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Efficiency and Productivity Improvements at aPlatinum ConcentratorDevelopment of a Management Tool to Measure and Monitor

OEE and Process Pain

ANTON KULLHJOSEFINE LMEGRAN

Department of Product and Production Development

CHALMERS UNIVERSITY OF TECHNOLOGYGothenburg, Sweden, 2013

Master of Science Thesis in Quality and Operations Management, Mechanical Engineering

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I

Efficiency and Productivity Improvements at aPlatinum Concentrator

Development of a Management Tool to Measure and MonitorOEE and Process Pain

ANTON KULLHJOSEFINE LMEGRAN

Department of Product and Production Development

CHALMERS UNIVERSITY OF TECHNOLOGYGothenburg, Sweden, 2013

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II

Efficiency and Productivity Improvements at a Platinum Concentrator

Development of a Management Tool to Measure and Monitor OEE and Process Pain

ANTON KULLH (B. Sc. Mechanical Engineering)

JOSEFINE LMEGRAN (B. Sc. Mechanical Engineering)

ANTON KULLH, JOSEFINE LMEGRAN, 2013.

Published and distributed byChalmers University of TechnologyDepartment of Product and Production DevelopmentSE-412 96 GothenburgSweden

Telephone + 46 (0)31-772 1000

In collaboration with

University of Cape TownAnglo American Platinum

Printed byReproserviceGothenburg, Sweden 2013

Cover photo:Parts of the comminution process at Mogalakwena North Concentrator, Limpopo,South Africa (Josefine lmegran, 2012)Efficiency and Productivity Improvements at a Platinum Concentrator

Development of a Management Tool to Measure and Monitor OEE and Process Pain

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III

ANTON KULLH

JOSEFINE LMEGRAN

Abstract

The current low platinum price has puthigh pressure on the industry and forcedcompanies to introduce cost cutting effortsas well as productivity increasing actions.Increasing the productivity can be doneeither by increasing the output ordecreasing the amount of consumedresources. This project has focused on thelatter. There are several productivityincreasing methods, such as TotalProductivity Maintenance (TPM) and Lean,to utilise. In the mining industry thesemethods have not been used to the sameextent as in, for instance, the automobileindustry to improve productivity. Existingresearch in mining mostly deals with thetechnical aspects of the process, such asoptimising single units.

This project has three distinct phases andwill use the incorporated tools of TPM and

Lean to, firstly define a calculation modelof equipment performance metrics for asingle stream comminution process.Secondly, a tool to perform real timecalculations of defined metrics will bedeveloped. Thirdly, a method for using thetool output in the organisation in a valuecreating way, with primary focus on findingroot-causes to productivity limiting issues,will be designed.

The project is a collaboration betweenChalmers University of Technology,Gothenburg, Sweden, and the University ofCape Town, South Africa. The projectsponsor is Anglo American Platinum andthe plant where the project has beenconducted is Mogalakwena North

Concentrator (MNC), Limpopo, SouthAfrica. MNC is ranked as the biggestsingle-stream platinum concentrator inSouth Africa and one of the largestfacilities of its type in the world (MiningWeekly, 2008).

The Masters thesis writers have developed

a method for calculating OverallEquipment Effectiveness (OEE) in acomminution process. The method

incorporates a method to calculate quality,which is a parameter that has previouslynot been defined for a comminutionprocess.

A method called Pain analysis has beendeveloped by the Masters thesis writers to

display duration and frequency of thereasons that cause the stops in the process.This new way of displaying stop data has

been appreciated by its users and hasreceived positive response from theorganisation.

The developed Overall Productivity Tool(OPT) is at this stage a fully functionalsoftware used by MNC in daily work. Themethods and day-to-day tools developed inthis Masters thesis project will be

incorporated in new software developed byAnglo American Platinum. The software isto be implemented throughout theorganisation.

Answers to the research questions areprovided at the end of the report as well asrecommendations for the operations atMogalakwena North Concentrator.

Keywords: Overall EquipmentEffectiveness (OEE), productivity,

efficiency, quality, availability, performance,overall utilization, process pain, platinum,concentrator, Overall Productivity Tool(OPT)

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V

ACKNOWLEDGEMENTS

A number of people have been highlyvaluable to us in this Masters thesis project.

We would like to mention them here and

send them our deepest gratitude forassisting us throughout the project.

Great thanks to our examiner Prof. MagnusEvertsson (Chalmers University ofTechnology) as well as to our supervisorsDr. Erik Hulthn (Chalmers University ofTechnology) and Dr. Aubrey Mainza(University of Cape Town), who togetherinitiated this project. Without their early

vision of creating a Masters thesis projectfocused on increasing the productivity atMogalakwena North Concentrator (MNC),this project would not have been born.

We would also like to thank Neville Plintand Gary Humphries at Anglo AmericanPlatinum, who always have been just anemail away and provided guidance andfeedback throughout the project.

Thanks to Senior Concentrator ManagerBarry Davis for his positive attitude to thisproject from day one, for authorising us toget access to the plant as well as his officeand providing us feedback throughout theproject. We give many thanks also to PlantManager Ellie Moshoane and TechnicalManager Dane Gavin who have acted assupervisors on site and supported our workand provided reflections and feedback

every day. We would also like to thank themetallurgists on site, Albert Blom, SithiMazibuko, Felix Mokoele, Herman Kemp

and Howard Saffy, who always have beenpatient with our questions and given theirinput to our work.

We also want to send our gratitude to thebrilliant PhD students and at ChalmersRock Processing Systems Johannes Quistand Gauti Asbjrnsson for their invaluableinput and encouragement in all sorts ofmatters throughout the entire project.

We extend a huge thanks to BarbaraAndersen at the University of Cape Townwho arranged everything we could possiblyneed during our entire stay in South Africa.Without her help we would have beenforced to put more effort into bookingflights than typing code.

Finally, we would like to thank allemployees at Mogalakwena North

Concentrator for supporting our work,patiently allowing us to ask questions andproviding useful answers.

Last but not least, we would like to thankour families and friends for allencouragement and support during thisexciting journey from the 5th floor of theMechanical Engineering building atChalmers to one of the worlds largestplatinum concentrators.

