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15.761 Operations Management (MIT) 15.761 Operations Management (MIT)

Description

This course will introduce concepts and techniques for design, planning and control of manufacturing and service operations. The course provides basic definitions of operations management terms, tools and techniques for analyzing operations, and strategic context for making operational decisions. We present the material in five modules: Operations Analysis Coordination and Planning Quality Management Project Management Logistics and Supply Chain Management This course will introduce concepts and techniques for design, planning and control of manufacturing and service operations. The course provides basic definitions of operations management terms, tools and techniques for analyzing operations, and strategic context for making operational decisions. We present the material in five modules: Operations Analysis Coordination and Planning Quality Management Project Management Logistics and Supply Chain ManagementSubjects

manufacturing | manufacturing | service | service | analyzing operations | analyzing operations | operational decisions | operational decisions | operations analysis | operations analysis | quality management | quality management | project management | project management | logistics | logistics | supply chain management | supply chain management | job shop operations | job shop operations | process matching | process matching | queuing | queuing | forecasting | forecasting | queueing | queueing | analysis | analysis | analyzing | analyzing | operations | operations | coordination | coordination | planning | planning | quality | quality | project | project | management | management | supply chain | supply chain | job shop | job shop | decisions | decisions | decision making | decision making | operational | operational | design | design | control | control | materials | materials | production | production | scheduling | scheduling | reengineering | reengineering | capacity | capacity | facilities | facilities | strategy | strategy | process | process | processes | processes | matching | matching | inventory | inventory | vendor | vendor | customer | customerLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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15.768 Management of Services: Concepts, Design, and Delivery explores the use of operations tools and perspectives in the service sector, including both for-profit and not-for-profit organizations. The course builds on conceptual frameworks and cases from a wide range of service operations, selected from health care, hospitality, internet services, supply chain, transportation, retailing, food service, entertainment, financial services, humanitarian services, government services, and others. 15.768 Management of Services: Concepts, Design, and Delivery explores the use of operations tools and perspectives in the service sector, including both for-profit and not-for-profit organizations. The course builds on conceptual frameworks and cases from a wide range of service operations, selected from health care, hospitality, internet services, supply chain, transportation, retailing, food service, entertainment, financial services, humanitarian services, government services, and others.Subjects

operations management | operations management | service sector | service sector | case studies | case studies | operations strategy | operations strategy | process design | process design | service models | service models | operations frameworks | operations frameworks | retailing | retailing | data mining | data mining | disruptive models | disruptive models | supply chain | supply chain | organizational change | organizational changeLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace informationSubjects

autonomy | autonomy | decision | decision | decision-making | decision-making | reasoning | reasoning | optimization | optimization | autonomous | autonomous | autonomous systems | autonomous systems | decision support | decision support | algorithms | algorithms | artificial intelligence | artificial intelligence | a.i. | a.i. | operations | operations | operations research | operations research | logic | logic | deduction | deduction | heuristic search | heuristic search | constraint-based search | constraint-based search | model-based reasoning | model-based reasoning | planning | planning | execution | execution | uncertainty | uncertainty | machine learning | machine learning | linear programming | linear programming | dynamic programming | dynamic programming | integer programming | integer programming | network optimization | network optimization | decision analysis | decision analysis | decision theoretic planning | decision theoretic planning | Markov decision process | Markov decision process | scheme | scheme | propositional logic | propositional logic | constraints | constraints | Markov processes | Markov processes | computational performance | computational performance | satisfaction | satisfaction | learning algorithms | learning algorithms | system state | system state | state | state | search treees | search treees | plan spaces | plan spaces | model theory | model theory | decision trees | decision trees | function approximators | function approximators | optimization algorithms | optimization algorithms | limitations | limitations | tradeoffs | tradeoffs | search and reasoning | search and reasoning | game tree search | game tree search | local stochastic search | local stochastic search | stochastic | stochastic | genetic algorithms | genetic algorithms | constraint satisfaction | constraint satisfaction | propositional inference | propositional inference | rule-based systems | rule-based systems | rule-based | rule-based | model-based diagnosis | model-based diagnosis | neural nets | neural nets | reinforcement learning | reinforcement learning | web-based | web-based | search trees | search treesLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata15.997 Advanced Corporate Risk Management (MIT) 15.997 Advanced Corporate Risk Management (MIT)

