以人为中心的时尚服装制造技能和决策能力研究,以支持机器人设计工具的开发

Kat Thiel, S. Postlethwaite
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引用次数: 0

摘要

本文考察了将人为因素方法与时装设计实践研究相结合的研究结果,以确定英国缝纫机械师的现有技能水平,评估将机器人工具集成到小批量高价值时装设计工作流程中的兴趣,以帮助提高英国中小企业时装制造业的技能和在岸议程。尽管其创意设计在国际上享有盛誉,并为英国经济贡献了323亿英镑(牛津经济研究院,2018年),但英国时尚产业的自动化水平远低于其他行业。在可能进入制造业的年轻人中,对制造业缺乏兴趣,对现代奴隶制的焦虑,恶劣的工作条件,就业市场的不稳定,低水平的工资和培训正在加剧这种情况。将自动化、机器人技术和工程技术整合到一个高度创造性的英国时尚行业中,在微型生产过程中需要非常高水平的敏捷性,这些挑战可以通过人为因素和设计主导研究的联合研究来解决。该项目探讨了服装制造业的技能水平,为研究新工具的步骤提供信息,以确定可以由机器人完成的任务,或需要由熟练的人类制造商完成的任务——重要的是确定通过新技术和自动化提高工人满意度的要求。研究表明,缝纫技师对工作成就感和个人奖励的需求较高。目前,英国时装制造业缺乏支持可转移技能应用的系统,以振兴就业市场,提供机会,激励和吸引年轻劳动力进入这个可能充满活力的领域。在一项混合方法的研究中,研究人员使用问卷调查、桌面研究、眼球追踪和心率监测来证明缝纫师的认知决策和隐性/触觉知识。问卷调查和眼球追踪试验的参与者强调,奖励感是缝纫项目中成就感的主要驱动因素之一。因此,在创造性奖励活动的背景下调查新工具的开发是具有人为因素的设计研究的关键下一步。这项研究提出了如何在英国日益增长的技能短缺中提高社会科学和时装设计研究之间的协作能力,以创新制造过程的观点。这项严格限制范围的研究是展示这一研究领域价值的理想方式,作为未来更大规模合作工作的平台,重点是与微型和中小型服装设计和机器人企业共同研究,需要设计什么样的小型工具来实现新形式的陆上生产,自然导致新的设计美学。这些协作机器人系统可以支持制造排序的决策。交互式机器人已经有了在台式机上移动的潜力,也有了自我组装的潜力——这些概念可以帮助解决服装制造业的进一步发展目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human-centric research of skills and decision-making capacity in fashion garment manufacturing to support robotic design tool development
This paper examines the findings of research combining Human Factors methods with Fashion Design Practice Research to identify existing skills levels of UK sewing machinists, assessing the interest in integrating robotic tooling into low-volume high-value fashion design workflows to help an upskilling and onshoring agenda for UK SME fashion manufacturing. Despite its international reputation for creative design and contributing £32.3 billion to the UK economy (Oxford Economics, 2018), the UK’s fashion industry's levels of automation are much lower than other sectors. Amongst young people who might enter the industry a lack of interest in manufacturing, anxieties about modern-day slavery, poor working conditions, precarity in the jobs market, low levels of pay and training are exacerbating the situation. The challenges of integrating automation, robotics and engineering into a highly creative UK fashion sector with a need for very high levels of agility in micro-production processes can be addressed through joint research from Human Factors and design-led research. This project explored skills levels in garment manufacturing, to inform the steps in research of new tooling concerned with identifying tasks that can be performed by robots, or those needing to remain performed by skilled human makers - importantly identifying requirements for promoting worker satisfaction via new technology and automation. The research evidences sewing machinists’ need for better work fulfilment and personal reward. Currently, the UK fashion manufacturing sector lacks systems that support the application of transferable skills to rejuvenate the jobs market with opportunities that can inspire and entice a young workforce to enter what could be a dynamic field. In a mixed methods study, researchers used questionnaires, desk research, eye-tracking and heart-rate monitoring to evidence cognitive decision-making and tacit/tactile knowledge of sewing machinists. Participants of the questionnaire and eye-tracking trials stressed a sense of reward as one of the main drivers for fulfilment during a sewing project. Investigating the development of new tooling in the context of creatively rewarding activity is therefore a critical next step in design research with Human Factors. This study has delivered perspectives on ways to increase collaboration capability between social science and fashion design research to innovate within manufacturing processes amidst a growing skills shortage in the UK. This tightly limited scope study has been an ideal way of demonstrating the value in this area of research as a platform for a larger collaborative piece of work in the future with a focus on co-investigating, with micro and SME fashion design and robotics businesses, what kind of small-scale tools might need to be designed to enable new forms of on-shored production, leading naturally to a new design aesthetic. These cobot systems could support decision-making for fabrication sequencing. There is already potential for interactive robots to be mobile on desktops as well as self-assembling swarms - concepts that can help to address further development aims for garment manufacturing.
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