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VI

TABLE OF CONTENTS

.Chapter One - Introduction ....................................................................................................................... 1

1.1 Project Introduction .............................................................................................................................. 21.2 Company Introduction ......................................................................................................................... 2

1.3 Background ............................................................................................................................................ 2

1.4 Earlier Efforts In This Area ................................................................................................................ 3

1.5 Project Scope ......................................................................................................................................... 3

1.6 Research Questions .............................................................................................................................. 4

1.7 Delimitations ......................................................................................................................................... 4

Chapter Two Theoretical Framework ................................................................................................... 5

2.1 Productivity ............................................................................................................................................ 6

2.2 Total Productive Maintenance (TPM) ............................................................................................... 6

2.3 Overall Equipment Effectiveness (OEE) .......................................................................................... 6

2.4 Continuous improvement - Kaizen () ....................................................................................... 11

2.5 Performance Measurements .............................................................................................................. 12

2.6 Value Stream Mapping (VSM) ......................................................................................................... 13

2.7 RACI Matrix ....................................................................................................................................... 142.8 Platinum ............................................................................................................................................... 15

2.9 Extraction of Platinum-Group Metals (PGMs)............................................................................. 16

Chapter Three - Methodology ................................................................................................................. 17

3.1 Research Strategy ............................................................................................................................... 18

3.2 Research Approach ............................................................................................................................ 18

3.3 Theory .................................................................................................................................................. 18

3.4 Reliability ............................................................................................................................................. 203.5 Validity ................................................................................................................................................. 20

3.6 Ethical aspects ..................................................................................................................................... 21

Chapter Four - Data ................................................................................................................................. 23

4.1 Quantitative Data ............................................................................................................................... 24

4.2 Qualitative Data .................................................................................................................................. 25

4.3 Empirical Data .................................................................................................................................... 25

4.4 Current Value Stream Maps .............................................................................................................. 29
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VII

Chapter Five - Results .............................................................................................................................. 31

5.1 Calculation Model ............................................................................................................................... 32

Final OEE Calculation ......................................................................................................................... 33

Availability ............................................................................................................................................ 35

Utilised Uptime ..................................................................................................................................... 36

MTBF & MTTR .................................................................................................................................... 36

Pain Analysis ......................................................................................................................................... 36

5.2 The Overall Productivity Tool (OPT) .............................................................................................. 39

5.3 OPT Method ........................................................................................................................................ 43

User Expertise ....................................................................................................................................... 43

Five WHYs ............................................................................................................................................ 43OPT Guidelines ..................................................................................................................................... 43

OPT Meeting Procedure ...................................................................................................................... 44

OPT Action List .................................................................................................................................... 44

5.4 OEE For a General Single Stream Process ..................................................................................... 45

5.5 Crusher and Mill Stops Reporting Procedure ................................................................................. 45

Chapter Six Discussion & Conclusions ............................................................................................... 47

6.1 Calculation Model ............................................................................................................................... 486.2 The Overall Productivity Tool (OPT) .............................................................................................. 57

6.3 OPT Method ........................................................................................................................................ 58

6.4 OEE for a General Single Stream Process ...................................................................................... 59

6.5 Crusher and Mill Stop Reporting Procedure ................................................................................... 60

6.6 Research Questions and Answers ..................................................................................................... 60

6.7 Observations ........................................................................................................................................ 62

6.8 Recommendations .............................................................................................................................. 64

6.9 Future Research .................................................................................................................................. 64

References ................................................................................................................................................. 66
http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094418http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094419http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094425http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094426http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094427http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094428http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094429http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094430http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094431http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094432http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094432http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094432http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094434http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094438http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094439http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094440http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094441http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094442http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094444http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094445http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094447http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094447http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094445http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094444http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094442http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094441http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094440http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094439http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094438http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094434http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094432http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx%23_Toc346094431http://d/Dropbox/My%20Dropbox/Master's%20thesis%20at%20MNC&UCT%20in%20cooperation%20with%20Chalmers/Report/Final_report_v6_20130116.docx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VIII

APPENDIX

APPENDIX I

Process Maps

APPENDIX II

Lynxx Cameras Map

APPENDIX III

Job Card Inspections and Maintenance Map

APPENDIX IV

OPT Print Screens

APPENDIX V

OPT Manual

OPT Meeting Procedure

OPT Action List

Organisational Chart

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1

CHAPTER ONE

INTRODUCTION

This chapter will introduce the Masters Thesis project by presenting a background oftheproblem, a company introduction, earlier efforts in the area, the project aim and finally the

research questions

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CHAPTER 1 - Introduction

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1.1PROJECT INTRODUCTION

The project is a collaboration betweenChalmers University of Technology,Gothenburg, Sweden, and the University of

Cape Town, South Africa. The sponsor ofthe project is Anglo American Platinumand the plant where the project has beenconducted is Mogalakwena NorthConcentrator (MNC), Limpopo, SouthAfrica. MNC is ranked as the largest single-stream platinum concentrator in SouthAfrica and one of the largest facilities of itstype in the world (Mining Weekly, 2008).

The examiner of this thesis is Prof. MagnusEvertsson (Chalmers University ofTechnology). Dr. Erik Hulthn (ChalmersUniversity of Technology) and Dr. AubreyMainza (University of Cape Town) haveacted as supervisors. The writers of thisMasters thesis are B.Sc. Anton Kullh

(Chalmers University of Technology) andB.Sc. Josefine lmegran (ChalmersUniversity of Technology).

This project was initiated by the supervisorswho wanted to investigate how to increaseproductivity in a comminution process. Theproject scope has thereafter evolvedthroughout the project as the writers havegained more knowledge in the area ofresearch. It is important to have a validmeasure of productivity in order to be ableto increase it and to be able to judge if yourefforts are contributing to productivityimprovements. The final scope is set asthree distinct phases and can be viewedunder 1.5 Project Scope.

1.2COMPANY INTRODUCTION

Anglo American Platinum Limited is aSouth African company which holds about40% of the worlds newly mined platinum,

making them the world leading primaryproducer of platinum. The equivalentof

refined platinum produced by their ownmines amounted to about 44 tons in 2011.

To operate more effectively and efficientlyAnglo Platinum recently accomplished a

thorough reconstruction and they nowoperate nine individual mines aroundSouth Africa. One of them is MogalakwenaMine, which is situated 30 kilometresnorthwest of Mokopane in the Limpopoprovince and operates under a mining rightcovering a total area of 137 squarekilometres (Anglo American, 2012).Mogalakwena Mine provides ore toMogalakwena South Concentrator (MSC)

and Mogalakwena North Concentrator(MNC). MNC is ranked as the largestsingle-stream platinum concentrator inSouth Africa and one of the largestfacilities of its type in the world and is theplant where this Masters thesis project wasconducted (Mining Weekly, 2008).

1.3BACKGROUND

South Africa accounts for nearly 80% ofthe global platinum production, whichmakes the platinum price highly influencedby the economy of the country.

During the last five years there has been alarge decrease in the platinum spot price. InMarch 2008 the price peaked at 2273USD/oz t (Kitco, 2012), which can becompared to the spot price at the start of

this project (mid-August 2012); 1485USD/oz t (Kitco, 2012).

The price drop has several explanations.Firstly, the price spiked in 2008 due to aprospected supply shortage. Secondly, thesector has experienced wage inflation inexcess of the general inflation. Thirdly, thestrengthening of the rand has decreased thegap between dollar-denominated sales and

rand-based costs. As a result of this, somehigh cost mines have had trouble running

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profitable operations during recent years.(Mail & Guardian, 2011)

This significant drop in price has put highpressure on the industry and forced

companies to introduce cost cutting effortsas well as productivity increasing actions.This project will deal with the aspects ofproductivity.

An increase in productivity can gain severalstakeholders and be profitable not only forthe company itself, but also for the nearbycommunities, the region and the country.

