. The purpose is to investigate how such textiles could be applied to alter the usual static expression of exterior architectural and urban elements, such as facades and windbreaks. The design investigations were made on a manual knitting machine and on a CNC (computer numerically controlled) flat knitting machine. Four knitting techniques – tuck stitch, hanging stitches, false lace, and drop stitch – were explored based on their ability to create a three-dimensional effect on the surface level as well as on an architectural scale. Physical textile samples produced using those four techniques were subjected to controlled action of airflow. Digital experiments were also conducted, to probe the possibilities of digitally simulating textile behaviours in wind. The results indicate that especially the drop stitch technique exhibits interesting potentials. The variations in the drop stitch pattern generate both an aesthetic effect of volumetric expression of the textile architectural surface and seem beneficial in terms of wind speed reduction. Thus, these types of knitted textiles could be applied to design architecture that are efficient in terms of improving the aesthetic user experience and comfort in windy urban areas.

1. Introduction

Although textiles are not the most common building material, several good examples of textile architecture exist. An influential architect and theorist Gottfried Semper has claimed that the wall originates from woven structures, such as bast mats. In his seminal book “The four elements of architecture”, he postulates that the true function of a wall is to serve as an enclosure instead of being merely a load-carrying structure (Semper, 2010). Textiles can, however, also be used to carry structural loads. Architect and engineer Frei Otto is perhaps the most well-known designer of tensioned, load-carrying architectural constructions. The work of Krüger (2009) demonstrates that the area of textile architecture shows great variation and richness of the design solutions, both for tensile and non-structural textiles.

Most examples of textiles in architecture use a woven textile, while the knitted structure is not as widely explored within this context. Compared to a knitted textile, in a woven structure the behaviour of the textile is more directly linked to the thread’s strength and stiffness because the threads in the weave are almost straight. In a knit, the thread is forming linking loops. As a result, bigger deformations of the textile occur when forces are applied and the loops are stretched out.

Although scarce, examples of architectural designs and research work on knitted structures exist. For instance, the myTread and Lumen installations by Jenny Sabin (Sabin, 2013; Sabin et al., 2018), Isoropia and The Tower developed at the CITA – Centre for Information Technology and Architecture in Copenhagen (Deleuran et al., 2015; La Magna et al., 2018; Ramsgaard Thomsen et al., 2019), the Knit Tensegrity Shell project by Gupta et al. (2019) and Sean Ahlquist’s sensory architecture (Ahlquist, 2015, 2016). These structures are, however, with some exceptions, mainly based on the principle of tensile textiles, in which the material is stretched until the structure is virtually stiff. They are designed to remain static and, in terms of geometric expression, are bound to an anticlastic surface typology only.

Highlights

Abstract

Keywords

1. Introduction

2. Literature review

3. Problem formulation

4. Methodology

5. Case study

6. Conclusions and future work

Declaration of Competing Interest

Acknowledgments

References

Abstract

Multi-objective optimization, such as quality, productivity, and cost, of the textile manufacturing process is increasingly challenging because of the growing complexity involved in the development of textile industry in the upcoming big data era. It is hard for traditional methods to deal with high-dimension decision space in this issue, and prior experts’ knowledge is required as well as human intervention. This paper proposed a novel framework that transformed the textile process optimization problem into a stochastic game, and introduced deep Q-networks algorithm instead of current methods to approach it in a multi-agent system. The developed multi-agent reinforcement learning system applied a utilitarian selection mechanism to maximize the sum of all agents’ rewards (obeying the increasing ε-greedy policy) in each state, to avoid the interruption of multiple equilibria and achieve the correlated equilibrium optimal solutions of the textile process. The case study result reflects that the proposed MARL system can achieve the optimal solutions for the textile ozonation process, and it performs better than the traditional approaches.

1. Introduction

The textile manufacturing process adds value to fiber materials by converting the fibers into yarns, fabrics, and finished products [1]. Under the arousing global competition, textile companies have to face the challenges of cost reduction and performance improvement. There is a growing public concern on the environment which imposes bounds to the textile manufacturers on the exploitation of power, water and resources. The future development of textile manufacturing relies heavily on product customization and shortened manufacturing cycles since the distributors and consumers are increasingly looking for flexible capacity sensitive to demand variability. To deal with the high degree of variability in materials, processes and parameters, the manufacturers traditionally conduct trial and error, and lean on the expertise and experience [2]. There is a strong need to develop innovative methods to improve the textile manufacturing process.

Since textile manufacturing consists of a very long value chain of processes from raw materials to finished products (a brief example is provided in Fig. 1), the combinations of processes and parameters at different stages could be stochastic and immense when factors of the targeted performance vary in any respect [3–5]. And because of the number of factors such as increasing component (or product) complexity, it is difficult to obtain the optimal scenario of a textile manufacturing process. Meanwhile, the performance of the textile process is always governed by a few criteria and the quality of their significance with an overall objective is different [6]. Thus the optimization problems in this domain always take multiple objectives into account. It is very challenging for the simultaneous optimization of multiple targets in a textile production scheme from high dimensional space.

Scholars tended to employ mathematical programming methods and meta-heuristic algorithms to overwhelm textile manufacturing process optimization problems. Krishna et al. [7] utilized dynamic programming models to find the optimal maintenance policy of sewing machine and to decrease their costs in the textile industry. Majumdar [8] applied linear programming to maximize the overall profit of functional clothing production, and applied goal programming to optimize two conflict objectives, namely ultraviolet protective property and air permeability, of the functional clothing.

1- Introduction

2- Literature review

3- Hypotheses and conceptual models

4- Methods

5- Results

6- Discussion

7- Conclusions

References

Abstract

The aim of the present study was to evaluate how the business-to-business (B2B) networks in the Japanese textile and apparel industry changed between 2005 and 2010 using data on 200 companies. Network analysis was used to study the properties of the B2B networks, and how their structures changed was characterized using the USD/JPY exchange rate. The network analysis revealed power-law properties of the B2B networks, and the core networks characterized by the largest degree centrality exhibited positive correlations with the USD/JPY exchange rate. By contrast, the peripheral networks characterized by the network path length exhibited the negative correlations with the exchange rate USD/JPY. Therefore, the changes that occurred in the B2B networks are explained as the complementarity of comparative advantages originating in the USD/JPY exchange rate. Moreover, the USD/JPY exchange rate afected the B2B networks through not only the complementarity of importing and exporting but also by changing the structures.

Introduction

Generally, there have been trade frictions between Chinese-U.S. industries involved in information communication technology (ICT) (CNN 2019), and those trade frictions seem to have infuenced those various industries. Te adaptations to these economic fuctuations are necessary for the industries and the comprised companies in various regions. It is important to understand the state and its changing of the industries infuenced by macroeconomy for these necessaries of the companies. However, these phenomena are difcult to analyze because the required datasets cannot be obtained synchronously and spatiotemporally. We require typical cases of trade frictions in order to understand the industries with the companies. Our aim in the present study was to demonstrate the changing of the business-to-business (B2B) networks as the industries caused by the exchange rate as the economic fuctuations. To do this, the present study used datasets on the Japanese textile and apparel industry to show the statistical properties of the B2B networks and the changing relationships with the USD/JPY exchange rate. Te method of complex systems was applied to the datasets of the B2B networks. As a result, the analyses revealed an adaptation in the economic changes that took place in the B2B networks. Te present study contributed considerations to a method of how the industries with companies should behave with the global economy as complex systems.