Pit, Haul Fleet, and Crushing Optimization Tony Gianni Trimble - - PDF document

3/6/2018 1 Pit, Haul Fleet, and Crushing Optimization

Tony Gianni Trimble LOADRITE

Presenter Introduction

• Eastern NA Sales Manager Trimble Loadrite
• 5 years as Technical Support Engineer
• Hundreds of quarries around the world
• Belt scales, plant integration, online reporting

3/6/2018 2

Overview

• Company founded in 1978
• Publicly traded on the NASDAQ

since 1990

• 2014 Revenue $2.5B; 8,000+

employees

• Customers in 150+ countries
• Transforming industrial work

processes through integrated positioning, communications and information technologies

• Over 2,000 patents issued

Unique Position

• Rich domain knowledge
• Field-centric
• Solutions focused
• Mixed fleet support
• OEM partnerships
• Global reach
• Local support

Transforming The Way The World Works Transforming The Aggregates Workflow

EXTRACTION PROCESSING LOADOUT TRANSPORT PRODUCTION CONSTR SITE

• Optimize overall equipment utilization
• Reduce cost of production/transport
• Reduce waste and errors
• Improve customer service and prices
• Improve community relations
• Improve safety
• Reduce transactional friction
• Reduce waste at hand-off points
• Improve information accuracy
• Improve information completeness
• Protect the integrity of the

information

• Provide transparency to all

participants

• Define “Connected Quarry”

– Available Technology

• Performance Metrics and Operational Improvements
• Common causes of increased costs, reduced efficiencies
• Effect on productivity and production
• Equipment, technology to correct issues
• Expected potential savings with process improvement

through sample quarry

• Customer examples

Agenda

3/6/2018 3 THE CONNECTED QUARRY

• Real time link/visibility of all three zones
• Extraction
• Processing
• Loadout
• Staying connected to operations
• Connecting people to the process

The Connected Quarry Available Technology

EXTRACTION PROCESSING LOADOUT

• Pit loading scales
• Haul Truck Monitoring
• Drill positioning
• Dredge positioning
• Conveyor Belt Scales
• Downtime Entry
• Plant Automation
• Loader scales
• Loadout integration
• Conveyor Belt Scales

Information Management & Reporting

3/6/2018 4

Available Technology

• Cloud based reporting

– Fix Today’s Problems – Increased Accessibility – Operational Analysis

KEY PERFORMANCE INDICATORS

Key Performance Indicators

• Meeting production hours
• Sales
• Equipment utilization
• Production cost
• Inventory
• Production / target
• Utilization vs scheduled time
• Cost / ton
• Inventory / sales ratio

3/6/2018 5

Agenda

• Throughput per hour
• Cost per hour
• Idling, running empty
• Reduction of wasted material
• Value of service

SAMPLE QUARRY

Sample Quarry Operation

• Production:
• 900,000 ton theoretical capacity
• Selling 730,000 tons per year, at $10/ton
• Fleet:
• Pit: 1 Drill (1 shot/ 2 wks), 1 Pit Loader, 3 Haul Trucks
• Processing: 3 crushers, 10 belts
• Loadout: 4 Loaders, 1 water truck, 1 weigh bridge
• Other parameters:
• 17 staff
• 11 months/yr, 5 days/wk, 8 hrs/day operation

3/6/2018 6

Sample Quarry Operational Metrics Sample Quarry Income Statement

3/6/2018 7 EXTRACTION

Extraction

• Load correctly from the pit loader
• Eliminate guesswork involved in haul truck loading
• Manage blast performance
• Quickly identify opportunities for improvement in loading,

cycle times, equipment utilization and maintenance

Extraction

3/6/2018 8

Extraction

• Pit loader scales optimize the load

in each truck

– By loading closer to optimal weight, avoid under loaded trucks, and reduce the number of cycles – Optimize truck loads and cycle times, minimize fuel consumption and maintenance costs

