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The effect of pick density, constituent filament fineness and heat‐setting on the fabric thickness and compressional properties have been studied before and after laundering. With the increase in pick density fabric thickness, compression and compressibility increases up to a certain extent. Coarser filament textured yarn fabric have higher thickness, compression and compressibility than that of finer filament textured yarn fabrics. Heat‐set fabrics possess higher thickness, compression and compressibility than the grey textured yarn fabrics. However, fabric compressional recovery and resiliency are mainly influenced by the fabric pick density rather than the effect of heat‐setting and filament fineness of constituent textured yarns. On laundering, fabric thickness, compression and compressibility improve particularly for the fabric of lower pick density. The effect of laundering is marginal on fabric compressional recovery and resiliency.

The purpose of this paper is to investigate the effect of pick density, pile height and pile yarn count (both single- and double-ply yarn) on the colour fastness to crocking, colour fastness to washing, colour fastness to water of woven velour printed terry fabrics. These variables have also been optimized for developing high-quality fabrics.

Variables were selected on the basis of past research experience and samples were prepared according to the Box–Behnken design of experiments. The samples were tested for colour fastness to crocking, colour fastness to washing and colour fastness to water by following AATCC 8, AATCC 61, 2A and AATCC 107, respectively.

The colour fastness to crocking, washing and water of woven velour printed terry fabrics increases with the decrease in pile height and pick density. The colour fastness properties of the fabric increase with increase in fineness of the pile yarn count. Woven velour printed terry fabric with 16.25 picks per cm, 3.5 mm pile height and 16 Ne pile yarn will show best colour fastness. Woven velour printed terry fabric (plied pile yarn) with 16.25 picks per cm, 3.5 mm pile height and 2/24 Ne pile yarn will show best colour fastness

Proved a practical approach to control fastness properties of the fabric by changing fabric variables.

Colour fastness properties of woven velour printed terry fabrics have never been reported. The research work gives the better understanding to develop high quality of fabrics by reducing pile height and pick density. This will also reduce the cost of the fabric.

Increasing personnel costs and labour shortages have pushed retailers to give increasing attention to their intralogistics operations. We study hybrid order picking systems, in which humans and robots share work time, workspace and objectives and are in permanent contact. This necessitates a collaboration of humans and their mechanical coworkers (cobots).

Through a longitudinal case study on individual-level technology adaption, we accompanied a pilot testing of an industrial truck that automatically follows order pickers in their travel direction. Grounded on empirical field research and a unique large-scale data set comprising N = 2,086,260 storage location visits, where N = 57,239 storage location visits were performed in a hybrid setting and N = 2,029,021 in a manual setting, we applied a multilevel model to estimate the impact of this cobot settings on task performance.

We show that cobot settings can reduce the time required for picking tasks by as much as 33.57%. Furthermore, practical factors such as product weight, pick density and travel distance mitigate this effect, suggesting that cobots are especially beneficial for short-distance orders.

Given that the literature on hybrid order picking systems has primarily applied simulation approaches, the study is among the first to provide empirical evidence from a real-world setting. The results are discussed from the perspective of Industry 5.0 and can prevent managers from making investment decisions into ineffective robotic technology.

Bending and shear rigidities of woven fabrics depend on fibre, yarn and fabric-related parameters. However, there is lack of research efforts to understand how bending and shear rigidities change in woven fabrics having similar areal density. The purpose of this paper is to investigate the change in bending and shear rigidities in plain woven fabrics having similar areal density.

A total of 18 fabrics were woven (9 each for 100 per cent cotton and 100 per cent polyester) keeping the areal density same. Yarns of 20, 30 and 40 Ne were used in warp and weft wise directions and fabric sett was adjusted to attain the desired areal density.

When warp yarns become finer, keeping weft yarns same, bending rigidity remains unchanged but shear rigidity increases in warp wise direction. When weft yarns are made finer, keeping the warp yarns same, both the bending and shear rigidities of fabric increase in warp wise direction. Similar results for fabric bending and shear rigidities were obtained in transpose direction. There is a strong association between fabric shear rigidity and number of interlacement points per unit area of fabric even when fabric areal density is same.

Very limited research has been reported on the low-stress mechanical properties of woven fabrics having similar areal density. A novel attempt has been made in this research work to investigate the bending and shear rigidities of woven fabrics having similar areal density. Besides, it has been shown that it is possible to design a set of woven fabrics having similar bending rigidity but different shear rigidity.

This paper aims to develop an approach to design a warehouse that uses class-based storage policy in a way that minimizes both space cost and material handling cost.

The authors argue for and develop an optimization model for joint determination of lane depth, lateral width and product partitions for minimizing the sum of handling and space costs. In doing so, the assumption of perfect sharing is also relaxed. Using computational experiments, the authors characterize the operating conditions based on pick density and cost ratio. The authors further outline an approach to decide the conditions under which it is advantageous to implement multiple classes.

More classes are preferred when both the pick density and cost ratio are higher and vice versa. Factors such as demand skewness, lane depth and stacking height affect the space-sharing dynamics.

The paper gives the practical insights on when the conditions under which it is advisable to partition a warehouse into a certain number of classes instead of maintaining and when to maintain as a single-class block. It also gives a method to estimate the space-sharing factor, given a combination of operating parameters.