1.4EARLIER EFFORTS IN

THIS AREA

In the mining industry TPM and Lean havenot been used to the same extent toimprove productivity as in, for instance, theautomobile industry. There is someresearch literature on productivityincreasing efforts in comminution processesbut it mostly deals with the technicalaspects of the process, such as optimising asingle unit, i.e. a ball mill. This approachcan result in an unintended sub-optimisation instead of an optimisation ofthe entire process chain. The research has agap concerning the usage of the abovementioned methodologies to improve thetotal productivity of the comminutionprocess. Therefore, this thesis aims to helpfill the gap and explain how to work withproductivity increasing efforts throughoutthe entire process, instead of only in singleunits.

1.5PROJECT SCOPE

To increase productivity, the process needsto be completely comprehended andcontrolled. It is highly important to have a

valid and accurate method of calculatingequipment performance metrics, so that it

can be monitored. Further, it will allow forthe results of performed productivityincreasing actions to be analysed andevaluated. This is in agreement with theauthor of the book TPM Vgen till stndiga

frbttringarrjan Ljungberg:

What you do not measure, you cannot controland what you cannot control, you cannot

improve.(Ljungberg, 2000 p.37)

The methods TPM and Lean and theirincorporated tools will found a basis forthis Masters thesis project, which is divided

into three distinct phases. Firstly, a

calculation model of equipmentperformance metrics for a single streamcomminution process will be defined. Thiscalculation model will be aligned with theAnglo American Equipment PerformanceMetrics Standard and fully functional for asingle-stream comminution process.Secondly, a tool to perform real-timecalculations of the defined metrics will bedeveloped. To achieve this, user friendly

software which automatically computes thedefined equipment performance metrics forthe equipment included in the project willbe developed. Thirdly, a method will bedesigned for using the tool output in theorganisation in a value creating way. Theprimary focus will be on designing amethod for finding root-causes toproductivity limiting issues.

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31 2

Definea calculationmodel for OEE &other equipment

performance metrics

in a single streamprocess

Developa tool thatcalculates OEE &other equipment

performance metrics

in real time

Designa methoddescribing how to usethe tool output in the

organisation with

primary focus onfinding root causes

Figure 1The three phases of this Masters thesis project

1.6RESEARCH QUESTIONS

The following research questions have been

formulated for this Masters thesis. Theresearch questions cover the areas ofOverall Equipment Effectiveness (OEE),Performance indicators, productivity andSHE (Safety, Hygiene, Environment).

1. How can a method be developed todefine and rank process unitscritical to productivity in acomminution process?

2.

How should OEE numbers becalculated in a single-streamcomminution process?

3. Which factors in the process chainare more critical to productivity according to the OEE philosophy?

4. How can OEE be used as aperformance measure of equipment

and process performance?5. How can OEE help to improve

SHE (Safety, Hygiene,Environment)?

6. How can measuring OEE help toimprove productivity?

1.7DELIMITATIONS

To fulfil the purpose of this Masters thesis,

the project concentrated on the initial partof the comminution circuit of a mineralsprocessing plant, which at MNC includesthe primary gyratory crushing, thesecondary crushing, HPGR-crushing,classifiers, feeders, and conveyors.

The research was limited to this area fortwo reasons; it is a good idea to start theimplementation in a small scale and itwould have been too time consuming forthe Masters thesis to include a larger

section of the plant.

The decision to limit the project to a sub-set of the plant is supported by Idhammar(2010) who argues that implementing OEEin a part of the plant will facilitate animplementation throughout the plant at alater stage. Idhammar also states that anearly pilot can eliminate issues and provide

useful training and experience for staffmembers.

The developed tool will be fully functional,however not completely integrated into theScada and PI-system at the plant.

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CHAPTER TWO

THEORETICAL FRAMEWORK

This chapter will present the theoretical framework used for the Masters thesis project.

The theoretical framework shall act to facilitate understanding for readers with no or littleformer experience of the industry and the methodologies used in the project.

However, the targeted readers of the report are assumed to already possess a basic knowledgein the area. Some basic definitions are therefore left out.

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CHAPTER 2 Theoretical Framework

7

effectiveness and to understand how theprocess is performing. OEE is a methodthat can help to do this by giving a betterunderstanding of how well a process isperforming and by identifying what thelimiting factors are. (Hansen, 2001)

An OEE number of 100% corresponds to aunit which is performing at its maximum

capacity always running, always at theoptimal speed and producing perfectquality.

It is essential to note that OEE is morethan just one number; it is, in total, four,which are all individually useful. The OEEmeasurement combines the availability ofthe machine, the performance rate and thequality rate in one equation (M. Maran, etal., 2012)

OEE Availability x Performance x Quality Equation 2

=

Gross Operating TimeAvailability

Planned Production Time

Planned Production Time Unplanned Downtime

Planned Production Time

Equation 3

Net Operating Time Ideal Cycle TimePerformance

Operating TimeGross Operating Time

Total Pieces

Equation 4

Valuable Operating Time Good PiecesQuality

Net Operating Time Total Pieces Equation 5

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2.3.1GENERAL OEEDEFINITION

There is no established standard for how tocalculate OEE for a single streamcomminution process. A version frequentlyused in the manufacturing industry, derivedfrom (Nakajima, 1989), is presented inEquation 2, and explained in more detail inEquation 3, 4, 5 and Figure 2.

Availability is the ratio between GrossOperating Time and Planned ProductionTime, where Gross Operating Time isPlanned Production Time minusUnplanned Downtime. For definitions of

parameters, seeFigure 2.

Performance is the ratio between NetOperating Time and Gross Operating Time,where Net Operating Time is GrossOperating Time minus Speed Losses, or theratio between the actual speed and nominal,budgeted, or target cycle time.

Quality is the ratio between ValuableOperating Time and Quality Losses, whereValuable Operating Time is Net OperatingTime minus Quality Losses, or the ratiobetween Good Pieces and Total Pieces.The OEE calculation parameters aredescribed inFigure 2.

Figure: Freely after Method and a system for improving the operability of a production plant

Figure 2Definitions of the general OEE parameters

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2.3.2ANGLO AMERICAN

EQUIPMENT PERFORMANCE

METRICS OEEDEFINITION

The Anglo American EquipmentPerformance Metrics (a company internalstandard) offers another way of calculatingthe OEE, which will be presented in thissection.

The metric corresponding to the generalOEE calculations availability is titledOverall Utilisation (see Equation 6). This

represents the ratio between Primaryproduction (P200) time and Total time(T000), where Primary production isdefined as Time equipment is utilised for

production and Total time is defined asThe total possible hours available.

(Anglo American Equipment PerformanceMetrics, 2012) For definitions ofparameters, see Figure 3.

