Defining Near-Term to Long-Term Research Opportunities to Advance Metrics, Models, and Methods for Smart and Sustainable Manufacturing.

IF 0.8 Q4 ENGINEERING, MANUFACTURING Smart and Sustainable Manufacturing Systems Pub Date : 2020-02-21 DOI:10.1520/ssms20190047
A. Raman, Karl R. Haapala, Kamyar Raoufi, B. Linke, W. Bernstein, Katherine C. Morris
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引用次数: 7

Abstract

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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定义近期到长期的研究机会,以推进智能和可持续制造的指标、模型和方法。
在过去的一个世纪里,研究一直集中在不断改进制造过程和系统的性能上——通常用成本、质量、生产率、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、计算方法和从过程到企业层面应用的数据分析——可持续性绩效改善的潜力是巨大的。可持续制造寻求各种绩效指标的最佳平衡,以满足和优化所有利益相关者的目标。对业绩的准确衡量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,几乎没有跨领域的融合。为了将未来的研究重点放在先进制造上,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个为期一天的研讨会,由美国国家科学基金会赞助。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/混合制造工艺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进行了闪电演讲,讨论了他们对当前先进制造研究挑战的看法。讲习班参与者还在促进头脑风暴和反思活动中提供了他们的观点。其目的是通过改进可持续性指标、建模方法和决策支持方法来定义先进的制造研究和教育需求,以改善制造过程的性能。除了这些研讨会成果之外,还介绍了最近的文献综述,其中确定了几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业社区实现智能和可持续制造的短期、中期和长期需求。
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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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