Surface Mount Electronics Manufacturing Minor - Curriculum
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Probability and Statistics I
This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to real-world problems. A statistical package such as Minitab or R is used for data analysis and statistical applications. (Prerequisites: MATH-173 or MATH-182 or MATH 182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer).
Introduction to Statistics I
This course introduces statistical methods of extracting meaning from data, and basic inferential statistics. Topics covered include data and data integrity, exploratory data analysis, data visualization, numeric summary measures, the normal distribution, sampling distributions, confidence intervals, and hypothesis testing. The emphasis of the course is on statistical thinking rather than computation. Statistical software is used. (Prerequisites: Any 100 level MATH course, or NMTH-260 or NMTH-272 or NMTH-275 or (NMTH-250 with a C- or better) or a Math Placement Exam score of at least 35.) Lecture 3 (Fall, Spring, Summer).
This course covers basic statistical concepts and techniques including descriptive statistics, probability, inference, and quality control. The statistical package Minitab will be used to reinforce these techniques. The focus of this course is on statistical applications and quality improvement in engineering. This course is intended for engineering programs and has a calculus prerequisite. Note: This course may not be taken for credit if credit is to be earned in STAT-145 or STAT-155 or MATH 252.. (Prerequisite: MATH-173 or MATH-182 or MATH-182A or equivalent course.) Lecture 3 (Fall, Spring).
Probability and Statistics for Engineers I
Statistics in engineering; enumerative and analytic studies; descriptive statistics and statistical control; sample spaces and events; axioms of probability; counting techniques; conditional probability and independence; distributions of discrete and continuous random variables; joint distributions; central limit theorem. (Prerequisite: MATH-173 or MATH-182 or MATH-182A or equivalent course.) Lecture 3 (Fall, Spring).
Quality Engineering Principles
This course is designed to introduce the student to techniques required to maintain and improve quality within manufacturing organizations and the service sector through the use of statistical methodologies. The course covers concepts of quality, quality managements and assurance, product quality, design of quality control chart, statistical process control, and quality improvement through design by considering concept development and implementation. Traditional and modern quality systems will be discussed including the work of such quality gurus like Taguchi, Deming, Juran, and Shewhart. (Prerequisites: STAT-145 or STAT-205 or STAT-251 or MATH-251 or equivalent course.) Lecture 3 (Fall, Spring).
Lean Production & Supply Chain Operations
This course is designed to provide the student with knowledge and skills of contemporary theories and practices in operations and supply chain management employed by world class manufacturing organizations. Students are introduced to topics that include forecasting, aggregate planning, inventory management, capacity management, and supply chain management. Integrated with these topics are lean excellence tools VSM, 5S, Kanban, OEE and Standard Work Practices, Cycle Time Analysis. (Prerequisites: STAT-145 or STAT-205 or STAT-251 or MATH-251 or equivalent course.) Lecture 3 (Fall, Spring).
This course provides a thorough understanding of the technology, components, equipment, materials and manufacturing process for through hole technology and surface mount technology electronics manufacturing. Students will develop a strong foundation needed for advanced work in surface mount technology (SMT). Topics in Design for Manufacturing are also considered for high volume vs. low volume manufacturing. Students may only receive credit for this course or RMET-645, not both. Lecture 3, Recitation 1 (Fall).
Advanced Concepts in Semiconductor Packaging
The advanced course in semiconductor packaging will provide a thorough coverage of the materials, processes, failure, and reliability of chip level packaging. Specific topics include single-chip, multi-chip, wafer level and 3D stacked packaging, photonic integrated chip (PIC), smaller passives and embedded passive component technology, advanced substrates and microvia technology, solder technologies, metallurgy and joint formation, thermal management, thermal and mechanical behavior of packaging, failure analysis, and reliability testing. This course is cross-listed with RMET-656; students may receive credit for RMET-556 or RMET-656, not both. (Prerequisites: RMET-545 or equivalent course. Students cannot take and receive credit for this course if they have taken RMET-656.) Lecture 3 (Spring).