Figure: Freely after Anglo American Equipment Performance Metrics Time Model

Figure 3 Time definitions by Anglo American Equipment Performance Metrics

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The Performance metric (see Equation 7) isstated as The portion of the OEE Metricwhich represents the production rate atwhich the operation runs as a percentage ofits targeted rate. It is calculated as the

ratio between Actual Production Rate andTarget Production Rate, where ActualProduction Rate is the ratio betweenActual Production Achieved and PrimaryProduction (P200), whereas the TargetProduction Rate is defined as an input.(Anglo American Equipment PerformanceMetrics, 2012)

The Quality is stated as The portion of the

OEE Metric which represents the Qualityachieved at an operation as a percentage ofits targeted Quality and is calculated as

the ratio between Actual Quality andTarget Quality (see Equation 8). Both thenumerator and the denominator are statedas inputs and no calculation method forthem is provided in the Anglo AmericanEquipment Performance Metrics. (AngloAmerican Equipment Performance Metrics,

2012)

2.3.3OEEBENCHMARK

According to M. Lesshammar (1999) mostequipments OEE ranges from 40-60 %,whereas the world-class level is said to be85 %. Smith and Hawkins (2004) have

defined the world-class level at 85 % and itis composed of an Availability of 90%,Performance of 95% and Quality of 99%,which creates Equation 9.

According to Hansen (2001) very fewcompanies calculate OEE or use it tomaintain and set new priorities. He hasdefined different levels of OEE forcompanies to aim for, which can bedescribed as follows:

< 65 % Unacceptable. Money isconstantly lost. Take action!

65-75 % OK, only if improving trends

can be shown over a quarterly basis. 75-85 % Pretty good. But keep working

towards the world-class level.

According to Hansen (2001) a batch typeprocess should have a world-class OEEof >85 %, for continuous discrete processesthe OEE value should be >90 % and forcontinuous on stream processes the OEEvalue should be 95 % or better.

2.3.4OEEECONOMICS

It is often hard to measure the financialbenefits of proposed improvement projectsand it is easy to oversee important projectsand instead prioritise average projects.Bottlenecks are what prevent a process

200

000

Primary Production POverall Utilisation

Total time T

Equation 6

/=

Actual Production RatePerformance

Target Production Rate

Actual Production Achieved Primary Production


Equation 7

Actual QualityQuality

Target Quality Equation 8

90 % Equipment Availability x 95 % Performance Efficiency

x 99 % Rate of Quality = 84.6 % OEEEquation 9

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throughput and limits a plant frombecoming effective; therefore, bottlenecksshould be the first place where OEE isapplied. In order to prioritise the OEEimprovement projects relative to theaverage ones, it is important to be able toshow the financial gains. (Hansen, 2001)

Hansen (2001) has shown that there is alink between OEE and critical financialratios and that a company that understandsand applies OEE improvement projectswill harvest dividends year after year, sinceOEE improvement projects work toeliminate the root causes of problems.

According to Hansen (2001) a 10 %increase of OEE from 60 % to 66 % willgive:

21 % increase of Return on assets(ROA)

10 % increase of capacity 21 % improvement of the operating

income

He also states that starting on a low OEE,rather than on a high OEE, makes it easierto find opportunities to improve.

Ahlmann (2002) discusses the financialimplications of an increased OEE from 60 %to 80 % in Swedish industry and argues thatit shows a 20 % economic improvement.

2.4CONTINUOUS IMPROVEMENTKAIZEN ()

The term kaizen, in Japanese, literallymeans change (kai) for the better (zen).Kaizen is defined by Oxford Dictionaries as:

a Japanese business philosophy of continuousimprovement of working practices, personal

efficiency, etc..

Continuous improvement is the process ofmaking incremental improvements, nomatter how small, to achieve the lean goalof eliminating all waste that does not addany value but only adds cost.Kaizenteaches employees skills to workmore effectively in smaller groups, solvingproblems, documenting and improvingprocesses, collecting and analysing data,and also to self-manage within the peergroup. (Liker and Convis, 2012)

The concepts of Kaizen started in the earlydays of Toyota and included the nowfamous concepts of just-in-time (JIT),

process flow and quality improvements.

Kaizen can be divided into six main stepswhich became the basis for the ToyotaKaizen course developed by the companyin the 1970s. (Kato and Smalley, 2011)

1. Discover Improvement Potential

2. Analyse the Current Methods

3.

Generate Original Ideas

4. Develop an Implementation Plan

5. Implement the Plan

6. Evaluate the New Method

It has been understood that, in realtity,continuous improvements are impossiblesince some parts of the process sometimesneed to be operated in the same way as theday before. Everything cannot be changedto the better every day. Continuousimprovement is a vision, a dream, which nocompany can totally master. (Liker andFranz, 2011)

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2.4.1THE FIVE WHYS 5WHYS

One root-cause finding technique includedin the kaizen methodology is the 5 WHYs.It implies to ask why a problem exists fivetimes, going to a deeper level with eachwhy until the root cause of the problem isfound. The user of the technique shouldtake countermeasures at the deepest levelfeasible of cause and at the level that willprevent reoccurrence of the problem.(Liker and Convis, 2012)

To visualize the root causes, which may bemultiple, an Ishikawa diagram (also known

as a fishbone diagram) can be used in orderto create a clear picture of the currentsituation and to map out the possible rootcauses (see Figure 4). (Perrin, 2008)

2.5PERFORMANCE

MEASUREMENTS

Using performance measures is a

procedure aimed at collecting andreporting information regarding theperformance of an operation or individualparts thereof. This procedure can help theorganisation to define and measure thegoals it is aiming to achieve.

In the industry, performance measures aremost often denoted as KPIs (KeyPerformance Indicators). Widely used KPImetrics are, for instance, cycle time, MeanTime Between Failure (MTBF) andutilisation. (Taylor Fitz-Gibbon, 1990)

Halachmi (2005) elaborates on the logic ofreasons in support of introducingperformance measurement as a promisingway to improve performance. Thisstrengthens the motives for measuring theperformance of the operations.

Picture: Real World Project Management

Figure 4- Ishikawa diagram

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If you do not measure results, you cannot tell

success from failure

If you cannot recognize failure, you will repeat

old mistakes and keep wasting resources.If you cannot relate results to consumed

resources, you do not know what is the real

cost...

(Halachmi, 2005, p.504)

2.5.1MEAN TIME BETWEEN

FAILURES (MTBF)Mean Time Between Failures (MTBF) is ameasure of asset reliability. It is the averagetime between one failure and anotherfailure for repairable assets (see Equation10). An increasing MTBF indicatesimproved asset reliability. MTBF is bestwhen used on asset or component level andshould be performed on critical assets andtrended over time. Low MTBF numbersshould be approached with analysis (i.e.,root-cause failure analysis (RCFA) orfailure mode and effect analysis (FMEA))in order to identify how the asset reliabilitycan be improved. (Gulati, 2009)

2.5.2MEAN TIME TO REPAIR

(MTTR)

Mean Time To Repair (MTTR) is a

measure of the average time required torestore an assets back to working condition

(see Equation 11). In the context ofmaintenance, MTTR is comprised of twoparts; the first is the identification of theproblem and the required repairs; thesecond is the actual repair of the equipment.

