Manufacturing Systems Minor

Overview for Manufacturing Systems Minor

The manufacturing systems minor provides students with a foundation in the professional study and practice of manufacturing operations. Students develop a required foundation of manufacturing processes and statistics, then they select three advanced manufacturing courses to fulfill the following requirements: quality engineering principles, engineering economics, lean production and supply systems, integrated design for manufacturing and assembly, or electronics manufacturing.

Notes about this minor:

The plan code for Manufacturing Systems Minor is MANUFSY-MN.

Curriculum for Manufacturing Systems Minor

Required Courses
Choose one of the following
   Manufacturing Processes
This introductory course investigates the four major categories of traditional manufacturing processes as well as newly developed non-traditional techniques. This course focuses on understanding the concepts of past and current manufacturing processes. Students will learn how typical industrial piece parts and assemblies are manufactured. Topics focus on processes and related theory for the traditional manufacturing processes of material removal, metal forming, joining, casting and molding, as well as more recently developed processes such as powder metallurgy, rapid prototyping, EDM, chemical machining, water jet, LASER and plasma cutting. (NTID Supported Students.) Lec/Lab 5 (Spring).
   Manufacturing Processes
This course will focus on the understanding and application of manufacturing processes. Students will be challenged to discover and learn how typical piece parts and assemblies are manufactured. Topics include material properties and the following process families: casting, material removal, deformation, consolidation, powder metallurgy, plastics fabrication, EDM, water jet, chemical, LASERS, plasma, and rapid prototyping. (This class is restricted to MCET-BS or MECA-BS or RMET-BS or EMET-BS or MANUFSY-MN or ENGTEH-UND students.) Lecture 3 (Fall).
Choose one of the following
   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 (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. (Prerequisite: MATH-101 or MATH-111 or NMTH-260 or NMTH-272 or NMTH-275 or a math placement exam score of at least 35.) Lecture 3 (Fall, Spring, Summer).
   Applied Statistics
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).
Choose three of the following
   Quality Engineering Principles
   Lean Production & Supply Chain Operations
   Integrated Design for Manufacture & Assembly
   Electronics Manufacturing