Description

This is a course on how corporations make use of the insights and tools of risk management. Most courses on derivatives, futures and options, and financial engineering are taught from the viewpoint of investment bankers and traders in the securities. This course is taught from the point of view of the manufacturing corporation, the utility, the software firm — any potential end-user of derivatives, but not the dealer. Among the topics we will discuss are how companies manage risk, instruments for hedging, liability management and organization, governance and control. This is a course on how corporations make use of the insights and tools of risk management. Most courses on derivatives, futures and options, and financial engineering are taught from the viewpoint of investment bankers and traders in the securities. This course is taught from the point of view of the manufacturing corporation, the utility, the software firm — any potential end-user of derivatives, but not the dealer. Among the topics we will discuss are how companies manage risk, instruments for hedging, liability management and organization, governance and control.Subjects

advanced corporate risk management | advanced corporate risk management | derivatives | futures and options | derivatives | futures and options | financial engineering | financial engineering | corporations | corporations | risk management | risk management | pricing models | pricing models | operations | operations | real assets | real assets | core strategy | core strategy | trading operations | trading operations | contracts | contracts | hedging | hedging | corporate governance | corporate governance | shareholders | shareholders | valuation | valuation | liability management | liability managementLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.050J Information and Entropy (MIT) 6.050J Information and Entropy (MIT)

Description

6.050J / 2.110J presents the unified theory of information with applications to computing, communications, thermodynamics, and other sciences. It covers digital signals and streams, codes, compression, noise, and probability, reversible and irreversible operations, information in biological systems, channel capacity, maximum-entropy formalism, thermodynamic equilibrium, temperature, the Second Law of Thermodynamics, and quantum computation. Designed for MIT freshmen as an elective, this course has been jointly developed by MIT's Departments of Electrical Engineering and Computer Science and Mechanical Engineering. There is no known course similar to 6.050J / 2.110J offered at any other university.  6.050J / 2.110J presents the unified theory of information with applications to computing, communications, thermodynamics, and other sciences. It covers digital signals and streams, codes, compression, noise, and probability, reversible and irreversible operations, information in biological systems, channel capacity, maximum-entropy formalism, thermodynamic equilibrium, temperature, the Second Law of Thermodynamics, and quantum computation. Designed for MIT freshmen as an elective, this course has been jointly developed by MIT's Departments of Electrical Engineering and Computer Science and Mechanical Engineering. There is no known course similar to 6.050J / 2.110J offered at any other university. Subjects

information and entropy | information and entropy | computing | computing | communications | communications | thermodynamics | thermodynamics | digital signals and streams | digital signals and streams | codes | codes | compression | compression | noise | noise | probability | probability | reversible operations | reversible operations | irreversible operations | irreversible operations | information in biological systems | information in biological systems | channel capacity | channel capacity | aximum-entropy formalism | aximum-entropy formalism | thermodynamic equilibrium | thermodynamic equilibrium | temperature | temperature | second law of thermodynamics quantum computation | second law of thermodynamics quantum computation | maximum-entropy formalism | maximum-entropy formalism | second law of thermodynamics | second law of thermodynamics | quantum computation | quantum computation | biological systems | biological systems | unified theory of information | unified theory of information | digital signals | digital signals | digital streams | digital streams | bits | bits | errors | errors | processes | processes | inference | inference | maximum entropy | maximum entropy | physical systems | physical systems | energy | energy | quantum information | quantum information | 6.050 | 6.050 | 2.110 | 2.110License

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See all metadataESD.260J Logistics Systems (MIT) ESD.260J Logistics Systems (MIT)

Description

This course is a survey of analytic tools, approaches, and techniques which are useful in the design and operation of logistics systems and integrated supply chains. The material is taught from a managerial perspective, with an emphasis on where and how specific tools can be used to improve the overall performance and reduce the total cost of a supply chain. There is a strong emphasis on the development and use of fundamental models to illustrate the underlying concepts involved in both intra- and inter-company logistics operations. The following topics are covered: demand forecasting tools, inventory control algorithms, transportation operations and management, vehicle routing, scheduling, fleet dispatching algorithms and approaches, optimization of transportation carrier operations, supp This course is a survey of analytic tools, approaches, and techniques which are useful in the design and operation of logistics systems and integrated supply chains. The material is taught from a managerial perspective, with an emphasis on where and how specific tools can be used to improve the overall performance and reduce the total cost of a supply chain. There is a strong emphasis on the development and use of fundamental models to illustrate the underlying concepts involved in both intra- and inter-company logistics operations. The following topics are covered: demand forecasting tools, inventory control algorithms, transportation operations and management, vehicle routing, scheduling, fleet dispatching algorithms and approaches, optimization of transportation carrier operations, suppSubjects

