Quality Control in Mineral Resources

Historical background and general concepts for quality issues (definitions, assurance, certification, ISO, total quality, TQC). Sampling control, SPC statistical quality control processes. Examples and applications in the field of mineral production and processing industry (Mining - quarrying operations, cement, ceramic industry, metallurgy, building materials manufacturing industry etc).

Objectives

Provides the engineers with the appropriate theoretical background to conduct sampling quality control checks in various fields of the production processes

Prerequisites

Statistics

Syllabus

1. QUALITY - BASIC CONCEPTS - HISTORY 1.1. Definition of quality 1.2. Concepts related to quality 1.2.1. Standardization 1.2.2. Certification 1.2.3. Accreditation 1.3. Historical review of the quality and control 1.3.1. Traditional model of production and quality control 1.3.2. The cost of producing defective products 1.3.3. New model of production and quality control 1.3.4. Stages of development of quality procedures 1.3.5. Control - inspection 1.3.6. Statistical quality control 1.3.7. Quality assurance 1.3.8. Total Quality Control 1.3.9. Total quality Management 2. THEORIES ON QUALITY 2.1. Edwards W. Deming 2.2. Joseph Juran 2.3. Comparison theories Deming and Juran 2.4. Philip B. Crosby 3. QUALITY ASSURANCE SYSTEMS - TOTAL QUALITY 3.1. The importance of quality 3.2. Development of quality assurance systems 3.3. Series of quality system standards as ISO 9000 3.3.1. Structure of quality system ISO 9000 3.3.2. Principles of quality system ISO 9000 3.3.3. Structure and principles of quality system ISO 9000: 2008 3.3.4. Certification process in ISO 9000 3.3.5. Advantages - disadvantages and difficulties in applying quality standards in ISO 9000 3.4. Total Quality 4. KEY ELEMENTS OF STATISTICS AND PROBABILITY ΙΝ QUALITY CONTROL 4.1. Statistics, basic concepts and terminology 4.2. Data Descriptive Statistics 4.2.1 Presentation and display of statistical data 4.2.2. Measures position and dispersion of data - Percentage points 4.3. Basic probability theory elements 4.4. Distributions useful for quality control 4.4.1. Hypergeometric distribution 4.4.2. Binomial distribution or distribution Bernouli 4.4.3. Poisson distribution 4.4.4. Normal distribution 4.4.5 Distribution Student, Division F, X2 Distribution 4.5 Confidence interval estimation 4.5.1 Estimation of confidence interval for the mean 4.5.2 Estimation of confidence interval of the difference M1-M2 5. STATISTICAL QUALITY CONTROL 5.1. Definition of statistical quality control 5.2. Designation Methods of Production Quality 5.3. Types of sampling plans 5.4. Types of sampling plans for quality characteristics 5.5. Sampling plans for quality variables 6. STATISTICAL PROCESS CONTROL (SPC) 6.1. Definition of statistical process control 6.2. Analysis of the production process capabilities - capacity indices 6.3. General principles of process control charts 6.4. Construction and interpretation of control charts 6.5. Variable control charts 6. STATISTICAL PROCESS CONTROL (SPC) - (continued) 6.6. Property control charts 6.6.1. Rate control defective - Chart p 6.6.2. Check numbers faulty - Chart np 6.6.3. Checking the number of defects-c and u Charts 6.7 Specific control charts 6.7.1. Cumulative graph or chart CumSum 6.7.2. Chart with exponential smoothing or chart EWMA 6.7.3. Acceptance control chart 6.7.4. Chart with asymmetric control limits 6.7.5. Group control chart 6.7.6. Charts multifunctional 6.8. Control charts Design Methods 6.8.1. Design of control charts with statistical criteria 6.8.2. Economic criteria 7. APPLICATIONS-EXAMPLES IN INDUSTRY