确定近期到长期的研究机会,推进智能和可持续制造的指标、模型和方法。

IF 0.8 Q4 ENGINEERING, MANUFACTURING
Arvind Shankar Raman, Karl R Haapala, Kamyar Raoufi, Barbara S Linke, William Z Bernstein, K C Morris
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引用次数: 0

摘要

在过去的一个世纪里,研究的重点是不断提高制造工艺和系统的性能--通常以成本、质量、生产率以及材料和能源效率来衡量。随着智能制造技术的出现--更好的生产设备、传感技术、计算方法以及从工艺到企业层面的数据分析技术的应用--提高可持续发展绩效的潜力是巨大的。可持续生产寻求各种绩效衡量标准之间的最佳平衡,以满足和优化所有利益相关者的目标。准确的绩效衡量标准是实现可持续发展目标的基础。从历史上看,操作技术和信息技术经历了不同的发展,很少有跨领域的融合。为了让先进制造领域的未来研究工作有所侧重,作者在美国机械工程师学会和制造工程师学会的联合制造研究会议上组织了一次为期一天的研讨会,由美国国家科学基金会赞助。会议确定了研究需求,以帮助协调来自传统制造、纳米制造和增材制造/混合制造流程和系统的不同制造指标、模型和方法。来自学术界和政府实验室的专家应邀发表了闪电演讲,讨论了他们对当前先进制造研究挑战的看法。研讨会与会者还在头脑风暴分组讨论和反思活动中提出了自己的观点。研讨会的目的是确定先进制造研究和教育需求,以便通过改进可持续发展指标、建模方法和决策支持方法来提高制造工艺性能。除了这些研讨会成果之外,还对近期文献进行了回顾,确定了多个先进制造领域的研究机会。对未来研究的建议描述了先进制造领域在实现智能和可持续制造方面的短期、中期和长期需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Defining Near-Term to Long-Term Research Opportunities to Advance Metrics, Models, and Methods for Smart and Sustainable Manufacturing.

Over the past century, research has focused on continuously improving the performance of manufacturing processes and systems-often measured in terms of cost, quality, productivity, and material and energy efficiency. With the advent of smart manufacturing technologies-better production equipment, sensing technologies, computational methods, and data analytics applied from the process to enterprise levels-the potential for sustainability performance improvement is tremendous. Sustainable manufacturing seeks the best balance of a variety of performance measures to satisfy and optimize the goals of all stakeholders. Accurate measures of performance are the foundation on which sustainability objectives can be pursued. Historically, operational and information technologies have undergone disparate development, with little convergence across the domains. To focus future research efforts in advanced manufacturing, the authors organized a one-day workshop, sponsored by the U.S. National Science Foundation, at the joint manufacturing research conferences of the American Society of Mechanical Engineers and Society of Manufacturing Engineers. Research needs were identified to help harmonize disparate manufacturing metrics, models, and methods from across conventional manufacturing, nanomanufacturing, and additive/hybrid manufacturing processes and systems. Experts from academia and government labs presented invited lightning talks to discuss their perspectives on current advanced manufacturing research challenges. Workshop participants also provided their perspectives in facilitated brainstorming breakouts and a reflection activity. The aim was to define advanced manufacturing research and educational needs for improving manufacturing process performance through improved sustainability metrics, modeling approaches, and decision support methods. In addition to these workshop outcomes, a review of the recent literature is presented, which identifies research opportunities across several advanced manufacturing domains. Recommendations for future research describe the short-, mid-, and long-term needs of the advanced manufacturing community for enabling smart and sustainable manufacturing.

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来源期刊
Smart and Sustainable Manufacturing Systems
Smart and Sustainable Manufacturing Systems ENGINEERING, MANUFACTURING-
CiteScore
2.50
自引率
0.00%
发文量
17
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