Logistics systems | Logistics systems | Supply chain management | Supply chain management | Demand planning | Demand planning | Procurement | Procurement | Inventory | Inventory | Transportation planning | Transportation planning | Reverse logistics | Reverse logistics | Flexible contracting | Flexible contracting | Postponement | Postponement | Portfolio management | Portfolio management | Dual sourcing | Dual sourcing | demand forecasting tools | demand forecasting tools | inventory control algorithms | inventory control algorithms | transportation operations | transportation operations | vehicle routing | vehicle routing | scheduling | scheduling | fleet dispatching algorithms | fleet dispatching algorithms | optimization | optimization | transportation carrier operations | transportation carrier operations | supply chain network design | supply chain network design | procurement | procurement | sourcing | sourcing | auctions | auctions | supply contracts | supply contracts | collaboration | collaboration | supply chain uncertainty | supply chain uncertainty | ESD.260 | ESD.260 | 1.260 | 1.260 | 15.770 | 15.770License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace informationSubjects

autonomy | autonomy | decision | decision | decision-making | decision-making | reasoning | reasoning | optimization | optimization | autonomous | autonomous | autonomous systems | autonomous systems | decision support | decision support | algorithms | algorithms | artificial intelligence | artificial intelligence | a.i. | a.i. | operations | operations | operations research | operations research | logic | logic | deduction | deduction | heuristic search | heuristic search | constraint-based search | constraint-based search | model-based reasoning | model-based reasoning | planning | planning | execution | execution | uncertainty | uncertainty | machine learning | machine learning | linear programming | linear programming | dynamic programming | dynamic programming | integer programming | integer programming | network optimization | network optimization | decision analysis | decision analysis | decision theoretic planning | decision theoretic planning | Markov decision process | Markov decision process | scheme | scheme | propositional logic | propositional logic | constraints | constraints | Markov processes | Markov processes | computational performance | computational performance | satisfaction | satisfaction | learning algorithms | learning algorithms | system state | system state | state | state | search treees | search treees | plan spaces | plan spaces | model theory | model theory | decision trees | decision trees | function approximators | function approximators | optimization algorithms | optimization algorithms | limitations | limitations | tradeoffs | tradeoffs | search and reasoning | search and reasoning | game tree search | game tree search | local stochastic search | local stochastic search | stochastic | stochastic | genetic algorithms | genetic algorithms | constraint satisfaction | constraint satisfaction | propositional inference | propositional inference | rule-based systems | rule-based systems | rule-based | rule-based | model-based diagnosis | model-based diagnosis | neural nets | neural nets | reinforcement learning | reinforcement learning | web-based | web-based | search trees | search treesLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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The class will cover mathematical techniques necessary for understanding of materials science and engineering topics such as energetics, materials structure and symmetry, materials response to applied fields, mechanics and physics of solids and soft materials. The class uses examples from 3.012 to introduce mathematical concepts and materials-related problem solving skills. Topics include linear algebra and orthonormal basis, eigenvalues and eigenvectors, quadratic forms, tensor operations, symmetry operations, calculus of several variables, introduction to complex analysis, ordinary and partial differential equations, theory of distributions, fourier analysis and random walks.Technical RequirementsMathematica® software is required to run the .nb files found on this course site. The class will cover mathematical techniques necessary for understanding of materials science and engineering topics such as energetics, materials structure and symmetry, materials response to applied fields, mechanics and physics of solids and soft materials. The class uses examples from 3.012 to introduce mathematical concepts and materials-related problem solving skills. Topics include linear algebra and orthonormal basis, eigenvalues and eigenvectors, quadratic forms, tensor operations, symmetry operations, calculus of several variables, introduction to complex analysis, ordinary and partial differential equations, theory of distributions, fourier analysis and random walks.Technical RequirementsMathematica® software is required to run the .nb files found on this course site.Subjects