One factor that will influence MTTR is theseverity of the breakdown; another factor isthe quality of the maintenance itself. Ahigh MTTR should be approached withgood troubleshooting methods, to quicklyidentify the root cause, and themaintenance actions should be reviewedregularly to identify improvementopportunities. (Mahadevan, 2009)

2.6VALUE STREAM

MAPPING (VSM)

Value Stream Mapping (VSM) is a lean

manufacturing technique used to analysethe flow of materials and information in asystem.

Value Stream Mapping involves all processsteps, both value added and non-valueadded ones. In that way Value StreamMapping can be used as a visual tool tohelp identify the hidden waste and sourcesof waste. Preferably, a current state map

should be drawn to document how thingsactually proceed in the process. Thereafter,a future state map should be developed toshape a lean process which has eliminatedroot causes of waste.

Rich et al. (2006) defined the seven ValueStream Mapping tools as:

Process Activity Mapping Supply Chain Responsiveness Matrix

Product Variety Funnel Quality Filter Mapping Forrester Effect Mapping Decision Point Analysis Overall Structure Maps

/MTBF Uptime Number of stops Equation 10

Equipment Downtime TimeMTTRNumber of stops

Equation 11

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2.7RACIMATRIX

In a large organisation whereresponsibilities are divided between severalparties and decisions impact many core

functions, it is important thatresponsibilities are clear and involvedifferent parties across the firm, especiallyin the decision-making process. The RACIMatrix is a method to manage decisionallocation processes (see Table 1). RACI isan acronym for Responsibility,Accountability, Consulting andInformation and stands for different rolesin the decision process. (Dressler, 2004)

Dressler (2004) defines the building blocksof the RACI Matrix as follows:

Responsibility (R) The roleresponsible for decisions that fall undertheir area of responsibility within theorganisation. This is an active andimportant role in the decision makingprocess.

Accountability (A) This role is theperson in charge of the individualtaking on the Responsibility role and

carries the accountability for thedecision made.

Consulting (C) This role is notaccountable or responsible for theconsequences of the decision made but

shall be consulted in the decisionmaking process.

Information (I) This group includesother persons in the organisations thatwill be impacted by the decision and itsoutcome shall be kept in theinformation loop.

According to Dressler (2004), the RACIMatrix is used by many effectiveorganisations to clarify ambiguous decisionareas and solve decision conflicts upfront.This to give people a clear understandingabout their roles in regards to contributingto an efficient decision making process.

Person A Person B Person C Person D Person E

Decision A A C I R

Decision B R A I C

Decision C C R A I

Table 1 An example of how a RACI Matrix can be created. R=Responsible,A=Accountable, C=Consulted, I=Informed.

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2.8PLATINUM

Platinum was discovered in 1735 in SouthAmerica by Ulloa and can be foundoccurring naturally, accompanied by small

quantities of iridium, osmium, palladium,ruthenium and rhodium, all of whichbelong to the same group of metals, thePlatinum Group Metals (PGM) (The PGMDatabase, 2012).Platinum is one of therarest elements in the Earth's crust and hasan averageabundance ofapproximately5g/kg. Other

precious metals likegold, copper andnickel denoteconcentration in oresin percentages, butplatinum denotesthis in parts permillion. Based on atypical conversionrate of 25%, 14 tons

of ore are required to produce 10 grams ofplatinum. (Probert, 2012)

Platinum, iridium and osmium are thedensest known metals. Platinum is 11%denser than gold and about twice theweight of the same volume of silver or lead.Platinum is soft, ductile and resistant tooxidation and high temperature corrosion.It has widespread catalytic uses. (Platinum

Today, 2012)

In 2009, approximately 45% of the world'splatinum was used in automotive catalyticconverters, which reduce noxious emissionsfrom vehicles. Jewellery accounted for 39%of demand and industrial uses accountedfor the rest. (Anglo Platinum, 2011)Examples of its industrial uses are high-temperature electric furnaces, coating

missile nose cones, jet engine fuel nozzlesand gas-turbine blades. These components

must perform reliably for long periods oftime at high temperatures under oxidisingconditions. Platinum is also used as acatalyst in cracking petroleum products.Currently there is a high interest in the useof platinum as a catalyst in fuel cells and inantipollution devices for automobiles.(ThePGM Database, 2012)

The price of platinum has varied widely; inthe 1890s it was cheap enough to be used

to adulterate gold. But in 1920, platinumwas nearly eight times as valuable as gold.The spot price on 2012-08-15 wasapproximately 1395 USD/oz t (1 oz t =

31.103 g), which can be compared to thegold price for the same day; 1594 USD/oz t(Kitco, 2012).

A comparison between platinum and itsmore well-known periodic table neighbourgold can be viewed in Table 2.

Platinum Gold

Chemical Symbol Pt Au

Atomic number 78 79

Atomic weight 195.084 196.967

Density (g/cm3) 21.45 19.30

Melting point (C) 1769 1064

Vickers hardness

(MPa)

549 216

Electrical resistivity(nohm-cm at 20C)

105 22.14

Tensile strength(MPa)

125-240 120

platinum

78

Pt195.08

Figure 5Platinum inthe periodic system

Table 2- A comparison between platinum andgold.

Freely from The PGM Database (2012)

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2.9EXTRACTION OF

PLATINUM-GROUP METALS

(PGMS)

To get pure platinum a long process has tobe followed. The extraction of platinum-group metals is described by Crundwell, etal. (2011) in the following five steps:

Step one is to mine ore with a highconcentrate of platinum-group metalswhile leaving rock lean in platinum-group metals behind.

Step two is to comminute the mined oreinto powder and isolate the platinum-group elements in the ore by creating aflotation concentrate consisting ofnickel-copper-iron sulfides that has ahigh content of platinum-groupelements.

Step three is to smelt and convert thisconcentrate to a nickel-copper sulphide

matte that is richer than theconcentrate in platinum-group metals.

Step four is to produce a, eitherthrough magnetic concentration or by

leaching separate platinum-groupelements in the converter matte, veryrich platinum-group metal concentratecontaining about 60% platinum-groupelements.

The last step is to refine thisconcentrate to individual platinum-group metals with purities in excess of99.9%.

In general the concentrating andsmelting/converting are done in or near themining region while the refining is done inthe region or in distant refineries.(Crundwell et al., 2011)

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CHAPTER THREE

METHODOLOGYIn this chapter the methodology of the thesis will be presented and analysed in order for the

reader to better understand the approach leading up to answering the research questions andfulfil the project scope. First, the research strategy and approach are presented. Next, detailsare given regarding the data collection methods used in the thesis project. Finally, reliability,

validity and ethical aspects of the study are discussed.

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OEE as a measure, the study of OEE andtherefore also TPM became a natural partof the studies. TPM also led the path tostudies of other maintenance fields, such asLean maintenance, which is closely linkedto improving productivity. The studies ofOEE were broadened by studying theeconomic factors associated with improvingOEE numbers, which also providedarguments for working with OEEimprovements.