Very few studies have seen class-based storage policy in the context of block stacked warehouse layout. Further, block stacking designs have mostly been approached with the objective of minimizing just the space cost. This study contributes to the literature by developing an integrated model, which has the practical utility.

Today, Jacquard woven fabric producers are able to digitally control each warp yarn individually, pre-program the variable pick density and speed for each filling yarn, and automatically change a pattern without stopping the weaving process. Jacquard CAD systems dramatically reduce the time to produce fabric from the artwork or target design The process of weave/color selection for each area of the pattern is, however, still highly dependent on the CAD system operator who works from a particular color gamut. Multiple weaving trials are required to get a sample that matches the original artwork since the process requires the designer‘s subjective evaluation. The lack of automatic selection of weaves/color matching prompts this research.

This paper addresses the development of a geometric model for predicting the color contribution of each warp and filling yarn on the fabric surface in terms of construction parameters. The combination of geometric modeling and existing color mixing equations enables the prediction of the final color of different areas of a Jacquard pattern. The model was verified experimentally and a close agreement was found between a color mixing equation and the experimental measurements.

Modeling helps to determine how structural parameters of fabric affect the surface of a fabric and also identify the way they influence fabric properties. Moreover, it helps to estimate and evaluate without the complexity and time-consuming experimental procedures. The purpose of this study is to develop and select the best regression model equations for the prediction and evaluation of surface roughness of plain-woven fabrics.

In this study, a linear and quadratic regression model was developed for the prediction and evaluation of surface roughness of plain-woven fabrics, and the capability in accuracy and reliability of the two-model equation was determined by the root mean square error (RMSE). The Design-Expert AE11 software was used for developing the two model equations and analysis of variance “ANOVA.” The count and density were used for developing linear model equation one “SMD1” as well as for quadratic model equation two “SMD2.”

From results and findings, the effects of count and density and their interactions on the roughness of plain-woven fabric were found statistically significant for both linear and quadratic models at a confidence interval of 95%. The count has a positive correlation with surface roughness, while density has a negative correlation. The correlations revealed that models were strongly correlated at a confidence interval of 95% with adjusted R² of 0.8483 and R² of 0.9079, respectively. The RMSE values of the quadratic model equation and linear model equation were 0.1596 and 0.0747, respectively.

Thus, the quadratic model equation has better capability accuracy and reliability in predictions and evaluations of surface roughness than a linear model. These models can be used to select a suitable fabric for various end applications, and it was also used for tests and predicts surface roughness of plain-woven fabrics. The regression model helps to reduce the gap between the subjective and objective surface roughness measurement methods.

The purpose of this paper is to study the performances of “pick‐and‐sort” order‐picking systems (OPSs) and investigate picking efficiency and design issues as a function of the number and length of the picking waves.

An analytical model is proposed to estimate the picking efficiency as a function of wavelength. The model, which has been tested by simulations, includes an algorithm to estimate the expected overlapping of order lines. Finally, a case study illustrates the use of the model in the initial assessment phase of OPS design, and resolves the trade‐off between picking efficiency and sorting cost.

The effect of the wavelength on picking efficiency is calculated.

The trade‐off analysis between picking efficiency and sorting cost refers to a specific sorting system and picking area layout.

The paper provides a tool to support the design of “pick‐and‐sort” OPS, where the importance of the length of the picking wave emerges.

This paper presents an innovative model that can be used in the initial phase of “pick‐and‐sort” OPS design.

Order picking is one of the most costly logistics processes in warehouses. As a result, the optimization of order picking processes has received an increased attention in recent years. One potential source for improving order picking is the reduction of picker blocking. The purpose of this paper is to investigate picker blocking under different storage assignment and order picker-route combinations and evaluate its effects on the performance of manual order picking processes.

This study develops an agent-based simulation model (ABS) for order picking in a rectangular warehouse. By employing an ABS, we are able to study the behaviour of individual order pickers and their interactions with the environment.

The simulation model determines shortest mean throughput times when the same routing policy is assigned to all order pickers. In addition, it evaluates the efficiency of alternative routing policies–storage assignment combinations.

The paper implies that ABS is well-suited for further investigations in the field of picker blocking, for example, with respect to the individual behaviour of agents.

Based on the results of this paper, warehouse managers can choose an appropriate routing policy that best matches their storage assignment policy and the number of order pickers employed.

This paper is the first to comprehensively study the effects of different combinations of order picker routing and storage assignment policies on the occurrence of picker blocking.

The tension variations across the width of the weaver's beam cause uneven tension in the fabric formation zone. As a result of the tension variation, the woven fabric tends to have fabric defects, such as non-uniform fabric density and differential dye take–up at various places on the fabric. As the warp ends are continuously subjected to varying tensions, warp breakage frequently occurs. As a result, the quality of the fabric produced suffers and there is reduced loom efficiency. However, uniformity in the fabric density is crucial, especially for technical and smart textiles. In this paper, the authors have attempted to model the varyingtensions across different segments of a warp sheet under a set of assumptions and derived a linear model. Furthermore, a prototype of an automatic tension control device is instrumentedwith two different positions which are located one meter apart and allows the tension variations across the warp-sheet to be practically observed. The measured average tension shows that variations in the internal tension on different segments of the warp-sheet can be minimized or even completely eliminated over time. With the implementation of a related experiment, the authors have shown the effectiveness of this automatic tension controller and its strong implications for the industry.