marker efficiency
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2020 ◽  
Vol 20 (4) ◽  
pp. 484-496
Author(s):  
Tayyab Naveed ◽  
Yueqi Zhong ◽  
Yu Zhicai ◽  
Muhammad Awais Naeem ◽  
Lu Kai ◽  
...  

AbstractIn the apparel manufacturing, the fabric is the single largest element in the cost of the garment. Therefore, effectual fabric consumption causes a reduction in cost and exertions. The purpose of this research is to study the effects of fabric width on the efficiency of marker (cutting) plans. Fabric consumption is in four types for human body shapes, that is, triangle, oval, square, and circle, in both genders to control the fabric utilization. Two clothing styles, fitted trousers and fitted shirts, are manufactured in an apparel manufacturing industry. The marker plans produced through Garment Gerber Technology software are accomplished in 36 different fabric widths (independent variables). The evaluation of dependent variables, that is, marker efficiency, marker loss, and fabric consumption efficiency relevant to four body shapes in variable fabric widths is analyzed for both women and men. The statistical analysis indicates that there is a linear relationship between marker efficiency and fabric width (sig <0.05). The regression analysis (p-value) between dependent variables and predictor variables (body types and fabric width) is also statistically significant. Also, the result implies that markers are more productive with larger fabric widths in all styles in both genders.


2020 ◽  
Vol 46 (2) ◽  
pp. 92-97 ◽  
Author(s):  
Ícaro Fier ◽  
Thiago Willian Almeida Balsalobre ◽  
Roberto Giacomini Chapola ◽  
Hermann Paulo Hoffmann ◽  
Monalisa Sampaio Carneiro

ABSTRACT Sugarcane (Saccharum spp.), an important crop for tropical and subtropical countries, is used in the production of sugar and biofuel. Orange rust, a disease caused by the fungus Puccinia kuehnii, can reduce the yield and harm the sugarcane industry. Molecular markers linked to resistance genes can help breeding programs confirm introgression of favorable alleles, find new resistance sources and release new cultivars that have durable resistance. In the current study, the aims were (i) to evaluate in the field the resistance to orange rust of 24 Brazilian commercial cultivars; (ii) to assess the frequency of the allele at G1 marker locus in the set of cultivars, and (iii) to study the usefulness of G1 marker to predict the resistant phenotype and its potential for marker assisted selection. A diagrammatic scale, which ranged from 1 (plants without symptoms) to 9 (highly susceptible plants), was used to determine the disease severity. Considering resistant cultivars those with mean severity up to 3, G1 marker efficiency in predicting the resistant phenotype was 71.43%. In addition, there was a reduction of 35% in the overall mean severity when G1 marker was present. G1 marker is an important molecular tool that can be used by breeding programs in the search for sugarcane cultivars resistant to orange rust.


2019 ◽  
Vol 19 (2) ◽  
pp. 104-118 ◽  
Author(s):  
Tayyab Naveed ◽  
Azmat Hussain ◽  
Aijaz Ahmed Babar ◽  
Awais Naeem ◽  
Hassan Mussana ◽  
...  

Abstract In the apparel manufacturing, fabric utilization always remains the significant apprehensions in controlling the production expenditure. Alteration in pattern shapes and marker preparation leads to the enormous utilization of fabric. The purpose of this research is to study fabric efficiency in correspondence with four different human body shapes in both genders. Two clothing styles, fitted trousers and fitted shirts, were processed conventionally in the garment manufacturing company. The comparative study of auto-marker and manual-marker making through Garment Gerber Technology (GGT) software were also accomplished. The evaluation of fabric consumptions, marker efficiency, marker loss, fabric loss, and fabric cost relevant to four different body shapes was analyzed for both women and men. The investigation carried out in this article concludes that there are differences in fabric consumptions, efficiencies, and cost-effectiveness relative to body shapes. The result revealed that the manualmarker of trousers for triangular body shape in women’s wears has the least fabric consumption (most cost-effective), whereas the shirt’s auto-marker for an oval body shape in men’s wears has the most fabric utilization (least costeffective). The manual-virtual-marker making is efficient (significant p-value) than auto-generated-markers. Also, fabric utilization for women’s garments is cost-effective than that for men. Trousers are cost-effective compared to the shirts.


2018 ◽  
Vol 18 (4) ◽  
pp. 348-363
Author(s):  
Daniel Domović ◽  
Tomislav Rolich ◽  
Marin Golub

Abstract Marker planning is an optimization arrangement problem, where a set of cutting parts need to be placed on a thin paper without overlapping to create a marker – an exact diagram of cutting parts that will be cut from a single spread. An optimal marker that utilizes the length of textile material has to be obtained. The aim of this research was to develop novel algorithms for obtaining an efficient marker that would achieve competitive results and optimize the garment production in terms of improving the utilization of textile material. In this research, a novel Grid heuristic was introduced for obtaining a marker, alongside its improvement methods: Grid-BLP and Grid-Shaking. These heuristics were hybridized with genetic algorithm that determined the placement order of cutting parts using the newly introduced All Equal First (AEF) placement order. A novel individual representation for genetic algorithm was designed that was composed of order sequence, rotation detection and the choice of placement algorithm (hyper-heuristic). Experiments were conducted to determine the best marker making method, and hyper-heuristic efficiency. The implementation and experiments were conducted in MATLAB using GEATbx toolbox on five datasets from the garment industry: ALBANO, DAGLI, MAO, MARQUES and MAN SHIRT. Marker efficiency in percentage was recorded with best results: 84.50%, 80.13%, 79.54%, 84.67% and 86.02% obtained for the datasets respectively. The most efficient heuristic was Grid-Shaking. Hyper-heuristic applied Grid-Shaking in 88% of times. The created algorithm is independent of cutting parts’ shape. It can produce markers of arbitrary shape and is flexible in terms of expansion to new instances from the garment industry (leather nesting, avoiding damaged areas of material, marker making with materials with patterns).


2018 ◽  
Vol 6 (6) ◽  
pp. e01159 ◽  
Author(s):  
Ali Amiryousefi ◽  
Jaakko Hyvönen ◽  
Péter Poczai
Keyword(s):  

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