After core studies regarding the process ingeneral and TPM methodologies, methodsfor identifying bottlenecks such as Value

stream mapping, were studied more closelysince they offered a very clear path toevaluate the production chain and directthe improvements to the right sections.

The remaining part of the literature studywas conducted during the empirical studyon site in cases where the empirical findingsresulted in new theoretical aspects to study.This is also in line with the chosen

abductive approach (Bryman & Bell, 2011).

3.3.1DATA COLLECTION

METHODS

The data needed for this thesis has mainlybeen collected through interviews,observations and by using secondary data.Most of the quantitative data was collectedthrough gathering data from the PI

database whereas the qualitative data wascollected through semi-structuredinterviews, which is also the usual firststep of engagement in the actionresearch approach (Scheinberg, 2009).

OBSERVATIONS

In order for the researchers to acquire theirown understanding of the situation,observations were conducted on site. This

helped with the understanding of thespecific steps in the production process as

well as the daily work and methods used.The observations also acted as indicationsof what theoretical fields were interestingfor further study and in that way led to amore focused literature study.

INTERVIEWS

A major part of the qualitative data wascollected through numerous interviews withpersons involved in the production processas well as management. The character ofthe interview was dependent on theposition of the interviewee and the type ofinformation sought (qualitative or

quantitative). The basic approach was anunstructured interview in order for theinterviewee to further elaborate on thequestions asked. In an unstructuredinterview, the interviewers do not followa strict structure of questions, but insteadmight have only one or a few questions toanswer. The interview therefore resemblesa conversation. (Bryman & Bell, 2011)

SECONDARY DATAThe major part of the data is secondary inthe sense that it stems from informationfrom metallurgists and specialists, and thatno long-term observations beside themachines have been conducted. Still, thedata is in most cases measured over a longperiod of time, which in a sense increasesits accuracy. This gathering of data alsolimited the cost of the project, though the

information might be difficult tounderstand and interpret and there isalways a risk that some importantinformation may be left out of the materialhanded to the researchers (Bryman andBell, 2011). The process data used forcalculation can also be seen as secondarydata. The process data comes from the PIdatabase were more than hundreds ofthousands of different measurement points

are logged.

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3.4RELIABILITY

The reliability concerns the results of theproject and whether they are repeatable ornot (Bryman & Bell, 2011). Achieving high

reliability when using action research is adifficult task since the purpose is to changepeoples mind-set and the environment inwhich they act. By taking field notesthroughout the entire project and also bykeeping a diary, the researchers intention

has been to write down all importantaspects of the thesis. The research is basedon a combination of quantitative andqualitative data compared with existing

methodologies within the area of increasingproductivity. This approach ensures thatthe results are best practice from atheoretical point of view applied in thespecific context.

3.5VALIDITY

The validity of the project deals with the

issue of whether the right aspects werestudied in order to answer the researchquestions. Bryman and Bell (2011) proposeto measure four different aspects in orderto determine the validity of the thesis;construct validity, internal validity, externalvalidity and ecological validity.

3.5.1CONSTRUCT VALIDITY

The construct validity is regarded as highsince data triangulation was used in caseswhere previous measurements werecompared with data collection on site.Since the researchers have spent extensivetime on site, the possibility of measuringcritical aspects on several occasions wasgood.

3.5.2INTERNAL VALIDITY

The internal validity deals with the issue ofcausality. The internal validity is highly

relevant to this thesis since one researchquestion aims to explore how certainchanges affect the productivity of theprocess. The cause and effect relations areclosely linked to the internal validity andthese have been tested throughtriangulation and pattern matching. Thevalidity has also been ensured by using wellknown methods and tools such as TPM,OEE and Lean.

3.5.3EXTERNAL VALIDITY

At first, the external validity can beregarded as rather low since the study aims

at improving the specific site in question.However, one of the research questions(number 1, see section 1.6) deals with howto develop a method, applicable at ageneral plant, to define and rank processunits, which gives the thesis an increasedexternal validity. To create an externalvalid thesis, proven methods have beenused and general equations and definitionshave been presented. This will help others

to interpret the content of the thesis intoother contexts and therefore increase theexternal validity. The aim for theresearchers has been to develop anaggregated method which is generic andcan be successfully implemented at similarplants.

3.5.4ECOLOGICAL VALIDITY

The ecological validity concerns whetherthe findings are applicable to everyday life.In this case, the findings are highlyapplicable to day-to-day operations in theprocess. Since the data has been collectedfrom the daily operations andimprovements have been done in the actualproduction equipment, even though in asmall scale at first, the ecological validityhas to be considered as high. The pitfall

might be that of the Hawthorne studies,which implies that people perform better

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just because they are being studied. Due tothe long time period and the size of theproduction system this has to be consideredas a low risk, but should still be kept inmind in projects of this kind.

3.6ETHICAL ASPECTS

The researchers believe that a well-functioning mining industry in the regionbenefits all stakeholders and that this thesisshould be a part of that development. Theaim of this thesis is ultimately to increasethe competitiveness of the company and

the region, which has been a guidelinethroughout the project. Interviewees andother participants in this research havebeen informed about the purpose and havehad the option to decline. This is to ensurethat the participants do not feel harmeddue to lack of informed consent, invasion ofprivacy or deception (Scheinberg, 2012).

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CHAPTER FOUR

DATA

This chapter will first present how the quantitative and qualitative data has been gathered.Next, the empirical data, including a process map, presentation of the units included in theproject as well as some remarkable facts about the comminuting units, are presented. The

quantitative and qualitative data has, together with the empirical data, served as input to theobtained results of this Masters thesis project.

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4.1QUANTITATIVE DATA

Most of the quantitative data has beenextracted from a highly technologicalprocess data system which collects and

stores process data continuously in adatabase. This is known as the PI-systemand PI-database. The PI-database consistsof hundreds of thousands of measurementpoints, called tags, which can bemanipulated and combined in almostlimitless combinations.

To provide a picture of how the developedtool (called the Overall Productivity Tool(OPT)) uses tags from the PI-database tocalculate the required metrics, see Table 3.The table displays the measures used for

process area 406 to perform the requiredcalculations.

Quantitative data has also been gatheredthrough interviews and observations. Whenapplicable, technical specifications havebeen gathered from original plant drawings.

UNIT MEASURE UNIT MEASURE

HPGR Crusher

406-CR-001Power [kW]

Conveyor

406-CV-003Running [ON/OFF]

HPGR Screen 1

406-SC-001Running [ON/OFF]

Conveyor


HPGR Screen 2

406-SC-002Running [ON/OFF]

Conveyor


HPGR Silo Feeder 1

406-FE-001Running time [min]

Conveyor


HPGR Silo Feeder 2

406-FE-002Speed [%]

Conveyor


HPGR Feed Bin

Feeder 1

406-FE-003

Speed [%]Belt scale

406-WT-010BMass [t]

HPGR Feed Bin

Feeder 2 406-FE-004Speed [%]

Belt scale

406-WT-402Mass [t]

HPGR Screen Feeder 1406-FE-005

Speed [%]Belt scale406-WT-416

Mass [t]

HPGR Screen Feeder 2406-FE-006

Speed [%]Belt scale406-WT-433

Mass [t]

Conveyor406-CV-001

Running [ON/OFF] Lynxx camera(placed at 406-CV-007)

Size [mm]

Conveyor


Table 3The data extracted from the PI-database in order to calculate the OEE measures for area 406

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4.2QUALITATIVE DATA

The qualitative data has been gatheredthrough unstructured interviews. In anunstructured interview, the interviewers do

not follow a strict structure of questions,but instead might have only one or a fewquestions for the interviewee (Bryman &Bell, 2011). The interview thereforeresembles a conversation. The unstructuredpersonal interviews have been conductedboth in Sweden and in South Africa.

