Online courses directory (19947)

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.

This course studies what makes a good design and how one develops a good design. Students consider how the design of engineered systems (such as hardware, software, materials, and manufacturing systems) differ from the "design" of natural systems such as biological systems; discuss complexity and how one makes use of complexity theory to improve design; and discover how one uses axiomatic design theory (AD theory) in design of many different kinds of engineered systems. Questions are analyzed using Axiomatic Design Theory and Complexity Theory. Case studies are presented including the design of machines, tribological systems, materials, manufacturing systems, and recent inventions. Implications of AD and complexity theories on biological systems discussed.

Logistics and supply chain structures can be found in virtually any system. In this business and management course you will learn not only what makes leading systems competitive but also how to design, or redesign, your own system.

The MOOC is based on a widely popular university course that will give you a working knowledge on supply chain strategy and design that can be applied in your organisation.

Course topics include:

• How to increase ROI (Return on Investment) using logistics
• Logistics trade-offs (service vs cost vs capital)
• The SCOR model for analysis of supply chains
• Sustainability in supply chains (the triple bottom line)
• The Bullwhip effect and how to beat it
• Strategies regarding:
  • Sourcing
  • Warehousing
  • Product range
  • Production
  • Distribution
  • Transportation
  • Etc.
• Concepts like:
  • Quick Response - QR
  • Efficient Consumer Response, ECR
  • Collaborative Planning, Forecasting and Replenishment, CPFR

Many of the topics in the course will be illustrated using real companies and real logistics professionals as logistics is not a theoretical subject – it exists all around us – everywhere.

By the end of this course, you will be able to better describe, understand and ultimately design your own system for your organisation based on existing knowledge in this exciting field.

Regardless of your industry or organisation type, the concepts and methods from this course will help you become a logistics and supply chain professional. You will never look at a hotel breakfast buffet, a loading bay, a warehouse, a factory, an emergency room or even at a fast food restaurant the same way again…

15.874 and 15.871 provide an introduction to system dynamics modeling for the analysis of business policy and strategy. Students learn to visualize a business organization in terms of the structures and policies that create dynamics and regulate performance. The course uses role playing games, simulation models, and management flight simulators to develop principles for the successful management of complex strategies. Special emphasis will be placed on case studies of successful strategies using system dynamics.

15.874 is a full semester course and 15.871 is a half semester course. The two classes meet together and cover the same material for the first half of the term. In the second half of the semester, only 15.874 continues.

Effective and meaningful engagement with complex modern medical systems requires an overarching set of tools.

System dynamics is such a tool, allowing health practitioners to model and simulate problems ranging from the molecular level to the entire healthcare system and beyond. This introductory course will teach you the fundamental principles of system dynamics as you learn how to use system dynamics software to explore problems relevant to your field of health. Whether you work in molecular biology, clinical medicine, health policy, or any other health-related field, this course will equip you to investigate the effects of time delays, feedback and system structure. You will learn how to interpret the causes of typical system behaviors such as growth, decay and oscillation in terms of the underlying system properties, and to rapidly develop computer-based models and run simulations to gain insight into the problems in your domain.

This course will empower you with a deeper understanding and an enhanced capacity to achieve useful interventions in healthcare.

Continuation of 15.871, emphasizing tools and methods needed to apply systems thinking and simulation modeling successfully in complex real-world settings. Uses simulation models, management flight simulators, and case studies to deepen the conceptual and modeling skills introduced in 15.871. Through models and case studies of successful applications students learn how to use qualitative and quantitative data to formulate and test models, and how to work effectively with senior executives to implement change successfully.

Many books and thousands of papers cover the field of system dynamics. With all of these resources available, it can be difficult to know where to begin. The System Dynamics in Education Project at MIT put together these resources to help people sort through the vast library of books and papers on system dynamics. This course site includes a collection of papers and computer exercises entitled “Road Maps,” as well as a collection of assignments and solutions that were initially part of a guided study to system dynamics.  Note that while the level of the course indicated in the upper right corner of the screen is "Undergraduate / Graduate," the material is suitable for people ranging from K-12 students to chief executives of corporations.

