美国皮革化学家协会杂志发表关于皮革科学、工程、技术和经济学各个方面的手稿，并将考虑解决行业关注的相关主题。示例：生皮/毛皮质量或利用、皮革生产方法/设备、制革材料/皮革化学品、新皮革和改进皮革、胶原蛋白研究、皮革副产品、皮革制品行业变化的影响、工艺效率、可持续性、监管、安全，环境，制革废物管理和行业经济学。

The Journal of the American Leather Chemists Association is a journal dedicated to all aspects of leather science, engineering, technology, and economics. We welcome manuscripts addressing relevant topics of concern to the industry, including but not limited to: the quality and utilization of raw hides and pelts, leather production methods and equipment, tanning materials and chemicals, new and improved leathers, collagen research, leather by-products, the impact of changes in the leather goods industry, process efficiency, sustainability, regulation, safety, environmental issues, leather waste management, and industry economics.

《Journal of the American Leather Chemists Association》是一本专注于皮革科学、工程、技术和经济学各个方面的期刊。我们欢迎关于行业关注的相关主题的手稿，包括但不限于：生皮和毛皮的质量与利用、皮革生产方法和设备、制革材料和化学品、新型皮革及其改进、胶原蛋白研究、皮革副产品、皮革制品行业变化的影响、工艺效率、可持续性、监管、安全、环境、制革废物管理以及行业经济学等。

Journal of the American Leather Chemists Association

None The Editors

Front Matter

前言

With the rapid advancement of robotic technology, traditional manufacturing industries are encountering unprecedented opportunities and challenges. The leather industry, as a typical representative, urgently requires automation. However, due to the irregular edges, softness, and variable shapes of leather, automation faces significant technical challenges. To address this issue, this study proposes a high-precision grasping point recognition model based on an improved PointNet++ algorithm. By incorporating the Shuffle Attention mechanism, the improved PointNet++ algorithm significantly enhances the capture of key features, improving the segmentation accuracy and overall performance of the leather grasping areas. Experimental results demonstrate that the improved model exhibits superior performance in leather recognition and grasping experiments, achieving a recognition success rate of 96% and a grasping success rate of 89.6%. These results fully validate the effectiveness and practicality of the improved model in handling leather, providing reliable technical support for automated leather processing.

Yuan Huan

Gongchang Ren

Ruoxuan Xu

Guang Jin

Jiangong Sun

Improved PointNet++ Algorithm for Feature Point Recognition in Dual-Arm Robotic Grasping and Unfolding of Leather

改进的PointNet++算法在双臂机器人抓取和展开皮革中的特征点识别

Leather is a material with unique mechanical properties, making it widely used in the production of footwear, clothing, sports articles, and in the field of coverings, such as in the automotive, furniture, marine and aeronautical industries. Leather processing involves three major stages: beamhouse, tanning, and finishing. In each of these stages, characteristic effluents are generated, which typically reach the Wastewater Treatment Plant (WWTP) mixed, for the so called end-of-pipe treatment, consisting of primary and secondary treatment. The objective of this study is to analyze the characteristics of the effluents generated in each processing stage individually and when mixed, in order to assess how the mixture impacts degradability. For the evaluation, wastewater corresponding to the three stages was generated, using raw hides for (i) beamhouse and (ii) tanning, and wet-blue leather for (iii) wet finishing. Subsequently, chemical inputs were added to the wastewater, forming synthetic effluents. The (iv) mixture of the effluent generated in the three stages was made based on the proportion of each effluent in relation to the total generated. Analyses of Biological Oxygen Demand (BOD) and Total Organic Carbon (TOC) were performed for the four samples. The BOD obtained for the mixture was zero, while the other three effluents obtained high values for the same analysis. This result indicates that an inhibitory environment to microbial growth was formed, preventing biodegradation. The TOC results indicate that the mixture contains an organic load proportional to the effluents that compose it. It was concluded that the organic load and biodegradability of the effluent can be strongly influenced by the processing methods of each tannery, such as the amount of water and inputs used, and that the secondary treatment of mixed effluents tends to be compromised compared to segregated treatment.

O. Manuelle Minozzo

Eduarda C.S. Pistorello

Vânia Queiroz

Bruno G. Duarte

Caroline Agustini

Synthetic Tannery Effluent Mixture Degradability Assessment

合成制革废水混合物降解性评估

Leather, a versatile material, faces high resource consumption and waste issues in production. This study explores the use of supercritical carbon dioxide (scCO2) as a green solvent for leather impregnation, assessing its impact on the leather’s chemical and physical properties. Furniture and upper shoe leathers were exposed to CO2 pressures between 100 and 250 bar at 40°C. Results show decreasing fat content with increased pressure, which correlates with reduced tensile strength - especially significant in upper shoe leather at 250 bar with a nearly 50% reduction in fat content from 7% to 3.7% and tensile strength from 480 N to 250 N. However, pressure treatment can also enhance tensile strength when fat reduction is low. The highest increase in tensile strength, from 110 N to 180 N, was observed for furniture leather following treatment at 100 bar. In industrial settings with lower CO2 surplus, fat extraction impacts are assumed to be minimal, suggesting significant potential for resource-efficient leather production using scCO2.

M. Prokein

M. Renner

Impact of Supercritical Carbon Dioxide on the Physical and Chemical Properties of Leather

超临界二氧化碳对皮革物理化学性质的影响

Lifelines

生命线

短名	JALCA
Journal Impact	0.67
国际分区	MATERIALS SCIENCE, TEXTILES(Q4)
期刊索引	SCI Q3中科院 4 区

ISSN	0002-9726
h-index	33
国内分区	工程技术(4区)工程技术应用化学(4区)工程技术材料科学纺织(4区)

涉及主题	化学有机化学生物工程类材料科学物理生物化学复合材料制浆造纸工业冶金化学工程量子力学生态学食品科学医学
出版信息	出版商: American Leather Chemists Association，出版周期: Monthly，期刊类型: journal，开源期刊: 否
基本数据	创刊年份: 1994，原创研究文献占比: 98.04%，自引率:50.00%， Gold OA占比: 0.00%
平均审稿周期	网友分享经验：平均3.0个月
平均录用比例	网友分享经验：容易

Journal of the American Leather Chemists Association

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Front Matter

Improved PointNet++ Algorithm for Feature Point Recognition in Dual-Arm Robotic Grasping and Unfolding of Leather

Synthetic Tannery Effluent Mixture Degradability Assessment

Impact of Supercritical Carbon Dioxide on the Physical and Chemical Properties of Leather

Lifelines

Front Matter

Improved PointNet++ Algorithm for Feature Point Recognition in Dual-Arm Robotic Grasping and Unfolding of Leather

Synthetic Tannery Effluent Mixture Degradability Assessment

Impact of Supercritical Carbon Dioxide on the Physical and Chemical Properties of Leather

Lifelines