During the pre-study in Swedenunstructured interviews were held with the

following persons at Chalmers Universityof Technology from August 15th untilSeptember 10th:

Prof. Magnus Evertsson, Chalmers

Rock Processing Systems

Dr. Erik Hulthn, Chalmers Rock

Processing Systems

Gauti Asbjrnsson, PhD student,

Chalmers Rock Processing Systems Johannes Quist, PhD student, Chalmers

Rock Processing Systems

Torbjrn Ylip, Senior Lecturer in

Producton Systems

Ludvig Lindlf, PhD student at the

Division of Operations Management

During the time spent at the University ofCape Town in South Africa, unstructuredinterviews were held with Dr. AubreyMainza, Department of Minerals Research,from September 12th until December 20th.

Unstructured interviews were held on sitewith persons with the following positionsfrom September until mid-December 2012:

Plant Manager Technical Manager

Metallurgist for Dry Section, Milling &

Classification and Flotation

Metallurgist Graduates for Milling &

Classification and Flotation

Engineering Specialists

Production Leaders

Operators

Planners

The following persons at Anglo AmericanPlatinum in Johannesburg have beenconsulted during the project (September -

mid-December 2012):

Head of R&D

Head of Control and Instrumentation

Head of Engineering

Leader Process Control Engineer

Control Engineer

Observations have been made on site fromSeptember to December 2012.

4.3EMPIRICAL DATA

The empirical study serves to give thereader an understanding of the currentstate in interesting areas of the operations,both in production technical and inorganisational terms. Along with thetheoretical framework it will serve as a

basis for the analysis. The data presentedhas been captured during interviews andobservations on site.

4.3.1ORGANISATIONAL CHART

To understand the organisational structureat Mogalakwena North Concentrator, anorganisational chart (Appendix I) over thedivisions involved in areas critical for thisproject, has been developed. This chartformed the basis for an understanding ofthe divisional and inter-divisional processes.

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4.3.2PROCESS MAP

The comminution circuit is divided intoseven sub-areas (102, 401, 405, 406, 407, 408and 440, see Figure 6). These areas are

mapped in more detail in Appendix I.Except for the information gathered frominterviews and observations; this mapcontains information from the originalplant drawings.

4.3.3UNITS IN A CONCENTRATOR

PLANT

In the following section, the different typesof process units included in the project andtheir dedicated tasks in the plant will bedescribed.

COMMINUTION

Comminution is a part of the concentratorprocess and is defined as:

The action of reducing a material,especially a mineral ore, to minute particles

or fragments.(Oxford Dictionaries, 2012)

Units dedicated to comminution in aconcentrator are, for instance, the primarycrusher, secondary crusher, High PressureGrinding Roll crusher (HPGR) and the ballmill.

CONVEYOR

A conveyor is a unit which has the purposeof moving or transporting bulk material or

Figure 6- Process map displaying area 102-408 at MNC (For more detailed maps, see

Appendix I)

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objects in a path predetermined by thedesign of the conveyor. The conveyor canbe horizontal, inclined or vertical in itsdesign. At MNC, all bulk transports areperformed by conveyors and the total

length of all conveyors is approximately9000 metres.

CLASSIFIER

A classifier is a unit which classifies thematerial physically by separating it basedon its particle size. At a concentrator thiscan be performed by, for instance, a grizzly,screen or cyclone, all which have the samepurpose but perform the separation ofmaterial in different ways.

FEEDER

A feeder is a unit that puts material inmotion. Its purpose is to regulate theamount of material that, for example, is fedinto a crusher or from a storage silo onto a

conveyor.

4.3.4AREA AFFILIATIONS OF

UNITS

The following section will present the nameand type of the units included in the projectbased on their area affiliation. Thepresentation order of the following tables isequal to the material flow order in the

process.

AREA 102

Table 4The name and number of units in process area 102

TYPE OF UNIT NO. OFUNITS

NAME

Comminution unit 1 102-CR-001 Primary crusherFeeder 2 102-FE-001 & 102-FE-002Conveyor 2 102-CV-001 & 102-CV-002

Classifier 0 -

AREA 401

Table 5-The name and number of units in process area 401


NAME

Comminution unit 0 -Feeder 6 401-FE-001 - 401-FE-006Conveyor 1 401-CV-001Classifier 1 401-GY-001 Grizzly

AREA 405

Table 6- The name and number of units in process area 405


NAME

Comminution unit 3 405-CR-001 405-CR-003 Secondary Crushers1,2,3

Feeder 5 405-FE-001 405-FE-005Conveyor 6 405-CV-001 405-CV-006

Classifier 2 405-SC-001 & 405-SC-002 Secondary Screen 1 & 2

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AREA 406



NAME

Comminution unit 1 406-CR-001 HPGR CrusherFeeder 6 406-FE-001 406-FE-006Conveyor 7 406-CV-001 406-CV-007Classifier 2 406-SC-001 & 406-SC-002 HPGR Screen 1 & 2

AREA 407



NAME

Comminution unit 0 -Feeder 2 407-FE-001 & 407-FE-002Conveyor 2 407-CV-001 & 407-CV-003Classifier 0 -

IN TOTAL

Table 9- The total number of units in process included in this project


Comminution unit 5

Feeder 21Conveyor 15Classifier 5

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4.3.4COMMINUTION UNIT FACTS

Since Mogalakwena North Concentrator isdesigned to be the worlds largest single

stream platinum concentrator (Mining

Weekly, 2008), it has several remarkableunits.

CRUSHERS

The circuit includes in total three crushingsystems one primary crusher, threesecondary crushers and one tertiary crusher(HPGR).

The primary crusher, which is the largestprimary gyratory crusher in the world,weighs 480 tonnes, is 60-feet (18.3 m) indiameter and has a 1 MW motor. Thecrusher can handle ore pieces up to onesquare sectional metre and has a maximumcapacity of 3000 tonnes per hour.

The secondary crusher system consists ofthree identical hydrocone crushers withdifferent settings due to the different sized

materials with which they are fed. Thisdesign makes the plant setting quite rareand requires customised equipmentperformance calculations.

The tertiary crusher is a HPGR (HighPressure Grinding Roll) crusher, whichutilises two 100 tonne rolls, one fixed inposition and the other moving horizontallyto adjust the gap between them, to crush

the ore. Mogalakwena North Concentratoris the first platinum plant in the world toutilise a HPGR crusher for this purpose.