energetics | energetics | materials structure and symmetry: applied fields | materials structure and symmetry: applied fields | mechanics and physics of solids and soft materials | mechanics and physics of solids and soft materials | linear algebra | linear algebra | orthonormal basis | orthonormal basis | eigenvalues | eigenvalues | eigenvectors | eigenvectors | quadratic forms | quadratic forms | tensor operations | tensor operations | symmetry operations | symmetry operations | calculus | calculus | complex analysis | complex analysis | differential equations | differential equations | theory of distributions | theory of distributions | fourier analysis | fourier analysis | random walks | random walks | mathematical technicques | mathematical technicques | materials science | materials science | materials engineering | materials engineering | materials structure | materials structure | symmetry | symmetry | applied fields | applied fields | materials response | materials response | solids mechanics | solids mechanics | solids physics | solids physics | soft materials | soft materials | multi-variable calculus | multi-variable calculus | ordinary differential equations | ordinary differential equations | partial differential equations | partial differential equations | applied mathematics | applied mathematics | mathematical techniques | mathematical techniquesLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.050J Information and Entropy (MIT) 6.050J Information and Entropy (MIT)

Description

Includes audio/video content: AV selected lectures. This course explores the ultimate limits to communication and computation, with an emphasis on the physical nature of information and information processing. Topics include: information and computation, digital signals, codes and compression, applications such as biological representations of information, logic circuits, computer architectures, and algorithmic information, noise, probability, error correction, reversible and irreversible operations, physics of computation, and quantum computation. The concept of entropy applied to channel capacity and to the second law of thermodynamics. Includes audio/video content: AV selected lectures. This course explores the ultimate limits to communication and computation, with an emphasis on the physical nature of information and information processing. Topics include: information and computation, digital signals, codes and compression, applications such as biological representations of information, logic circuits, computer architectures, and algorithmic information, noise, probability, error correction, reversible and irreversible operations, physics of computation, and quantum computation. The concept of entropy applied to channel capacity and to the second law of thermodynamics.Subjects

information and entropy | information and entropy | computing | computing | communications | communications | thermodynamics | thermodynamics | digital signals and streams | digital signals and streams | codes | codes | compression | compression | noise | noise | probability | probability | reversible operations | reversible operations | irreversible operations | irreversible operations | information in biological systems | information in biological systems | channel capacity | channel capacity | maximum-entropy formalism | maximum-entropy formalism | thermodynamic equilibrium | thermodynamic equilibrium | temperature | temperature | second law of thermodynamics quantum computation | second law of thermodynamics quantum computationLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata1.225J Transportation Flow Systems (MIT) 1.225J Transportation Flow Systems (MIT)

Description

Design, operation, and management of traffic flows over complex transportation networks are the foci of this course. It covers two major topics: traffic flow modeling and traffic flow operations. Sub-topics include deterministic and probabilistic models, elements of queuing theory, and traffic assignment. Concepts are illustrated through various applications and case studies. This is a half-term subject offered during the second half of the semester. Design, operation, and management of traffic flows over complex transportation networks are the foci of this course. It covers two major topics: traffic flow modeling and traffic flow operations. Sub-topics include deterministic and probabilistic models, elements of queuing theory, and traffic assignment. Concepts are illustrated through various applications and case studies. This is a half-term subject offered during the second half of the semester.Subjects

transportation | transportation | transportation flow systems | transportation flow systems | traffic | traffic | traffic flow | traffic flow | networks | networks | transportation networks | transportation networks | flow modeling | flow modeling | flow operations | flow operations | deteministic models | deteministic models | probabilistic models | probabilistic models | queuing theory | queuing theory | queues | queues | traffic assignment | traffic assignment | case studies | case studies | cumulative plots | cumulative plots | airport runway capacity | airport runway capacity | runway capacity | runway capacity | road traffic | road traffic | shortest paths | shortest paths | optimizations | optimizations | highway control | highway control | ramp metering | ramp metering | simulation models | simulation models | isolated signals | isolated signals | operations | operations | operational problems | operational problems | air traffic operation | air traffic operation | air | air | road | road | component | component | 1.225 | 1.225 | ESD.205 | ESD.205License

