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Information
| Code | MD0084 |
| Name | Mineral Processing Data Analysis and Modeling |
| Term | 2022-2023 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | |
| Course Instructor |
1 |
Course Goal / Objective
Data analysis methods in ore preparation, Statistical methods, Package programs used, factorial design, data grouping, linear modeling, nonlinear models, data analysis applications, , data analysis applications, Design Of experiment (DOE)
Course Content
Data analysis methods in ore preparation, Statistical methods, Package programs used, factorial design, data grouping, linear modeling, nonlinear models, data analysis applications, , data analysis applications, Design Of experiment (DOE)
Course Precondition
no
Resources
notes
Notes
visual sources
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | It uses modern engineering, computer modeling and simulation tools in the development of mining engineering projects and solving advanced engineering problems. |
| LO02 | Learns to independently conduct scientific and technical research on all subjects, including her field of specialization. |
| LO03 | Gains systematic thinking and problem solving abilities with the in-depth knowledge gained in the field of ore preparation. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Uses the mathematics, science, and engineering knowledge gained in undergraduate education in the advanced solution of mining engineering problems. | 5 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Have advanced theoretical and applied knowledge in the fields of mining engineering. | 4 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Learns to independently conduct scientific and technical research on all subjects, including the field of specialization. | 5 |
| PLO04 | Beceriler - Bilişsel, Uygulamalı | Gains the ability to transfer scientific and social values to others at every stage of works. | 4 |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Have the ability to prepare projects related to the working subjects of mining engineering. | 5 |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Have the ability to define, formulate and solve problems related to mining engineering at an advanced level. | 4 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Have the awareness of lifelong learning for professional development. | 5 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Have the ability to work independently, team work, and interdisciplinary. | 5 |
| PLO09 | Yetkinlikler - Alana Özgü Yetkinlik | Uses modern engineering, computer modeling and simulation tools in the development of mining engineering projects and solving advanced engineering problems. | 5 |
| PLO10 | Yetkinlikler - Öğrenme Yetkinliği | Gains systematic thinking and problem solving abilities with the in-depth knowledge gained in the field of Mining Engineering. | 5 |
| PLO11 | Yetkinlikler - Öğrenme Yetkinliği | Have the ability to use the in-depth knowledge gained in the field of Mining Engineering in interdisciplinary studies. | 5 |
| PLO12 | Yetkinlikler - Öğrenme Yetkinliği | Gains the ability to define a problem that requires expertise in the field of Mining Engineering. | 5 |
| PLO13 | Yetkinlikler - Öğrenme Yetkinliği | Gains the professional and ethical responsibility of mining engineering. | 4 |
| PLO14 | Yetkinlikler - Öğrenme Yetkinliği | Comprehends the universal and social effects of mining engineering applications. | 3 |
| PLO15 | Yetkinlikler - Öğrenme Yetkinliği | Have the ability to evaluate projects related to the study subjects of mining engineering. | 3 |
| PLO16 | Yetkinlikler - Öğrenme Yetkinliği | Gains the ability to interpret the results obtained in the solution of a problem that requires expertise in the field of Mining Engineering. | 4 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Graph drawing with excel on computer | notes | Öğretim Yöntemleri: Anlatım |
| 2 | Determination of basic test parameters | notes | Öğretim Yöntemleri: Anlatım |
| 3 | Classical experimental studies in the laboratory | notes | Öğretim Yöntemleri: Anlatım |
| 4 | ortalama, mod, medyan | notes | Öğretim Yöntemleri: Anlatım |
| 5 | Variance, standard deviation etc. topics | notes | Öğretim Yöntemleri: Anlatım |
| 6 | Using SPSS and minitab statistical programs | notes | Öğretim Yöntemleri: Anlatım |
| 7 | Using SPSS and minitab statistical programs | notes | Öğretim Yöntemleri: Anlatım |
| 8 | Using SPSS and minitab statistical programs | notes | Öğretim Yöntemleri: Anlatım |
| 9 | Using SPSS and minitab statistical programs | notes | Öğretim Yöntemleri: Anlatım |
| 10 | Using the Design-Expert Program | notes | Öğretim Yöntemleri: Anlatım |
| 11 | Using the Design-Expert Program | notes | Öğretim Yöntemleri: Anlatım |
| 12 | Using the Design-Expert Program | notes | Öğretim Yöntemleri: Anlatım |
| 13 | Using the Design-Expert Program | notes | Öğretim Yöntemleri: Anlatım |
| 14 | Using the Design-Expert Program | Notes | Öğretim Yöntemleri: Anlatım |
| 15 | Effective report preparation and presentation | notes | Öğretim Yöntemleri: Anlatım |
| 16 | make up exam | notes | Ölçme Yöntemleri: Ödev |
| 17 | final exam | notes | Ölçme Yöntemleri: Ödev |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||