© mining consultancy services (pty) ltd. 2016

Productivity

Optimisation

© Mining Consultancy Services (Pty) Ltd. 2016

REF: 0367

Content


– Brief company background

– Productivity Optimisation Project (POP) methodology

through two case studies:

– Underground case study

– Opencast case study

– Technology (hardware and software) currently in operation

and commercially available

MCS Introduction


MCS has a total staff compliment of 40 with offices in Johannesburg (South Africa),

Brisbane (Australia), Moscow (Russia). Started in 1988 in South Africa.

SA Project Examples - Optimization


Project Client Description

Greenside AATCFirst Productivity Optimisation Project done using the combination of machine monitoring and process based

management

Greenside AATCAimed at optimisation new sections and taking productivity from 1 million tonnes per annum per CM section to 1.4

million tonnes per CM section

Waterval Anglo Platinum Aimed at optimising production from the mine

Townlands Anglo Platinum Oversee new mechanisation projects

Goedehoop - Vlaklaagte shaft AATC POP Project on 5 sections

Goedehoop - Hope shaft AATC POP Project on 5 sections

Bank Colliery AATC POP Project on 3 sections

New Denmark AATC POP Project on 3 sections

Kriel Colliery AATC POP Project on 2 sections

Anglo Coal AATCOptimisation of all CM's collieries where POP's was done. This includes 23 fully mechanised sections over 7 shafts on

4 mines

Arthur Taylor Colliery Xstrata Coal SA POP on 4 sections and support contract

Tavistock Colliery Xstrata Coal SA POP on 3 sections and support contract

Boschmans Colliery Xstrata Coal SA POP on 5 sections and support contract

South Witbank Colliery Xstrata Coal SA POP on 3 sections and support contract

5-Seam Xstrata Coal SA POP on 2 sections and support contract

Douglas Colliery BHP Billiton Energy Coal Series of 3 POP projects on 7 sections and support contract

Khutala Colliery BHP Billiton Energy Coal Series of 4 POP projects on 14 sections and support contract

Gloria (Koornfontein) Colliery BHP Billiton Energy Coal Two sections

Middelbult Colliery Sasol Mining POP on 9 section and support contract

Syferfontein Colliery Sasol Mining POP on 10 sections and support contract

Bosjesspruit Colliery Sasol Mining POP on 11 sections and support contract

Brandspruit Colliery Sasol Mining POP on 9 sections and support contract

Twistdraai Colliery Sasol Mining POP on 11 sections and support contract

Sigma Colliery Sasol Mining POP on 4 sections and support contract

Sasol Wide Sasol Mining POP and support contact work on all sections

Kangra Kangra Coal Holdings POP on 5 sections

Mooiplaats Coal of Africa Limited POP on 5 sections

Tweefontein Glencore Open cast monitoring and optimisation

Our Mission


“Combining world leading Experience and

Innovation to deliver best practice Evaluation

in the pursuit of Value Adding Excellence”

Experience

Innovation

Evaluation

Case study approval


Our sincerest thanks to Glencore Tweefontein division for

allowing us to use their reports for the underground and

opencast Productivity Optimisation Project case studies.

Sustainable KPI Improvement


3 pillars to effective and sustainable Process Improvement

The holistic approach to

Productivity Optimisation

has consistently delivered the

best results.

It is based on the INTER-

CONNECTEDNESS of all the

aspects: leaving one out will

erode the effectiveness and

sustainability of the process.

Monitoring

Training

Improvement

Process

Spirit of KPI Improvement


BEST

SHIFT

BEST

WEEK

AVG.

BEST

MONTH

AVG.

ANNUAL

NORM =CONTINUAL

IMPROVEMENT

EMBRACE THE

DESIRE TO BE

THE BEST!

=

Standardized KPI’s


When KPI’s are understood and trusted by all

personnel - they start driving sustainable

behavioural (process) change.

Daily feedback is required to ensure gains

that have been made are sustained.

Since everybody is measured on the same

basis it creates competition and PEER

PRESSURE to improve

U/G Case study


Improvement process


Once a week the supervisors of every section present their results and action plans to the mine manager for review.