This course is offered to graduates and includes topics such as mathematical models of systems from observations of their behavior; time series, state-space, and input-output models; model structures, parametrization, and identifiability; non-parametric methods; prediction error methods for parameter estimation, convergence, consistency, and asymptotic distribution; relations to maximum likelihood estimation; recursive estimation; relation to Kalman filters; structure determination; order estimation; Akaike criterion; bounded but unknown noise model; and robustness and practical issues.

One objective of 15.066J is to introduce modeling, optimization and simulation, as it applies to the study and analysis of manufacturing systems for decision support. The introduction of optimization models and algorithms provide a framework to think about a wide range of issues that arise in manufacturing systems. The second objective is to expose students to a wide range of applications for these methods and models, and to integrate this material with their introduction to operations management.

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.

This course covers important concepts and techniques in designing and operating safety-critical systems. Topics include the nature of risk, formal accident and human error models, causes of accidents, fundamental concepts of system safety engineering, system and software hazard analysis, designing for safety, fault tolerance, safety issues in the design of human-machine interaction, verification of safety, creating a safety culture, and management of safety-critical projects. Includes a class project involving the high-level system design and analysis of a safety-critical system.

This course introduces the concepts of system safety and how to analyze and design safer systems. Topics include the causes of accidents in general, and recent major accidents in particular; hazard analysis, safety-driven design techniques; design of human-automation interaction; integrating safety into the system engineering process; and managing and operating safety-critical systems.

This course covers important concepts and techniques in designing and operating safety-critical systems. Topics include the nature of risk, formal accident and human error models, causes of accidents, fundamental concepts of system safety engineering, system and software hazard analysis, designing for safety, fault tolerance, safety issues in the design of human-machine interaction, verification of safety, creating a safety culture, and management of safety-critical projects. Includes a class project involving the high-level system design and analysis of a safety-critical system.

This course introduces the concepts of system safety and how to analyze and design safer systems. Topics include the causes of accidents in general, and recent major accidents in particular; hazard analysis, safety-driven design techniques; design of human-automation interaction; integrating safety into the system engineering process; and managing and operating safety-critical systems.

This course is about theory, techniques, and tools for rigorous development of computer systems.

Learn how to grow your business while you sleep, play or are on vacation by working smarter, not working harder.

This course provides an in-depth technical and policy analysis of various options for the nuclear fuel cycle. Topics include uranium supply, enrichment fuel fabrication, in-core physics and fuel management of uranium, thorium and other fuel types, reprocessing and waste disposal. Also covered are the principles of fuel cycle economics and the applied reactor physics of both contemporary and proposed thermal and fast reactors. Nonproliferation aspects, disposal of excess weapons plutonium, and transmutation of actinides and selected fission products in spent fuel are examined. Several state-of-the-art computer programs are provided for student use in problem sets and term papers.

This course provides an introduction to linear systems, transfer functions, and Laplace transforms. It covers stability and feedback, and provides basic design tools for specifications of transient response. It also briefly covers frequency-domain techniques.

 

This course provides an introduction to cellular and population-level systems biology with an emphasis on synthetic biology, modeling of genetic networks, cell-cell interactions, and evolutionary dynamics. Cellular systems include genetic switches and oscillators, network motifs, genetic network evolution, and cellular decision-making. Population-level systems include models of pattern formation, cell-cell communication, and evolutionary systems biology.

This course introduces the mathematical modeling techniques needed to address key questions in modern biology. An overview of modeling techniques in molecular biology and genetics, cell biology and developmental biology is covered. Key experiments that validate mathematical models are also discussed, as well as molecular, cellular, and developmental systems biology, bacterial chemotaxis, genetic oscillators, control theory and genetic networks, and gradient sensing systems. Additional specific topics include: constructing and modeling of genetic networks, lambda phage as a genetic switch, synthetic genetic switches, circadian rhythms, reaction diffusion equations, local activation and global inhibition models, center finding networks, general pattern formation models, modeling cell-cell communication, quorum sensing, and finally, models for Drosophila development.