未来生产系统的人体工程学设计

C. Schlick, J. Bützler
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引用次数: 1

摘要

日益激烈的全球竞争和由此产生的成本压力要求高质量的产品和高效的制造工艺。此外,面对短的产品生命周期和客户对多样性的需求,市场需要灵活适应不断变化的条件。为了保持竞争力,对于高工资国家的公司来说,预测客户的具体需求、个性化流程和极其灵活的反应是至关重要的。因此,需要创新的生产系统,能够不断适应不断变化的产品结构和相应的生产和装配过程[1]。实现更高程度适应性的一种方法是设计灵活的自动化生产系统。从而提高竞争优势,使制造商能够动态分配功能,使人机交互更有效。“高工资国家综合生产技术”卓越集群以这种方法为重点,通过结合生产工程、材料科学和人为因素等领域的专业知识,将关键技术纳入其中,提供基于科学的解决方案。其目的是发展可持续生产战略的基础,并建立方法和模型,帮助我们理解、预测和控制复杂的社会技术生产系统的行为。但是,特别是在高工资国家,复杂的社会技术生产系统的自动化水平已经达到了这样的程度,根据某种“收益递减规律”,进一步提高将不会导致生产力的显著提高。因此,自动化大大减少了过程错误的数量,但是单个错误的潜在后果的严重程度不成比例地增加了。因此,在计划、监控和优化复杂生产过程时,人类的决策和行动在未来也将至关重要。事实上,未来生产系统的技术复杂性日益增加,往往需要加强人为干预,特别是在加速、监督控制和重新配置方面。因此,未来的生产系统应侧重于整合人类操作员及其非凡的解决问题的能力、创造力和感觉运动技能。这期关于未来生产系统的人体工程学设计的特刊包含了2014年7月在波兰Kraków举行的第五届应用人因与人体工程学国际会议(AHFE)特别会议期间的五篇精选文章。该特刊侧重于设计未来生产系统的创新方法,并为读者提供了该领域最近工作的简明概述。Kuz, b tzler和Schlick分析了自优化装配系统中龙门机器人运动行为中的拟人化如何影响放置任务中目标位置的可预测性的研究问题。为了调查这个问题,他们开发了一个由机器人装配单元组成的模拟,并用于进行实验室研究。虚拟龙门机器人是
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ergonomic Design of Future Production Systems
Increasing global competition and the resulting cost pressures call for premium-quality products and highly effective manufacturing processes. Moreover, in the face of short product life cycles and customers’ demand for variety, markets demand flexible adaptation to changing conditions. In order to stay competitive, it is crucial for companies in high-wage countries to anticipate customer-specific needs, individualize their processes and react extremely flexibly. Therefore, innovative production systems are required that are able to adapt continuously to changing product structures and the corresponding production and assembly processes [1]. One approach to achieving a higher degree of adaptability is to design flexible automated production systems. The competitive advantage is thus improved, giving manufacturers the ability to allocate functions dynamically and to make human-machine interaction more effective. The Cluster of Excellence “Integrative Production Technology for High-Wage Countries” focuses on this approach and incorporates key technologies by combining expertise from the fields of production engineering, material sciences and human factors to provide science-based solutions. The aim is to develop the fundamentals of a sustainable production strategy as well as to build methods and models that help us understand, predict and control the behaviour of complex, socio-technical production systems [1]. However, especially in high-wage countries, the level of automation in complex, socio-technical production systems has already been taken so far that, according to some kind of “law of diminishing returns”, a further increase will not lead to a significant increase in productivity. As a result, the number of process errors is significantly reduced by automation but the severity of the potential consequences of a single error increases disproportionately. Therefore, human decisions and actions when planning, monitoring, and optimizing complex production processes will also be crucial in the future [2]. In fact, increasing technological complexity in future production systems will often require intensified human intervention, especially for ramp-up, supervisory control and reconfiguration. Hence, future production systems should focus on integrating the human operator and his or her extraordinary problem-solving abilities, creativity, and sensorimotor skills. This special issue on the ergonomic design of future production systems contains five selected contributions that were part of a special session during the 5th International Conference on Applied Human Factors and Ergonomics (AHFE) held in July 2014 in Kraków, Poland. The special issue focuses on innovative methods for designing future production systems and gives the reader a concise overview of recent work in the field. Kuz, Bützler and Schlick have analysed the research question of how anthropomorphism in the motion behaviour of a gantry robot in self-optimizing assembly systems affects the predictability of target positions during placement tasks. To investigate this question, they developed a simulation consisting of a robotized assembly cell, which they used to conduct a laboratory study. The virtual gantry robot was
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