MILLS

The primary and secondary mills are thetwo first gearless mill drives (GMD) at

Anglo Platinum. The drives are powered bya 17.5 MW motor, five times as big as asimilarly-sized throughput mill. When theplant was commissioned in 2009 theseGMDs, with a diameter of 26 feet (7,9 m),

were the largest installed in the world..(Probert, 2012)

LYNXX CAMERAS

The plant has five Lynxx cameras, whichoptically determine the particle size of thematerial which is being transported on aconveyor. The map displaying the installedpositions can be viewed in Appendix III.

4.4VALUE STREAM MAPS

The Value Stream Mapping process isbased on the interview results andobservations and consists of individualmaps of the current state of processes andthe operations found to be of interest forthis project. The maps were developed togive an enhanced understanding of the

current state of the processes and arepresented here to give the reader anenhanced understanding of the state.

CRUSHER AND MILL STOPS

REPORTING PROCEDURE MAP

An analysis of the production processcalled Pain analysis has been developed bythe Masters thesis writers. To be able toperform this analysis, data from crusherand mill stops is required. To understandthe internal reporting process for thesereports the entire process was mappedaccordingly (Figure 4).

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The Crusher and Mill Stops ReportingProcedure Map displays the procedure forreporting the stops. It can be seen that theinput to the report is a daily activity,

whereas the submitting of the report isdone on a monthly basis. This can beregarded as a poorly synchronisedprocedure and will eventually result inmissing or delayed data regarding the stops.The analysis of crusher and mill stoppageswill, due to this process, only be possibleonce a month, which is insufficient for thePain analysis.

JOB CARD INSPECTIONS MAP

A plants performance is highly affected bythe quality of the performed maintenancework. Due to this, the current process fordaily maintenance work at the plant wasmapped to acquire an understanding ofhow it works. The map of the job cardinspections can be viewed in Appendix IV.

Figure 4Current Crusher and Mill Stops Reporting Procedure Map

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CHAPTER FIVE

RESULTS

This chapter will present the results that have been obtained in the project. The results arepresented in three distinct sections Define, Develop and Design. The same sections are used

in the discussion and conclusions in order for the reader to more easily follow the red thread.

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1

31 2Definea calculation

model for OEE &other equipmentperformance metrics

in a single streamprocess

Developa tool thatcalculates OEE &other equipment

performance metricsin real time

Designa method

describing how to usethe tool output in theorganisation withprimary focus on

finding root causes

Define amodel

CHAPTER 5INTRODUCTION TO RESULTS

Figure 7Project phases

The results are presented according to thethree distinct project phases (see Figure 7).The first phase was to define a calculationmodel for OEE and other equipmentperformance metrics. The second phasewas to develop a tool (OPT) which uses thecalculation model to perform real timecalculations of OEE and other equipmentperformance metrics. The third phase wasto design a methodology to use in theorganisation to find root causes toproductivity limiting issues. Moreover, thischapter includes a presentation of how tocalculate OEE in a General Single StreamProcess and results from the new procedurefor Crusher and Mill Stops Reporting thatwas introduced at MNC by the twoMasters thesis writers.

5.1CALCULATION MODEL

In the following

section, the resultsof the first phase(see Figure 8) ofthis project will bepresented. Thispart contains thecalculation modelfor OEE and otherequipment performance metrics in a 24/7single stream comminution process.

The calculation model covers the fivemetrics; OEE, Availability, UtilisedUptime, Mean Time Between Failure(MTBF) & Mean Time To Repair (MTTR)and Pain (see Figure 9). The finalcalculation for these metrics will bepresented in the following sections. Thecalculations are based on the AngloAmerican Equipment Performance Metricsdefinitions and have taken inspiration froma customised calculation model developedby the Masters thesis writers (see section

5.4) to suit the process of MNC, since theAnglo American definition is notcomprehensive enough to be used in thisprocess. However, since it is a companystandard, the aim has been to use it asextensively as possible and it has been awish from the company not to deviate fromthe standard whenever possible.

Figure 8Projectphase 1 - Define

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Figure 9- Equipment metrics included in the calculation model

5.1.1FINAL OEECALCULATION

The final OEE equations used in allcalculations will be presented in this section.

The metrics consist of three parts - OverallUtilisation, Performance and Quality (seeEquation 12). The three components ofOEE can also be used as individual metrics.The components of the OEE equation arepresented in the following sections.

OVERALL UTILISATION

To determine the utilised time of a unit, the

ratio between Primary production time andTotal time is used. Primary production timeis defined as Time equipment is utilised

for production and Total time is defined

as The total possible hours available.

These definitions are taken from the AngloAmerican Equipment Performance Metrics.For explanations of the equationcomponents, see Figure 10.

To clarify, Overall Utilisation is the metriccorresponding to the general OEEcalculations measure known as Availability,

displaying the equipment usage, howevernotcalculated in the same way or with thesame result.

PERFORMANCE

Equipment Performance is calculatedaccording to the Anglo AmericanEquipment Performance Metrics as the

ratio between Actual Production Rate andTarget Production Rate. The Performanceessentially indicates how efficiently the unithas been working, i.e. to what degree theunit has been doing things in the correctway.

OEE Overall Utilisation x Performance x Quality Equation 12

Primary ProductionOverall Utilisation

Total time Equation 13

/=

Actual Production RatePerformance


Actual Production Achieved Primary Production


Equation 14

OEE

OverallUtilisation

Performance Quality

AvailabilityUtilisedUptime

MTBF&

MTTR

ProcessPain

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The Actual Production Rate is the ratiobetween Actual Production Achieved andPrimary Production, which both can becalculated with data drawn from the PI-database. The Target Production Rate,however, is an input measure which has to

be defined for every single unit.

QUALITY

The method to calculate the productQuality was developed by the Masters

thesis writers. The Quality looks at theparticle size and shows to what extent theparticle size is below the targeted size. Thetarget and actual particle size concerns the

P80 value, which is a commonly used valuein the comminution industry. P80 is definedas the size where 80 percent of the materialpasses a certain upper size limit. The

equation compares the Actual Particle Sizeat a certain point in the process to theTarget Particle Size for that point (seeEquation 15).

The Quality is defined as the mean

deviation above Target Size as a percentageof the Target Size (see Figure 11). Thisimplies that all particles below target sizeresult in zero deviation, hence a 100%Quality. To achieve the metric Qualitysuitable for the OEE calculation and notthe deviation, the ratio is subtracted from 1.For instance, if all particles are belowTarget Size, the Quality will be 100%. Ifsome particles are above Target Size, the

equation will compute their individualdeviation from the Target Size. Togetherwith the particle sizes below the TargetSize, which all are regarded as having no

1 Mean deviation from Target Size

QualityTarget Size

1

1

n

i i

Deviation from target

Ta

siz

rget

e

n

Size

Equation 15

Figure: Freely after Anglo American Equipment Performance Metrics Time Model

Figure 10- Time definitions by Ang

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