Study information

Digitisation and Automation - 2023 entry

MODULE TITLEDigitisation and Automation CREDIT VALUE30
MODULE CODECSM2320DA MODULE CONVENERUnknown
DURATION: TERM 1 2 3
DURATION: WEEKS 13
Number of Students Taking Module (anticipated) 20
DESCRIPTION - summary of the module content

Mine Automation has begun to revolutionise the ways in which we operate a mining project. This module gives you the opportunity to investigate the various levels of mine automation currently utilised within the industry, along with its rationale. It will provide you with a comprehensive overview of advanced mining systems and methods, including unmanned and remotely operated mining systems, and other digital technologies. You will also receive an introduction to basic computer analysis of data, including programming.

 

AIMS - intentions of the module

K15

The factors controlling the planning and deployment of automated and digital technologies in mine environments to improve operational efficiency, productivity, and safety.

K27

Data analysis techniques used to examine complex and interacting issues, to assist in developing appropriate solutions solving and support the decision-making process.

S4

Collect, analyse and use data from mining and asset management systems to review the impact on operation, using the outputs to improve the safety, efficiency and effectiveness of the mining system.

 

INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)

On successful completion of this module you should be able to:

Module Specific Skills and Knowledge

1. Basic programming
2. Numeric problem breakdown and analysis
3. Presenting numeric data
4. Statistical and other data summation tools and graphical output
5. Discussion of technologies underlying automation, such as location, sensing, software and digital communications
6. Understanding the drivers of automation and how it meets those drivers
7.Understanding the current state of the art, how it is applied in mining and the advantages that it brings
8.The limitations: economic, theoretical and practical

Discipline Specific Skills and Knowledge

9. Applying digital skills to mine operation and management
10. Analysing new technology such as automation and evaluating its potential to solve mine problems

Personal and Key Transferable / Employment Skills and Knowledge

11. Applying data handling skills to reduce data into knowledge and information
SYLLABUS PLAN - summary of the structure and academic content of the module

The syllabus includes two major topics:

Digitisation will be introduced through the introduction of basic programming skills in Python, and developed through the use of libraries such as MatPlotLib and Pandas to interrogate and interpret numerical data, either from engineering systems or financial sources.

Automation is approached through an introduction of the underlying technologies, and their application in mining, and taught through the use of appropriate tools and case studies.

LEARNING AND TEACHING
LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)
Scheduled Learning & Teaching Activities 45 Guided Independent Study 33 Placement / Study Abroad 0
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS
Category Hours of study time Description
Scheduled Learning Activity 33 Online Lectures & Webinars
Scheduled Learning Activity 0 Residential
Scheduled Learning Activity 12 Site based Group Activity
Guided Independent Study 33 Use of online learning materials.  Completion of assessments required to monitor progress.  Consultation with academic staff.

 

ASSESSMENT
FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade
SUMMATIVE ASSESSMENT (% of credit)
Coursework 50 Written Exams 50 Practical Exams 0
DETAILS OF SUMMATIVE ASSESSMENT
Form of Assessment % of Credit Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Exam 50 2 hours 1-11 Oral and written
Assignment  50 A report of 10 pages and two hand-ins of 100 lines of code 1-4 Oral and written

 

DETAILS OF RE-ASSESSMENT (where required by referral or deferral)
Original Form of Assessment Form of Re-assessment ILOs Re-assessed Time Scale for Re-assessment
Exam Resubmission 1-11 Programme schedule dependent
Assignmnet Resubmission 1-4 Programme schedule dependent

 

RE-ASSESSMENT NOTES

All passed components of the module will be rolled forward and will not be reassessed in the event of module failure.

 

RESOURCES
INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener

Basic reading:

  • Think Python
  • The status and future of mining automation: an overview, by Joe Cucuzza
  • Python data science handbook, by Jake VanderPlas
  • Mine mechanization and automation by Almgren, Kumar and Vagenas
  • Volume II: Mining Automation by Skrzypowski

 

Reading list for this module:

There are currently no reading list entries found for this module.

CREDIT VALUE 30 ECTS VALUE 15
PRE-REQUISITE MODULES None
CO-REQUISITE MODULES None
NQF LEVEL (FHEQ) 5 AVAILABLE AS DISTANCE LEARNING No
ORIGIN DATE Friday 19th August 2022 LAST REVISION DATE Wednesday 1st May 2024
KEY WORDS SEARCH Mining, Automation, Digital Technologies

Please note that all modules are subject to change, please get in touch if you have any questions about this module.