Action plans from

previous week

New actions Identified

Results of the previous & current week

U/G data acquisition


Section KPI’s for the week


Production KPI's Avarage 2014 Avarage 2015 Ngala Rhinos Inyathi Tigers w k avg Sisonke shifts

First sump late 9 10 2 -7 -6 0 -3 30

Last sump early 15 15 0 -1 0 -1 0 -5

Avg load time (sec) 82 77 77 77 53 72 69 81

Avg aw ay time (sec) 78 73 97 67 85 72 80 71

Avg relocation time (min) 22 17 18 19 16 13 16 17

Avg no. of relocs per shift 3,8 3,7 3,5 3,2 5,3 4,8 4,2 2,8

Avg TTPMC 3,77 2,6 3,28 1,98 2,81 2,26 2,6 1,07

Production rate 360 384 372 450 470 450 435 426

Time summary

Production time 186 224 191 196 164 247 197 100

Total tram time 142 78 101 79 117 116 103 86

FS/LS total lost time 24 25 2 -8 -6 -1 -3 25

Total dow ntime 200 137 149 153 96 63 118 207

Total minutes 359 378 443 420 371 425 415 445

Variance -192 -45 21 45 76 35 44 -38

Shifts w ith usable data 10 10 10 8 6 4

Avg booked tonnes per shift 1160 1484 1162 1458 1299 1892 1429 648

Dow ntime summary

Engineering DT 68 41 71 72 61 7 55 52

Operational DT 85 57 42 58 27 46 43 20

Section Belt DT 12 6 14 0 6 3 6 0

Trunk Belt DT 24 19 22 23 2 3 13 0

Shaft Belt DT 0 0 0 0 0 0 0 0

Outside DT 11 14 0 0 0 4 1 135

Total Dow ntime 200 137 149 153 96 63 118 207149

0

14

15

2

61

57

840

291

-140

36

149

139

107

349

2,2

3,43

75

29

21

90

Avarage 2013

15

Week report - Week 40 2 seam

6-Week KPI report for a crew


Tigers BProduction KPI's Latest targ Week 35 Week 36 Week 37 Week 38 Week 39 Week 40 6 w eek avg

First sump late 0 0 -3 10 30 -2 -4 9

Last sump early 0 3 -1 -1 -4 -1 -4 -1

Avg load time (sec) 75 71 74 75 78 72 75 74

Avg aw ay time (sec) 75 78 81 72 62 75 73 73

Avg relocation time (min) 20 16 17 14 19 17 13 16

Avg no. of relocs per shift 4,2 3,8 5,5 3,5 5 5,5 4,6

Avg TTPMC 2,8 2,19 2,4 2,22 1,89 2,13 2,45 2,21

Production rate 385 435 418 441 463 441 438 441

Time summary

Production time 230 119 206 245 176 144 262 187

Total tram time 100 94 92 111 71 97 130 99

FS/LS total lost time 0 3 -4 9 26 -3 -8 8

Total dow ntime 125 91 174 55 126 89 47 96

Total minutes 460 307 468 420 430 327 431 390

Variance 0 152 -9 40 32 133 30 69

Shifts w ith usable data 5 4 4 4 5 4 4

Avg booked tonnes per shift 1477 947 1471 1850 1388 1080 1961 1416

Dow ntime summary

Engineering DT 45 11 0 0 38 22 14 14

Operational DT 45 27 60 31 24 4 19 27

Section Belt DT 15 2 0 0 2 16 6 5

Trunk Belt DT 15 0 16 0 18 22 0 9

Shaft Belt DT 0 40 86 24 28 23 0 33

Outside DT 5 11 12 0 16 2 8 8

Total Dow ntime 125 91 174 55 126 89 47 96

Scoring tool per crew / supervisor


Pos

1

2

3

4

5

6

7

8

POS

7,92 2 7 8 1 0,1

2N. Khati and

G.Snyman52,9

3E Mathe and

W.Scott51,5

Top S/O TUGO 2 Seam

ShiftbossCombined

Total %

1 R. Khoza and N.Britz 61,8

52 5,2 21,8

Top Team TUGO 2 - Week 40

2 23 70 7 16

Rhinos B 9 0 2 27

Inyathi A 7 2

4D. Lebese and P.

