University - Industry Cooperative Research Programs in the Mathematical Sciences- Graduate Research Assistantships in Industrial Mathematics

工业数学的研究生研究助理被安置在江森自控公司（JCI）和Penta科技公司。这些合作加强了马奎特大学在工业数学教师研究、工业伙伴关系和研究培训方面的教育和研究任务，并为JCI和Penta提供关键业务的工业数学解决方案。在JCI，一家汽车座椅、电池和HVAC控制的制造商，学生将研究企业的混沌理论模型和企业敏捷性的措施，并使用真实数据进行验证，并将探索范围/目标系统分析。我们将开发简单的数学模型和商业游戏模拟问题，然后使用传统的运筹学工具，如计量经济模型和计算机模拟。JCI在企业的生物和生态范例方面的工作得到了马凯特大学的技术专长和资源的补充和丰富。在Penta（工程和建筑行业的商业解决方案提供商），该学生将使用数学建模和非线性全局优化技术开发软件分发系统，旨在为实时更新的交付提供最大的灵活性。Penta正在积极探索在线软件分发和产品更新系统，以便及时向客户交付软件。SDS的审查、设计、开发和实现将与针对客户站点异构环境的SDS优化的数学分析相结合。我们将确定对SDS准时交付造成最大限制的组件。这些数据将包括负载平衡、互联网传输速率、实时计算时间和人类交互延迟。这些数据将用于开发优化模型，以解决系统中最关键的瓶颈。该目标项目由MPS多学科活动办公室（OMA）和数学科学司（DMS）共同支持。

Graduate research assistants in industrial mathematics are placed at Johnson Controls, Inc. (JCI), and at Penta Technologies. These collaborations strengthen the Marquette's educational and research missions in faculty research in industrial mathematics, industrial partnerships, and research training, and deliver business-critical industrial mathematics solutions to JCI and Penta. At JCI, a manufacturer of automotive seats and batteries and HVAC controls, the student will investigate chaos theory models of the enterprise and measures of enterprise agility with validation using real data and will explore scoping/targeting systems analysis. We will develop simple mathematical models and business gaming simulations of the problem and then use traditional operations research tools such as econometric models and computer simulations. JCI's work on biological and ecological paradigms of the enterprise are complemented and enriched by the technical expertise and resources of Marquette University. At Penta, a business solutions provider for the engineering and construction industry, the student will use mathematical modeling and nonlinear global optimization techniques to develop a software distribution system aimed at providing maximum flexibility in the delivery of real-time updates. Penta is actively exploring on-line software distribution and product update systems to deliver software to clients in a timely manner. The review, design, development, and implementation of the SDS will be coupled with a mathematical analysis of SDS optimization for a heterogeneous environment of customer sites. We will determine components causing the greatest constraints to SDS on-time delivery. The data will include load-balancing, internet transport rates, real-time computational time, and human-interaction delays. This data will be used to develop an optimization model that will be solved to address the most critical bottlenecks in the system. This GOALI project is jo intly supported by the MPS Office of Multidisciplinary Activities (OMA) and the Division of Mathematical Sciences (DMS).