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This half-term course introduces students to problems and analysis related to the design, planning, control, and improvement of manufacturing and service operations. Class sessions involve explaining concepts, working examples, and discussing cases. A wide range of topics are covered, including: process analysis, quality management, supply chain design, procurement, and product development. Toward the end of the course, students work in teams to manage a virtual factory in a web-based simulation exercise. This half-term course introduces students to problems and analysis related to the design, planning, control, and improvement of manufacturing and service operations. Class sessions involve explaining concepts, working examples, and discussing cases. A wide range of topics are covered, including: process analysis, quality management, supply chain design, procurement, and product development. Toward the end of the course, students work in teams to manage a virtual factory in a web-based simulation exercise.Subjects

operations management | operations management | service operations | service operations | manufacturing design | manufacturing design | manufacturing planning | manufacturing planning | production control | production control | quality management | quality management | process design | process design | reengineering | reengineering | product development | product development | project management | project management | supply chain design | supply chain design | improving manufacturing processes | improving manufacturing processes | capacity | capacity | inventory | inventory | quality control | quality control | product design | product design | factory management | factory managementLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata15.764 The Theory of Operations Management (MIT) 15.764 The Theory of Operations Management (MIT)

Description

The doctoral seminar 15.764 focuses on theoretical work for studying operations planning and control problems. This term's special topic, "Customer-Driven Operations," considers how a number of companies have succeeded in focusing their operation systems on the customer. The class reviews the quantitative models and theoretical tools underlying some of the customer-driven operational practices of these cutting-edge companies. Students will read and present research papers on topics such as distribution systems, short life-cycle product management, and forecast evolution models. This MIT OpenCourseWare site is dedicated to the memory of Bhuwan Singh, a member of the class. The doctoral seminar 15.764 focuses on theoretical work for studying operations planning and control problems. This term's special topic, "Customer-Driven Operations," considers how a number of companies have succeeded in focusing their operation systems on the customer. The class reviews the quantitative models and theoretical tools underlying some of the customer-driven operational practices of these cutting-edge companies. Students will read and present research papers on topics such as distribution systems, short life-cycle product management, and forecast evolution models. This MIT OpenCourseWare site is dedicated to the memory of Bhuwan Singh, a member of the class.Subjects

operations management | operations management | customer-focused operation systems | customer-focused operation systems | customer focus | customer focus | direct-to-consumer business model | direct-to-consumer business model | life-cycle management | life-cycle management | customer-driven operations | customer-driven operations | operational practices | operational practices | distribution systems | distribution systems | customer choice models | customer choice models | assemble-to-order production systems | assemble-to-order production systems | customer service centers | customer service centers | forecast evolution models | forecast evolution models | warehouse systems | warehouse systems | inventory policies | inventory policies | procurement | procurement | managing customer relationships | managing customer relationships | consumer behavior | consumer behavior | short life-cycle production management | short life-cycle production managementLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata15.063 Communicating With Data (MIT) 15.063 Communicating With Data (MIT)

Description

Communicating With Data has a distinctive structure and content, combining fundamental quantitative techniques of using data to make informed management decisions with illustrations of how real decision makers, even highly trained professionals, fall prey to errors and biases in their understanding. We present the fundamental concepts underlying the quantitative techniques as a way of thinking, not just a way of calculating, in order to enhance decision-making skills. Rather than survey all of the techniques of management science, we stress those fundamental concepts and tools that we believe are most important for the practical analysis of management decisions, presenting the material as much as possible in the context of realistic business situations from a variety of settings. Exer Communicating With Data has a distinctive structure and content, combining fundamental quantitative techniques of using data to make informed management decisions with illustrations of how real decision makers, even highly trained professionals, fall prey to errors and biases in their understanding. We present the fundamental concepts underlying the quantitative techniques as a way of thinking, not just a way of calculating, in order to enhance decision-making skills. Rather than survey all of the techniques of management science, we stress those fundamental concepts and tools that we believe are most important for the practical analysis of management decisions, presenting the material as much as possible in the context of realistic business situations from a variety of settings. ExerSubjects

quantitative | quantitative | data analysis | data analysis | graphs | graphs | charts | charts | factual decisions | factual decisions | statistics | statistics | communication | communication | fact-based | fact-based | information analysis | information analysis | spreadsheets | spreadsheets | models | models | probability | probability | decision analysis | decision analysis | regression | regression | simulation | simulation | linear | linear | nonlinear | nonlinear | optimization | optimization | data | data | analysis | analysis | marketing | marketing | finance | finance | operations management | operations management | strategy | strategy | operations | operations | management | management | diagrams | diagrams | formula | formula | structure | structure | content | contentLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata15.761 Operations Management (MIT)