Nhlapho45,0

Ngala B

4,4 11,6

Tigers A 7 1 3 22 40 4 18

23,3

Ngala A 5 1 5 16 44

82 8,2 13,8

Rhinos A 9 0 2 27 37 3,7

3 27

Inyathi B 7 1 3 22

Total

scoreVariance Penalty points Points total

Tigers B 10 0 1 30 30

Team +3 points +1 point 0 points

0,1 7,9Ngala B 2 2 7 8 1

8,2 13,8

Ngala A 5 1 5 16 44 4,4 11,6

Inyathi B 7 1 3 22 82

4 18

Inyathi A 7 2 2 23 70 7 16

Tigers A 7 1 3 22 40

3,7 23,3

Rhinos B 9 0 2 27 52 5,2 21,8

Rhinos A 9 0 2 27 37

Penalty points Points total

Tigers B 10 0 1 30 30 3 27

Team +3 points +1 point 0 points Total Variance

Combines Shift Overseer scores


Individual shift overseer score


Opencast data acquisition


MonitoringDragline

Report

Excavator

ReportTruck Report

Primary fleet currently included


Primary Machines

Loading Area(Bin)

Trucks

Processing(Plant)

Dragline Shift report and KPI’s


Dragline Scoring tool


Target Cycle 18 Cycle 19 Cycle 20 Cycle 21 Cycle 22

First Swing Late(min) 0 3 44 20 31 0 3

Last Swing Early(min) 0 28 114 22 144 122 0

Number of Swings 500 440 394 398 372 417 0

Operational Delays 120 185 141 179 124 104 3

Avg cycles per cycling hour 60 58,69 60,31 57,24 56,86 57.79 1

Avg TCM 24000 20068,4 18734,7 18351,78 16784,64 21091 0

Avg Bucket fill Time 16 14,4 3

Total 10



Number of Swings 500 492 373 343 416 476 1



Avg TCM 24000 23822,64 17131,89 16234,19 20421,44 24076 3


Total 12



Number of Swings 500 465 322 414 398 475 1


Avg cycles per cycling hour 60 56 52,11 60,44 59,65 61,68 3

Avg TCM 24000 21613,2 15571,92 20687,58 20174,62 24780 3

Avg Bucket fill Time 16 14 3

Total 13



Number of Swings 500 435 379 379 420 486 1



Avg TCM 24000 20636,4 18984,11 18169,26 19882,8 24081 3


Total 9

2

1

4

7

5

8

6

Dragline

K Patience

Siphiwe

Zikalala

William

Makopo

Scoring Tool Report For Dragline

From 2016/11/07 To 2016/11/20: Cycle 22

Shifts

Worked

Total

Points

Position

A Ngwenya

3

TOC – Pit …. With 2 Excavators


Target Cycle 18 Cycle 19 Cycle 20 Cycle 21 Cycle 22 Target Cycle 18 Cycle 19 Cycle 20 Cycle 21 Cycle 22

First Load Late(min) 7:30 0 67 70 154 106 7:30 4 83 37 144 70 88Last Load Early(min) 18:30 -1 233 167 91 91 18:30 21 42 113 175 235 163Loads per hour 14,25 13,53 0,69 0,91 2,78 15,4 18,62 9,89 12,98 5,72 3,46 20,7 18,05Operational Delays 120 13 11 0 0 110 120 24 18 12 69 80 95Number of loads 114 137 7 10 30 123,5 149 102 120 61 33 165,8 144,65Avg eBCM 6061 6203 326 450 1377 1485 8030 4615 5415 2781 1492 472 978,5

Total 9 9 18

First Load Late(min) 7:30 47 16 12 36 139 7:30 62 63 114 6 26 82,5Last Load Early(min) 18:30 66 10 244 25 125 18:30 72 46 98 125 228 176,5Loads per hour 14,25 8,31 9,84 5,27 2 8,5 18,62 6,28 3,37 5,57 3,86 16,4 12,45Operational Delays 120 0 0 29 0 132 120 19 0 24 11 77 104,5Number of loads 114 88 98 48 20 68,4 149 65 35 50 35 131,4 99,9Avg eBCM 6061 3997 4447 2187 933 795 8030 2947 1582 2250 1607 585 690