Extraction

• Not all operators

are the same

• Load out

management system helps to:

– Identify ‘A’ operators – Assist ‘B’ and ‘C’

• perators

Extraction

• Haul trucks activity

– Loading time – Haul time – Queuing time

• Shows machinery

availability/performance

– Identifies bottlenecks, bunching/line-ups – Empowers fleet managers to make improvements that affect production during the shift

3/6/2018 9

Extraction

• Automated product totals provides

accurate production figures

• Avoid tabulating load sheets
• Highlights material movement issues
• Increased Safety

Extraction Extraction

• Key metric is ton per hour

– More truck loads, not necessary more ton – More ton/truck, not necessary more productive

• With measures, you can manage machines, processes &

people

#34 hauls 2 t more every time. Is it better? #34 takes 2 min more every cycle #34 does 10 t/h less. Less productive!

*A quarry in North Carolina. LOADRITE loader scale installed on a pit-loader

Why did #34 starts late and finishes early??

Is the Pit keeping up with the primary crusher?

3/6/2018 10

Extraction

Shap Beck Quarry

• X2350 Excavator Scale
• Reporting software

Eighty (80) day Payback

• Purely from optimizing haulage

Additional value from:

• Better management of blasting contractors
• Hard data to right-size equipment

Recommended to rollout on largest global sites

“Having Loadrite systems and reports was like putting reading glasses on. We could see and analyze every detail of our

• peration.”
• Chris Herbert, plant supervisor Shap

Beck Quarry, UK

Extraction

• Higher Efficiency

– Reduce truck cycle time

• Higher Productivity

– Reduce the number of truck cycles

• Monitor blast efficiency
• Reduce re-handling

Extraction

• 2 more trucks
• 1 minute reduction in cycle time
• Cost improved by 10 cents/ton ($100,000 decrease)
• With a system that costs about 2.2 cents/ton (over 7 years)

3/6/2018 11 EXTRACTION – EXAMPLE

Extraction – Example

52 Telsmith Primary 3042 Lippmann 6x16 Screen 4in, 1¾, 11/2 3/4 1/2 1 ¾ + 1 1 48 Telsmith 5x16 Screen Deck 6x16 Wash ½ Wash Bin 3/8 Wash Bin Wash 5x14 Screen Deck 3/8 Plant 44 SBS Telsmith Bin Surge Hopper

Extraction – Example

• What was the issue?

– Large amount of material returned – Gradation showed 90% correctly crushed – First screen off primary major bottleneck – Plant slow down to 175TPH – 10 years in place

3/6/2018 12

Extraction – Example

0.00 50.00 100.00 150.00 200.00 250.00 300.00 350.00 6 AM 8 AM 11 AM 1 PM 3 PM 8 AM 10 AM 12 PM 2 PM 12 PM 2 PM 8 AM 10 AM 12 PM 8 AM 10 AM 12 PM 2 PM 6 AM 8 AM 10 AM 12 PM 2 PM 7 AM 9 AM 11 AM 1 PM 3 PM 9 AM 11 AM 1 PM 3 PM 11 AM 1 PM 3 PM 8 AM 10 AM 12 PM 2 PM 4 PM 10-Sep 11-Sep 15- Sep 16-Sep 17-Sep 18-Sep 21-Sep 22-Sep 23-Sep 24-Sep

Primary Crusher

Extraction – Example

• Theoretical:

– Cycle time: 5 – 6 minutes = 10 cycles per hour – Load Weight: 30 ton – 10 cycles x 30 tons = 300 tons per hour

Loadout Plant Pit

Extraction – Example

20 40 60 80 100 28-28.5 28.5-29 29-29.5 29.5-30 30-30.5 30.5-31 31-31.5 31.5-32 32-32.5 32.5-33 33-33.5 33.5-34 34-34.5 34.5-35 35-35.5 35.5-36 36-36.5 36.5-37 37-37.5

