Course Descriptions
Credits: 3 (1,0,4)
Prerequisite: NA
This course focuses on learning various CAD tools and understanding the graphical interpretation of orthographic projections such as pictorial and section views, dimensioning, assembly drawings, etc. In addition, the student will learn about planar projection theory, including sketching of perspective, isometric, multi-view, auxiliary, and section views. The course provides students with 3D Modeling skills based on 2D based drawings. Additionally, students learn how to realize the 3D digital model using 3D printer technology. The related software to learn is AutoCAD and SolidWorks.
Credits: 4 (3,1,2)
Prerequisite: NA
This course covers the concept of programming languages in Python. It enables the student to understand and write basic coding based on various operators, functions, logic statements, strings, tuples, etc., in the Python programming language. In addition, the course covers the basic concept of files and exceptions.
Credits: 3 (3,1,0)
Prerequisite: MATH 111
The course introduces a range of statistical concepts and techniques with applications. This course focuses on descriptive statistics that includes data types, frequency distribution, measure of central tendencies and deviations, basic probability theory, random variables and sampling techniques. Students also learn the use of Excel through projects.
Credits: 3 (3,0,0)
Prerequisite: NA
The course will help in developing an understanding of the concepts of Industrial and Systems Engineering principles. This course will also provide students with the ability to analyze a situation in a team environment and use the appropriate tools and techniques of Industrial and Systems Engineering to solve the issues, and present solutions.
Credits: 3 (3,0,1)
Prerequisite: EE 101, ISE 201
Applications of decision support systems in industrial and systems engineering; developing and implementing decision support systems arising in industrial and systems engineering using popular database management and spreadsheet software; Microsoft Excel; Visual Basic for Excel.
Credits: 3 (3,0,0)
Prerequisite: STAT 101
The course is designed for engineering problem solving and for development of engineering applied statistical thinking. The course covers principles of engineering data collection; principles of experimentation; confidence intervals and hypothesis testing for one, two and multi-sample studies; test for independence, homogeneity; simple and multiple regression analysis and interpretations; analysis of variance. Students employ statistical software such as R to perform statistical data analysis.
Credits: 3 (2,2,0)
Prerequisite: ME 101
This course presents an introduction to design to offer students a solid composition for the design procedure that they can use with a range of design techniques and software bundles. The course is constructed to educate students and designers by doing hands-on design exercises and providing a range of means essential for their designs.
Credits: 3 (3,1,0)
Prerequisite: MATH 113
This course covers linear algebra techniques including matrices, determinants, systems of linear equations, vector spaces, eigenvalues, and eigenvectors. It also explores linear transformations and their applications.
Credits: 3 (3,1,0)
Prerequisite: MATH 113
This course introduces students to various topics in the concept of differential equations. Topics include techniques for solving first order differential equations, homogeneous and general second order linear equations, higher order linear equations, power series solutions, the Laplace transform and applications in science and engineering, elementary partial differential equations, Laplace’s equation, the heat equation, and the wave equation.
Credits: 3 (3,0,1)
Prerequisite: CHEM 101, PHY 105
Introduction to the properties of engineering materials: mechanical, electrical and chemical; fundamentals of crystallography; impurities and imperfections in solids; atomic diffusion; single phase metals and alloys; elastic and plastic deformation, recrystallization and grain growth; multi-phase materials; phase diagrams with emphasis on iron-iron carbide system; heat treatment processes such as annealing, normalizing and quenching; studies of widely used engineering materials such as steels, plastics, ceramics, concrete and wood; in addition to fundamentals of metallurgy and alloys. Laboratory experiments are associated with the lectures.
Credits: 3 (3,0,1)
Prerequisite: ME 212
The course focuses on manufacturing processes of metals and plastics including machining and forming, plastic processing, powder metallurgy, welding and casting. The course concentrates on process selection for optimum design. Laboratory experiments are associated with lectures.
Credits: 3 (3,0,0)
Prerequisite: Math 113 and EE 101
This course focuses on the coupling of technical analysis and economic feasibility to determine the best course of action among alternatives competing for scarce resources. Studies the principles, concepts, and methodology of the time value of money as applied to governmental, industrial, and personal economic decisions. Topics include cost-estimating techniques for engineering projects, benefit-cost analysis, present worth, rate of return, depreciation, taxes, break-even analysis, risk and sensitivity analysis, capital investment, and the comparison of alternatives. Discussion includes the ethical and social responsibilities of engineers as they apply to project decisions affecting job creation and loss, personnel placement, and capital expenditure.
Credits: 2 (2,0,0)
Prerequisite: NA
This course is an introduction to engineering ethics. Topics include ethical theories, professional engineering responsibility, codes of ethics, ethical assessment, conflicts of interest, risk and safety, loyalty and dissent, as well as overarching professional concerns and methodologies to solve ethical problems.
Credits: 3 (3,0,1)
Prerequisite: ISE 221
This course introduces data science concepts and statistics and machine learning techniques for analyzing and discovering knowledge from large data sets that occur in engineering domains such as manufacturing, healthcare, sustainability, and energy. Topics include data reduction, data exploration, data visualization, concept description, mining association rules, classification, prediction, and clustering. The course discusses data mining case studies from manufacturing, retail, healthcare, biomedical, telecommunication and other sectors. Artificial intelligence is introduced using applications of neural networks.
Credits: 3 (3,1,0)
Prerequisite: EE 101, STAT 101, MATH 225
This course studies resource optimization through mathematical programming. The course starts with teaching the art of mathematical modeling for engineering and management problems. Emphasis is placed on applications of optimization models to typical engineering management problems. Topics include problem formulation, mathematical model building, linear programming, Simplex algorithm and duality. Applications to transportation, assignment, resource allocation, scheduling, routing, and facility location and layout problems will be shown. Post-optimality analysis is studied from the viewpoint of technology management. The course includes a project involving a real-life problem.
