Courses tagged with "Information needs" (40)

ESD.864 Modeling and Assessment for Policy explores how scientific information and quantitative models can be used to inform policy decision-making. Students will develop an understanding of quantitative modeling techniques and their role in the policy process through case studies and interactive activities. The course addresses issues such as analysis of scientific assessment processes, uses of integrated assessment models, public perception of quantitative information, methods for dealing with uncertainties, and design choices in building policy-relevant models. Examples used in this class focus on models and information used in earth system governance.

ESD.864 Modeling and Assessment for Policy explores how scientific information and quantitative models can be used to inform policy decision-making. Students will develop an understanding of quantitative modeling techniques and their role in the policy process through case studies and interactive activities. The course addresses issues such as analysis of scientific assessment processes, uses of integrated assessment models, public perception of quantitative information, methods for dealing with uncertainties, and design choices in building policy-relevant models. Examples used in this class focus on models and information used in earth system governance.

In this class, students use data and systems knowledge to build models of complex socio-technical systems for improved system design and decision-making. Students will enhance their model-building skills, through review and extension of functions of random variables, Poisson processes, and Markov processes; move from applied probability to statistics via Chi-squared t and f tests, derived as functions of random variables; and review classical statistics, hypothesis tests, regression, correlation and causation, simple data mining techniques, and Bayesian vs. classical statistics. A class project is required.

There is need for a rigorous, quantitative multidisciplinary design methodology that works with the non-quantitative and creative side of the design process in engineering systems. The goal of multidisciplinary systems design optimization is to create advanced and complex engineering systems that must be competitive not only in terms of performance, but also in terms of life-cycle value. The objective of the course is to present tools and methodologies for performing system optimization in a multidisciplinary design context. Focus will be equally strong on all three aspects of the problem: (i) the multidisciplinary character of engineering systems, (ii) design of these complex systems, and (iii) tools for optimization.

This course provides a deep understanding of engineering systems at a level intended for research on complex engineering systems. It provides a review and extension of what is known about system architecture and complexity from a theoretical point of view while examining the origins of and recent developments in the field. The class considers how and where the theory has been applied, and uses key analytical methods proposed. Students examine the level of observational (qualitative and quantitative) understanding necessary for successful use of the theoretical framework for a specific engineering system. Case studies apply the theory and principles to engineering systems.

This seminar applies a systems perspective to understand health care delivery today, its stakeholders and problems as well as opportunities. Students are introduced to the 'systems perspective' that has been used successfully in other industries, and will address the introduction of new processes, technologies and strategies to improve overall health outcomes. Students are assigned to teams to work on a semester‐long group project, in collaboration with staff of a nearby Boston hospital.

This subject presents a range of advanced topics in integrated logistics and supply chain management. The course was conducted in a lecture-discussion format, with participation of corporate executives as guest lecturers. Students prepare industry assessment analyses and make formal classroom presentations. Specific topics alternate from year to year, but basic content includes procurement strategies and strategic sourcing, dynamic pricing and revenue management tactics, mitigation of supply chain risk through supply contracts, strategic outsourcing of supply chain functions and operations, management and operation of third party logistics providers, and management of supply chain security.

The course is designed for students in the System Design and Management (SDM) program and therefore assumes that you already have a basic knowledge of project management. The objective is to introduce advanced methods and tools of project management in a realistic context such that they can be taken back to the workplace to improve management of development projects. In contrast to traditional courses on the subject we will emphasize scenarios that cannot be fully predicted such as task iterations, unplanned rework, perceived versus actual progress and misalignments between tasks, product architectures and organizations.

This class was also offered in Course 13 (Department of Ocean Engineering) as 13.615J. In 2005, ocean engineering subjects became part of Course 2 (Department of Mechanical Engineering), and the 13.470J designation was retired.

This course covers principles and methods for technical System Architecture. It presents a synthetic view including: the resolution of ambiguity to identify system goals and boundaries; the creative process of mapping form to function; and the analysis of complexity and methods of decomposition and re-integration. Industrial speakers and faculty present examples from various industries. Heuristic and formal methods are presented. Restricted to SDM (System Design and Management) students.

Subject focuses on management principles, methods, and tools to effectively plan and implement successful system and product development projects. Material is divided into four major sections: project preparation, planning, monitoring, and adaptation. Brief review of classical techniques such as CPM and PERT. Emphasis on new methodologies and tools such as Design Structure Matrix (DSM), probabilistic project simulation, as well as project system dynamics (SD). Topics are covered from strategic, tactical, and operational perspectives. Industrial case studies expose factors that are typical drivers of success and failure in complex projects with both hardware and software content. Term projects analyze and evaluate past and ongoing projects in student's area of interest. Projects used to apply concepts discussed in class.

Systems Engineering is an interdisciplinary approach and means to enable the realization of successful systems. It focuses on defining customer needs and required functionality early in the development cycle, documenting requirements, then proceeding with design synthesis and system validation while considering the complete problem including operations, performance, test, manufacturing, cost, and schedule. This subject emphasizes the links of systems engineering to fundamentals of decision theory, statistics, and optimization. It also introduces the most current, commercially successful techniques for systems engineering.