Truck Load Weight

3/6/2018 13

Extraction – Example

200 400 600 0:04 0:05 0:06 0:07 0:08 0:09 0:10 0:11 0:12 0:13 0:14 0:15 Count of Cycles Cycle Time in Minutes

Truck Cycle Time

Extraction – Example

0.00 100.00 200.00 300.00 400.00

6 AM 10 AM 1 PM 8 AM 11 AM 12 PM 7 AM 10 AM 8 AM 11 AM 2 PM 8 AM 11 AM 2 PM 9 AM 12 PM 3 PM 11 AM 2 PM 11 AM 2 PM 8 AM 11 AM 2 PM 8 AM 11 AM 2 PM 10-Sep 11-Sep 15- Sep 16-Sep 17-Sep 18-Sep 21-Sep 22-Sep 23-Sep 24-Sep 25-Sep

Hauling Tons Per Hour

Extraction – Example

0.00 50.00 100.00 150.00 200.00 250.00 300.00 350.00 400.00 6 AM 8 AM 11 AM 1 PM 3 PM 8 AM 10 AM 12 PM 2 PM 12 PM 2 PM 8 AM 10 AM 12 PM 8 AM 10 AM 12 PM 2 PM 6 AM 8 AM 10 AM 12 PM 2 PM 7 AM 9 AM 11 AM 1 PM 3 PM 9 AM 11 AM 1 PM 3 PM 11 AM 1 PM 3 PM 8 AM 10 AM 12 PM 2 PM 4 PM 10-Sep 11-Sep 15- Sep 16-Sep 17-Sep 18-Sep 21-Sep 22-Sep 23-Sep 24-Sep

Primary Crusher Face to Haul

3/6/2018 14 PROCESSING

Processing

• Increase the profitability of operations by monitoring and

improving your crushing and screening

• Measure production, energy from crushers and screens
• Monitor throughput on conveyor belts to calculate stockpile

tonnage

Processing

• Installation of belt scales

to monitor flow of product through the system

• Visibility into plant
• perations
• Process Management

– Over/under loading – Stop time – Black belt time

3/6/2018 15

Processing

• Identify bottle necks and pinch

points

• Undersized equipment
• Monitor wear parts against tons

processed

• Identify waste
• Energy used per ton
• Cost analysis
• Help with inventory accuracy at

month/quarter and year-end

Processing

• Review real plant availability

information

• Run time, black-belt time,

scheduled time

• Track down time
• Belt start and stop times
• First and last time the belt was

loaded

• Immediate efficiency feedback

08:49 07:17 01:32 17.4% Start time 07:10 Stop time 16:50 11 Time of first load 07:55 Time of last load 16:40 Black belt % Number of belt stops

Primary

Run time Run time loaded Black belt run time 2 4 6 8 10 07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 Stopped time Black belt time Loaded time Minutes 83% Run time loaded Black belt run time

Processing

600 50

3/6/2018 16

Processing

• Instantaneous Operational

Data

– Rate (TPH) – Total Tons – Belt Status

• Zeroing of Scales

– Maintains highest level of accuracy

• Graphical trends of

production

• Down time event

coding/tracking

Processing

• 5% reduction in black belt time
• 1% reduction in maintenance costs
• Reduced downtime events
• Cost improved by 9 cents/ton with a system that costs about 1.5

cents/ton (over 7 years)

PROCESSING – EXAMPLE

3/6/2018 17

Processing - Example

Problem Description:

• 30+ sites across North America
• Increased competition = reduce capital

expenses and operating costs

• The main focus:

– Reduction black belt run time of each plant – Leads to reduction in energy cost – reduce time based maintenance – Increase throughput