Description

This course will introduce concepts and techniques for design, planning and control of manufacturing and service operations. The course provides basic definitions of operations management terms, tools and techniques for analyzing operations, and strategic context for making operational decisions. We present the material in five modules: Operations Analysis Coordination and Planning Quality Management Project Management Logistics and Supply Chain ManagementSubjects

manufacturing | service | analyzing operations | operational decisions | operations analysis | quality management | project management | logistics | supply chain management | job shop operations | process matching | queuing | forecasting | queueing | analysis | analyzing | operations | coordination | planning | quality | project | management | supply chain | job shop | decisions | decision making | operational | design | control | materials | production | scheduling | reengineering | capacity | facilities | strategy | process | processes | matching | inventory | vendor | customerLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadataUnderstanding operations management

Description

Operations management is one of the central functions of all organisations whether producing goods or services, or in the private, public or voluntary sectors. This unit will provide you with a basic framework for understanding this function and discusses the role of operations managers, in particular the importance of focusing on suppliers and customers.Subjects

business and management | customers | management | marketing | operations | operations_manager | operations_system | suppliers | Education | X000License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/Site sourced from

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See all metadata15.768 Management of Services: Concepts, Design, and Delivery (MIT)

Description

15.768 Management of Services: Concepts, Design, and Delivery explores the use of operations tools and perspectives in the service sector, including both for-profit and not-for-profit organizations. The course builds on conceptual frameworks and cases from a wide range of service operations, selected from health care, hospitality, internet services, supply chain, transportation, retailing, food service, entertainment, financial services, humanitarian services, government services, and others.Subjects

operations management | service sector | case studies | operations strategy | process design | service models | operations frameworks | retailing | data mining | disruptive models | supply chain | organizational changeLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata18.100C Analysis I (MIT) 18.100C Analysis I (MIT)

Description

This course is meant as a first introduction to rigorous mathematics; understanding and writing of proofs will be emphasized. We will cover basic notions in real analysis: point-set topology, metric spaces, sequences and series, continuity, differentiability, and integration. This course is meant as a first introduction to rigorous mathematics; understanding and writing of proofs will be emphasized. We will cover basic notions in real analysis: point-set topology, metric spaces, sequences and series, continuity, differentiability, and integration.Subjects

analysis | analysis | sequences | sequences | series | series | continuity | continuity | differentiability | differentiability | Riemann | Riemann | uniformity | uniformity | limit operations | limit operations | proofs | proofs | point-set topology | point-set topology | n-space | n-space | communication | communication | writing | writingLicense

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See all metadata18.100A Analysis I (MIT) 18.100A Analysis I (MIT)

Description

Analysis I (18.100) in its various versions covers fundamentals of mathematical analysis: continuity, differentiability, some form of the Riemann integral, sequences and series of numbers and functions, uniform convergence with applications to interchange of limit operations, some point-set topology, including some work in Euclidean n-space. MIT students may choose to take one of three versions of 18.100: Option A (18.100A) chooses less abstract definitions and proofs, and gives applications where possible. Option B (18.100B) is more demanding and for students with more mathematical maturity; it places more emphasis from the beginning on point-set topology and n-space, whereas Option A is concerned primarily with analysis on the real line, saving for the last weeks work in 2-space (the pla Analysis I (18.100) in its various versions covers fundamentals of mathematical analysis: continuity, differentiability, some form of the Riemann integral, sequences and series of numbers and functions, uniform convergence with applications to interchange of limit operations, some point-set topology, including some work in Euclidean n-space. MIT students may choose to take one of three versions of 18.100: Option A (18.100A) chooses less abstract definitions and proofs, and gives applications where possible. Option B (18.100B) is more demanding and for students with more mathematical maturity; it places more emphasis from the beginning on point-set topology and n-space, whereas Option A is concerned primarily with analysis on the real line, saving for the last weeks work in 2-space (the plaSubjects

mathematical analysis | mathematical analysis | convergence of sequences | convergence of sequences | convergence of series | convergence of series | continuity | continuity | differentiability | differentiability | Riemann integral | Riemann integral | sequences and series of functions | sequences and series of functions | uniformity | uniformity | interchange of limit operations | interchange of limit operations | utility of abstract concepts | utility of abstract concepts | construction of proofs | construction of proofs | point-set topology | point-set topology | n-space | n-spaceLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata21A.350J The Anthropology of Computing (MIT) 21A.350J The Anthropology of Computing (MIT)

