IEMS-382 : Production Planning and Scheduling
This course focuses on applications of operations research methods to practical problems of operations engineering and management. Topics include operations strategy, process-flow measures of operations, capacity management, throughput improvement, impact of variability on operations, demand forecasting, analysis of flow time and corresponding improvement strategies, aggregate production planning and scheduling deterministic and stochastic inventory control models, MRP and ERP, lean operations and improving inventory and supply chain performance.
TEACHING
IEMS-383 : Service Operations Management
The service industry accounts for about 75% of US employment and almost 60% of all personal consumption. This course will explore the service industries (e.g., transportation, health care, retailing, hospitality, education, emergency services) with a view toward developing models that allow planners to reduce costs and enhance customer service. Topics to be covered include facility location planning for services (e.g., ambulances, fire stations, retail and hospitality services, etc.), resource allocation problems, workforce planning and scheduling, project management, managing customer waiting time, after-sales service management, call center workforce management, pricing and revenue management. The goal is to provide an understanding of the key differences between the service and manufacturing sectors, and to establish the conceptual and analytical frameworks to better manage service businesses. The course also addresses the interface of operations with marketing and advertising in a service business. Quantitative methods that are introduced or strengthened in the course are Goal Programming, Queueing Theory, Decision Analysis, Critical Path Method (CPM) and PERT, Mixed Integer Programming and Nonlinear Programming. These methods are presented through applications in operations, marketing, advertising and pricing in service businesses.
IEMS-482 : Operations
This is a course on modeling and analysis of operations systems for graduate students. Emphasis will be on developing a framework for organizing tools and research results in this field and on modeling techniques necessary to conduct operations system research. Specific topics to be covered include: control and design of single-stage production systems such as produce-to-order and produce-to-stock systems, control and design of multiple-stage production systems including flow lines and job shops in both manufacturing and service systems. Building foundation for variability analysis, the course presents quantitative models of lean operations and supply chain coordination, including contract design. The course also introduces concepts and analytical models of pricing and revenue management. Methodologies that are used to analyze operations systems are stochastic processes, queueing networks, Markov decision process, and game theory.
OPNS-430 : Operations Management
This course is a core course for MBA students in the Kellogg School of Management. It provides a general introduction to operations management. Operations management is the design and control of business processes, that is, the recurring activities of a firm. Along with finance and marketing, operations is one of the three primary functions of a firm. This course aims to (1) familiarize students with the major operational problems and issues that confront managers, and (2) provide students with language, concepts, insights and tools to deal with these issues in order to gain competitive advantage through operations. The course discusses how different business strategies require different business processes, and vice versa, how different operational capabilities allow and support different strategies to gain a competitive advantage. A process view of operations will be used and the course consists of six modules, including operations strategy, process analysis and applications, lean operations, capacity management in services, data driven quality management, and supply chain management.
IEMS-407 : Quantitative Methods of Decision Making
This course is for the Master of Engineering Management (MEM) professional master program. The course is aimed at providing students an understanding of how various business situations are modeled and optimized effectively using mathematical modeling and quantitative techniques. Examples of the techniques covered in this course are time-series analysis, regression, optimization (linear, nonlinear, and discrete), probabilistic modeling, decision analysis, and simulation. Application areas include forecasting, finance, operations, production and logistics. Students will learn through examples, cases, and use of software.