Credits: 3 (3,0,0)
Prerequisite: MATH 223; ISE 311, ISE 303
Operations Research II builds on foundational optimization concepts and deepens students’ ability to model and solve complex real-world decision problems using advanced analytical techniques. The course covers discrete optimization methods such as Integer Linear Programming and Dynamic Programming, as well as Nonlinear Programming including unconstrained and constrained optimization, Lagrangian methods, KKT conditions, and Quadratic Programming. It also introduces stochastic processes with emphasis on Markov chains and queuing models. Students will develop the skills to formulate models, interpret results, and apply advanced operations research techniques effectively in decision-making contexts.
Credits: 3 (3,0,1)
Prerequisite: Junior Level Standing, STAT 101, ISE 201
This course studies requirements flow down, cost estimation, analysis on design, probabilistic design, logistic support, maintainability, availability, interface control, system integration, reliability growth modelling, cost estimation, sparings, testing and performance evaluation, system safety modelling, installation procedures, asset management, disposal, asset purchase and replacement policies, and decision-making. More specifically, the topics covered include terminologies for reliability engineering, failure data analysis and modelling, system reliability modelling, system maintainability and availability, design for reliability, reliability testing, reliability growth testing, and reliability management.
Credits: 3 (3,0,0)
Prerequisite: STAT 101, ME 212
This course will provide students with exposure to the fundamentals of forecasting techniques, project planning, aggregate planning and master scheduling, inventory analysis and control, materials requirement planning, job shop scheduling, and dispatching problems. Further parts of the course touch upon recent developments in manufacturing, Japanese manufacturing techniques, and hybrid manufacturing management systems.
Credits: 3 (3,0,0)
Prerequisite: STAT 101, ME 212
This course examines the principles and techniques of managing and improving quality in manufacturing and service facilities. Topics include quality control charts for processes as well as raw materials and end items, continuous quality improvement tools, service quality, total quality management concept, and quality awards.
Credits: 3 (3,0,0)
Prerequisite: ISE 332
This course introduces fundamental knowledge on facility design stages of industrial factory product, process and material handling analysis; area allocation and space analysis; flow analysis; plant layout and plan; computerized facility layout and allocations. The course also tackles topics related to facilities and property industries, budgeting, standards, labor relations, safety, personnel administration, maintenance, energy conservation, HVAC systems and space planning.
Credits: 3 (3,0,0)
Prerequisite: PHY 105; Junior Level Standing
This course is concerned with the design and evaluation of interaction between users and an engineered system. It focuses on the human performance of tasks, the structure of human-system communication, human capabilities to use system components, and the design, specification, and evaluation of interfaces. It discusses displays and controls, cognition, perception, cumulative trauma disorders, biomechanics of work, work analysis and design, methods engineering, basic work measurement techniques, and applications and limitations of stopwatch time study and predetermined motion times.
Credits: 3 (3,1,0)
Prerequisite: ISE 302, STAT 101
This course introduces functions and techniques for effective management of systems development and effective project leadership. Project definition, phases, and work breakdown. Scope, risk, configuration, and quality management. Cost and time estimation. Tools for planning, scheduling, monitoring and controlling project development.
Credits: 3 (2,0,3)
Prerequisite: ISE 311, ISE 332, STAT 272, ISE 303
This course presents an introduction to discrete event simulation systems. Emphasis is placed on modeling and the use of simulation languages and software to solve real-world problems in manufacturing as well as service sectors. The course discusses modeling techniques of entities, queues, resources and entity transfers in discrete event environments. It teaches students the skills to formulate and build valid models, implement the model in a software platform, perform simulation analysis of the system, analyze results properly, and avoid costly solutions and errors. The theory of simulation involves probability and statistics, thus a good background in probability and statistics is required.
Credits: 3 (3,0,1)
Prerequisite: ME 303; ISE 332
Common production machines and manufacturing systems are dealt with, particularly automated systems, robotics, computer control and integration techniques, materials handling, inspection processes and process control. The course addresses societal and environmental issues related to manufacturing.
Credits: 3 (3,0,0)
Prerequisite: Completion of 90 credit hours
This course focuses on production systems. Lean production tools and techniques are described. Issues relating to employee involvement, improvement teams, training and culture are presented. Planning for lean process implementation and the necessity of sustaining improvements are discussed. Examples of applications in manufacturing and business processes are presented. The concept of cellular manufacturing and its application is discussed. The concept of Six Sigma is covered and the relation between lean and Six Sigma is introduced.
Credits: 10
Prerequisite: Completion of 90 credit hours
The PSU COOP Education Program combines classroom learning with work experience to assist students in applying their knowledge and skills to real life situations and building strong partnerships between PSU and the local business community, as well as enabling students to create future quality careers in response to the evolving local economic and workforce development needs. Students are expected to prepare and present a report of their work experience.
Credits: 1 (1,0,1)
Prerequisite: ENG 301, ME 202, Completion of 90 credit hours
Project groups deliver products that have progressed through the design, analysis, testing and evaluation stages. Project teams produce a polished professional report that describes the design process, implementation and testing, verification and validation, and a critical appraisal of the project. An oral presentation and graphic works are complementary project deliverables.
Credits: 2 (1,0,3)
Prerequisite: ME 493
This course is a continuation of Senior Design Project I. Project groups deliver their products that have progressed through the design, analysis, testing and evaluation stages. The project teams produce a polished professional report that describes the design process, implementation and testing, verification and validation, and a critical appraisal of the project. An oral presentation and graphic works are complementary project deliverables.