Description

This course examines computers anthropologically, as meaningful tools revealing the social and cultural orders that produce them. We read classic texts in computer science along with works analyzing links between machines and culture. We explore early computation theory and capitalist manufacturing; cybernetics and WWII operations research; artificial intelligence and gendered subjectivity; the creation and commodification of the personal computer; the hacking aesthetic; non-Western histories of computing; the growth of the Internet as a military, academic, and commercial project; the politics of identity in cyberspace; and the emergence of "evolutionary" computation. This course examines computers anthropologically, as meaningful tools revealing the social and cultural orders that produce them. We read classic texts in computer science along with works analyzing links between machines and culture. We explore early computation theory and capitalist manufacturing; cybernetics and WWII operations research; artificial intelligence and gendered subjectivity; the creation and commodification of the personal computer; the hacking aesthetic; non-Western histories of computing; the growth of the Internet as a military, academic, and commercial project; the politics of identity in cyberspace; and the emergence of "evolutionary" computation.Subjects

Computing | Computing | machines and culture | machines and culture | computation theory | computation theory | cybernetics | cybernetics | operations research | operations research | artifical intelligence | artifical intelligence | personal computer | personal computer | commodification | commodification | hacking | hacking | hacker | hacker | Internet | Internet | cyberspace | cyberspace | indentity in cyberspace | indentity in cyberspace | cosmology | cosmology | clockwork | clockwork | Charles Babbage | Charles Babbage | Ada Lovelace | Ada Lovelace | Industrial Revolution | Industrial Revolution | calculating machine | calculating machine | coding | coding | cold war | cold war | Alan Turing | Alan Turing | African mathematical systems | African mathematical systems | counterculture | counterculture | PC | PC | gaming | gaming | open source | open source | free software | free software | software | software | 21A.350 | 21A.350 | SP.484 | SP.484 | STS.086 | STS.086License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata18.100B Analysis I (MIT) 18.100B Analysis I (MIT)

Description

Analysis I covers fundamentals of mathematical analysis: convergence of sequences and series, continuity, differentiability, Riemann integral, sequences and series of functions, uniformity, and interchange of limit operations. Analysis I covers fundamentals of mathematical analysis: convergence of sequences and series, continuity, differentiability, Riemann integral, sequences and series of functions, uniformity, and interchange of limit operations.Subjects

mathematical analysis | mathematical analysis | convergence of sequences | convergence of sequences | convergence of series | convergence of series | continuity | continuity | differentiability | differentiability | Riemann integral | Riemann integral | sequences and series of functions | sequences and series of functions | uniformity | uniformity | interchange of limit operations | interchange of limit operations | utility of abstract concepts | utility of abstract concepts | construction of proofs | construction of proofs | point-set topology | point-set topology | n-space | n-spaceLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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The United States is spending about $400 billion this year on national defense, some $40 billion on homeland security, and $85 billion on military operations and nation-building in Iraq and Afghanistan. This course is for students who want to know how the dollars we spend on national security relate to military forces, systems, and policy choices, and who wish to develop a personal tool kit for framing and assessing defense policy alternatives. The course aims to familiarize students with budgetary concepts and processes; to examine relationships among strategy, forces, and budgets; to explore tradeoffs among the main categories of defense spending; and to develop frameworks for identifying the costs of new military policies. The course begins with an overview of U.S. spending for national The United States is spending about $400 billion this year on national defense, some $40 billion on homeland security, and $85 billion on military operations and nation-building in Iraq and Afghanistan. This course is for students who want to know how the dollars we spend on national security relate to military forces, systems, and policy choices, and who wish to develop a personal tool kit for framing and assessing defense policy alternatives. The course aims to familiarize students with budgetary concepts and processes; to examine relationships among strategy, forces, and budgets; to explore tradeoffs among the main categories of defense spending; and to develop frameworks for identifying the costs of new military policies. The course begins with an overview of U.S. spending for nationalSubjects

United States | United States | national defense | national defense | homeland security | homeland security | military operations | military operations | budget | budget | military forces | military forces | systems | systems | policy | policy | strategy | strategy | spending | spending | terrorism | terrorism | pay | pay | benefits | benefits | federal | federal | infrastructure | infrastructure | readiness | readiness | alternative | alternative | defense | defense | plans | plansLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata15.769 Operations Strategy (MIT) 15.769 Operations Strategy (MIT)