• Optimize use of staff by monitoring

production and stockpiles and removing unnecessary production shifts

Empty run time in hrs / day $ 150 $ 250 $ 500 $ 1,000 $ 1,500 $ 2,000 00:15:00 3,063 $ 5,104 $ 10,208 $ 20,417 $ 30,625 $ 40,833 $ 00:30:00 12,250 $ 20,417 $ 40,833 $ 81,667 $ 122,500 $ 163,333 $ 00:45:00 21,438 $ 35,729 $ 71,458 $ 142,917 $ 214,375 $ 285,833 $ 01:00:00 30,625 $ 51,042 $ 102,083 $ 204,167 $ 306,250 $ 408,333 $ 01:15:00 39,813 $ 66,354 $ 132,708 $ 265,417 $ 398,125 $ 530,833 $ 01:30:00 49,000 $ 81,667 $ 163,333 $ 326,667 $ 490,000 $ 653,333 $ 01:45:00 58,188 $ 96,979 $ 193,958 $ 387,917 $ 581,875 $ 775,833 $ 02:00:00 67,375 $ 112,292 $ 224,583 $ 449,167 $ 673,750 $ 898,333 $ Processing plant operating cost in $ / hour1

• 5 days/week and 49 weeks per year (245 days)
• 1Cost to operate the processing plant when fully manned; not including

hauling, load-out, overhead cost, office etc.

• Not included: ‘Opportunity lost' for not crushing additional rock
• Excl. 10 min/day for start-up and shut-down

Processing - Example

What was the solution?

• Installation of belt scales on each site after

the primary crusher

• Various pieces of data communication

infrastructure to provide the best solution

• Access to Cloud Based Reports by regional

and site management

Internet

Processing - Example

3/6/2018 18

Benefits:

• Operating plant only when material

has to be processed

• Consolidate all data in single data base
• Reduce software and hardware

variations

• Overall reduction in operating cost,

power consumption, maintenance

• Increase in management productivity

by remote monitoring of all sites

Processing - Example Processing – Example 2

Problem Description:

• Increased competition = reduce

capital expenses and operating costs

• Process Improvement needed

– Focus of management team to quantify and standardized downtime events

Processing – Example 2

What was the solution?

• Installation of belt scales

after the primary crusher

• Various pieces of data

communication infrastructure

• Display for data entry of

downtime reasons

• Access to Cloud Based

Reports by regional and site management

Internet

3/6/2018 19

Processing – Example 2 Processing – Example 2

Benefits:

• Accurately monitor the performance of

the site

• Understand WHY downtime occurred

not only WHEN

• Be able to compare data from several

sites based on standardized data entry

• Consolidate all data into one single

database

• Reduce software and hardware

variations

Processing – Example 3

Large quarry in France, Europe

• Quarry with a production of

1,500,000+ tons per year

• Major regional supplier of various

aggregate products

• Several small mobile crushers in

various parts of the quarry produce high quality products

3/6/2018 20

Processing – Example 3

Challenge:

• Quarry purchased by an investment

group

– required transparent production data and weekly production reports – Annual consolidation of data was unacceptable and would have made any previous reports inaccurate

• Process improvement had to be

implemented with dependable and accurate weighing and operating data

Processing – Example 3

Solution:

• Belt scales installed 11 conveyor

belts

• Various pieces of data

communication created infrastructure

• Several integrators configured to

weigh two conveyor belts each to reduce overall installation cost

• Cloud based reports to assist with

the data consolidation

Processing – Example 3

Benefits

• Monitoring of production and stockpile of

each product

• Understanding of the performance and

limitation of each mobile crusher and screener

• Monitoring the performance of the loading

machines

Overall reduction in operating cost, reduced maintenance and increased management productivity Reduction of capital cost by restructuring the production and use of smaller excavators for loading and smaller mobile crushers

3/6/2018 21 SUMMARY

Improved Performance Metrics

• Throughput per hour, cycle times
• Utilization
• Cost per hour
• Sales / Extraction ratio
• Customer Satisfaction

Achieved Financial Benefit

Cost improved by 19 cents/ton, With an investment of 3.7 cents/ton (over 7 years)

3/6/2018 22

Video Questions?

THANK YOU! Booth #1142