GOALI: Intelligent Decomposition Heuristics for Scheduling Semiconductor Manufacturing Facilities

GOALI：用于调度半导体制造设施的智能分解启发式方法

• 批准号: 9613708
• 负责人: Reha Uzsoy
• 金额: $ 29.95万
• 依托单位: Purdue Research Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-07-01 至 2001-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9613708&HistoricalAwards=false
• 关键词: GOALI; Intelligent; Decomposition; Heuristics; Scheduling

9613708 Uzsoy This GOALI award represents a combined industry-university research effort geared toward the development of optimization-based approximate scheduling procedures for complex manufacturing operations. While optimization-based scheduling approaches for complex manufacturing systems are not new, they have found relatively little use in practice, primarily because they have focused on exact solutions to computationally intractable problems. This research takes a different tack, employing a combination of heuristic decomposition methods and machine learning to develop effective approximate scheduling procedures for a general class of job-shops that encompass sequence dependent setup times, batching, and pipelining. The investigators include a senior researcher from Intel Corporation, and they will use semiconductor wafer fabrication facilities and assembly and test facilities as the testbeds for their research. The complexity of semiconductor manufacturing and the competitive pressures faced by the industry have made effective manufacturing management, in particular shop-floor control, essential to a company's survival. An important part of shop floor control is scheduling the movement of material through the equipment in the factory to obtain the best possible system performance. If successful, this work has the potential to reduce variability in lead times, thus allowing a company the ability to maintain lower floor inventories, respond rapidly to changing market conditions, and quote accurate and competitive lead times to their customers. The strong intellectual involvement of an industrial partner in this research will further ensure its relevance to practical manufacturing environments.

9613708 Uzsoy这个GOALI奖代表了一个联合的行业和大学的研究工作，面向复杂的制造业务的优化为基础的近似调度程序的发展。 虽然复杂制造系统的基于优化的调度方法并不新鲜，但它们在实践中的应用相对较少，主要是因为它们专注于计算棘手问题的精确解决方案。 本研究采取了不同的策略，采用启发式分解方法和机器学习相结合，开发有效的近似调度程序的一般类的作业车间，包括序列相关的设置时间，排序，流水线。 研究人员包括英特尔公司的一名高级研究员，他们将使用半导体晶圆制造设施和组装和测试设施作为他们研究的试验台。 半导体制造的复杂性和行业面临的竞争压力使得有效的制造管理，特别是车间控制，对公司的生存至关重要。 车间控制的一个重要组成部分是调度物料在工厂设备中的移动，以获得最佳的系统性能。 如果成功，这项工作有可能减少交货时间的变化，从而使公司能够保持较低的库存，快速响应不断变化的市场条件，并向客户提供准确和有竞争力的交货时间。 工业合作伙伴在这项研究中的强大智力参与将进一步确保其与实际制造环境的相关性。