Description

The class provides a unifying framework for analyzing strategic issues in manufacturing and service operations. Relationships between manufacturing and service companies and their suppliers, customers, and competitors are analyzed. The material also covers decisions in technology, facilities, vertical integration, human resources and other strategic areas. Means of competition such as cost, quality, and innovativeness are explored, together with an approach to make operations decisions in the era of outsourcing and globalization. The class provides a unifying framework for analyzing strategic issues in manufacturing and service operations. Relationships between manufacturing and service companies and their suppliers, customers, and competitors are analyzed. The material also covers decisions in technology, facilities, vertical integration, human resources and other strategic areas. Means of competition such as cost, quality, and innovativeness are explored, together with an approach to make operations decisions in the era of outsourcing and globalization.Subjects

operations | operations | reengineering | reengineering | process design | process design | manufacturing | manufacturing | stragegy | stragegy | supply chain | supply chain | three dimensional concurrent engineering | three dimensional concurrent engineering | charles fine | charles fine | clockspeed | clockspeed | product development | product developmentLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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A proper understanding of modern military operations requires a prior understanding of both the material side of war, including especially weapon, sensor, communication, and information processing technologies, and the human or organizational side of war, including especially military doctrine, which is an institutionalized vision within military organizations that predicts how the material tools of war will be wielded on future battlefields. Military doctrine makes assumptions about the nature of future battlefields, and determines what the division of labor on those battlefields will be between different military tools. Doctrine also therefore determines the organizational hierarchy among the various branches of the military which wield those tools. Thus, one way to think of the relation A proper understanding of modern military operations requires a prior understanding of both the material side of war, including especially weapon, sensor, communication, and information processing technologies, and the human or organizational side of war, including especially military doctrine, which is an institutionalized vision within military organizations that predicts how the material tools of war will be wielded on future battlefields. Military doctrine makes assumptions about the nature of future battlefields, and determines what the division of labor on those battlefields will be between different military tools. Doctrine also therefore determines the organizational hierarchy among the various branches of the military which wield those tools. Thus, one way to think of the relationSubjects

Political science | Political science | military | military | modern | modern | operations | operations | material | material | war | war | weapon | weapon | sensor | sensor | communication | communication | information processing | information processing | technologies | technologies | human | human | organizational | organizational | doctrine | doctrine | future | future | battlefields | battlefields | organizational hierarchy | organizational hierarchy | branches. | branches. | branches | branchesLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata18.06 Linear Algebra (MIT) 18.06 Linear Algebra (MIT)

Description

This is a basic subject on matrix theory and linear algebra. Emphasis is given to topics that will be useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, similarity, and positive definite matrices. This is a basic subject on matrix theory and linear algebra. Emphasis is given to topics that will be useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, similarity, and positive definite matrices.Subjects

Generalized spaces | Generalized spaces | Linear algebra | Linear algebra | Algebra | Universal | Algebra | Universal | Mathematical analysis | Mathematical analysis | Calculus of operations | Calculus of operations | Line geometry | Line geometry | Topology | Topology | matrix theory | matrix theory | systems of equations | systems of equations | vector spaces | vector spaces | systems determinants | systems determinants | eigen values | eigen values | positive definite matrices | positive definite matrices | Markov processes | Markov processes | Fourier transforms | Fourier transforms | differential equations | differential equations | linear algebra | linear algebra | determinants | determinants | eigenvalues | eigenvalues | similarity | similarity | least-squares approximations | least-squares approximations | stability of differential equations | stability of differential equations | networks | networksLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata5.069 Crystal Structure Analysis (MIT) 5.069 Crystal Structure Analysis (MIT)

Description

This course covers the following topics: X-ray diffraction: symmetry, space groups, geometry of diffraction, structure factors, phase problem, direct methods, Patterson methods, electron density maps, structure refinement, how to grow good crystals, powder methods, limits of X-ray diffraction methods, and structure data bases. This course covers the following topics: X-ray diffraction: symmetry, space groups, geometry of diffraction, structure factors, phase problem, direct methods, Patterson methods, electron density maps, structure refinement, how to grow good crystals, powder methods, limits of X-ray diffraction methods, and structure data bases.Subjects

crystallography | crystallography | inorganic chemistry | inorganic chemistry | physical methods | physical methods | crystal structure determination | crystal structure determination | 3D structure | 3D structure | x-ray crystallagraphy | x-ray crystallagraphy | diffraction | diffraction | x-rays | x-rays | symmetry | symmetry | phasing | phasing | crystal structure | crystal structure | symmetry operations | symmetry operations | crystal lattice | crystal lattice | structure refinement | structure refinement | electron density maps | electron density maps | space group determination | space group determination | anomalous scattering | anomalous scatteringLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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