The course aims to familiarize students with the mathematical tools and methodology for Improving the Quality of Products, Processes and Services. The course deals with Quality Assurance and Control of products (or processes or services) with Statistics tools. The classic definition of quality is the satisfaction of the customer/consumer needs of the producer/supplier when the needs are defined by the customer himself, who may be an individual (B2C) or a collective, e.g. public, other business (B2B), regulatory authority. Quality is distinguished by: (1) Quality Improvement for Existing Products and (2) Quality-in-Designing New Products. Quality Improvement is the subject of the course described here. The methodology for Quality Improvement is taught, including the following steps: (1) Problem Identification, (2) Measurement, (3) Analysis, (4) Optimization and (5) Control. The engineer translates the needs into measurable quantities that characterize the quality of the product and selects CQAs according to specifications (LSL, USL). It recognizes the factors affecting CQA, that is, the composition and properties of raw materials and operating conditions, and selects Critical Material Characteristics (CMAs) and Critical Process Parameters (CPPs), respectively. Designs experiments with controlled raw materials and operating conditions, arranges for CQA measurements for different CMA and CPP values, and develops approximate relationships between CQA, CMA and CPP. It recognizes the values of quality agents, CMA and CPP, which optimize quality, CQA, and sets control limits for agents that ensure quality in accordance with specifications. The methodology for Quality Improvement, using tools from Statistics and Experimental Design (DOE) and Statistical Process Control (SPC) techniques, is taught through lectures and exercises using the MINITAB software in the small computer lab.