Total 1 3 4

First Load Late(min) 7:30 -10 0 189 75 52 7:30 8 39 43 71 108 80Last Load Early(min) 18:30 78 68 9 2 48 18:30 -1 100 25 82 0 24Loads per hour 14,25 12,1 5,38 6,6 6,32 16,9 18,62 13,6 9,49 5,92 4,43 19,8 18,35Operational Delays 120 34 19 79 54 172 120 33 63 53 43 94 133Number of loads 114 107 56 59 62 135,9 149 116 85 48 40 158,3 147,1Avg eBCM 6061 4837 2558 2655 2817 3127 8030 5231 3841 2160 1800 4792 3959,5

Total 6 12 18

First Load Late(min) 7:30 126 80 54 -3 52 7:30 16 67 65 65 12 32Last Load Early(min) 18:30 1 4 162 50 10 18:30 16 80 139 7 0 5Loads per hour 14,25 11,8 7,75 5,59 4,66 18,5 18,62 10,62 9,66 8,01 11,34 20,6 19,55Operational Delays 120 51 21 19 69 117 120 65 115 7 113 75 96Number of loads 114 106 70 43 43 148,6 149 97 81 57 92 165 156,8Avg eBCM 6061 4770 3183 1968 1962 2550 8030 4380 3667 2565 4149 5310 3930

Total 10 12 22

Scoring Tool Report For EX301 & EX302

From 2016/11/07 To 2016/11/20

2

4

2

16

Thomas

Ditshele

Dan

Hlabangwane

Ryno Wessels

Isac Pheko

EX302EX301AVE Of

Cycle 22

8

6

8

Shifts

24-Hour period Digger Summary report


Individual Digger Report


Content


– Brief company background

– Productivity Optimisation Project (POP) methodology

through two case studies:

– Underground case study

– Opencast case study

– Technology (hardware and software) currently in

operation and commercially available

Data capturing via Hand Held PC


Approved for underground use


MCS ProdMate® Mobile

Application This proprietary application is used to create an online portal

underground to enable an Integrated Production

Management System. It makes accurate electronic reporting,

that replaces paper based systems, possible. The following

are examples of information that can be electronically

reported in near real time though simple to use drop down

menus and tick boxes, eliminating typing and human errors:

• Statutory reporting, safety inspections and task

observation

• Downtimes, mining and roof support sequence and

conditions

• Planned, periodic and ad-hock checks and inspections

• Consumables and other materials stock levels and

ordering

All reports can be viewed through dashboards and be

emailed through to relevant personnel

Built to run the MCS ProdMate® Mobile Application

Underground Wi-Fi configuration

© Mining Consultancy Services (Pty) Ltd. 2016 30

Components:1. Single node fibre to belt drive2. Copper into section3. Combined IS power supply and

media converter mounted in switchgear

4. NS40 IS W-Fi node mounted on switchgear

5. Bi-directional antenna, one mounted and other one suspended

2

1

3

4

5

U/G Data and comms


Daily Close out Meetings

Management of actions

ProdNote®

In-SectionWi-Fi

PlanningBoard

Mining Process Information


Monitoring

ProdNote®

In-SectionWi-Fi

Downtime and Production

SC Report CM Report RB Report

Roofbolters


– Number of bolts installed

– Utilisation – first use / last use

– Efficiency – All shift activities

– ONLINE DASHBOARDS

Laptop

Smart Phone IPad

TV Screens

Roofbolter Wi-Fi System


Components:6. Second combined IS

power supply and media converter mounted in switchgear

7. Composite cable suspended against roof

8. NS 40 IR Wi-Fi node mounted against ribside

9. Uni-directional antennas suspended

10. Roofbolter system using VIP & two mounted antennas

6

7

8

10

9

Roofbolter with One Node


Components:• The roofbolter monitoring can also

be done through a single Wi-Fi node as shown here

Roofbolter reports


Hauling efficiency tracking online


– Each shuttle car’s location can be monitored by means of Wi-Fi tags.

– This is used to determine queuing at the feeder breaker.

– Affordable solution

1

3

• Shuttle Cars and Battery Haulers:

Shuttle cars added


Components:11. Combined IS power supply and

media converter mounted on feeder breaker

12. NS 40 IR Wi-Fi node mounted and two Omni-directional antennas mounted on feeder breaker

13. T3 Vehicle tags mounted on shuttle cars

13

12

11

Live dashboards (15 minute update)


Shuttle car reports


Shuttle car report


Thank you


© mining consultancy services (pty) ltd. 2016

Documents