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Technology Investment Priorities in Mining in Asia-Pacific 2016

Published By :

Timetric

Published Date : Aug 2016

Category :

Mining

No. of Pages : 70 Pages

Synopsis
Overall trends in the data revealed:

Over 60% of mines have already invested in tire monitoring fleet management shift optimization energy management predictive maintenance and environmental monitoring technologies.

The greatest increases in penetration over the last two years have been in real-time video training and environmental monitoring technologies.

UAVs/drones currently have the lowest penetration of the technologies examined with only 17% of mines having invested to date however a significant increase is expected over the next two years.

The commodity sector expected to have the greatest increase in technology penetration over the next 2 years is the precious metals sector whilst India offers the best opportunities for vendors as does the largest company segment with revenues greater than US$10 billion.

Surpac is by far the most used software nominated by 29% of the mines. This was followed by Minex with 15% and MineScape with 10%.

Summary
This report provides a detailed analysis of investment intentions across different areas of technology in the Asia-pacific industry. The analysis is based upon Timetrics survey of over 110 mine general maintenance and procurement managers including other mine-site and corporate decision-makers. The focus is on what technologies mines currently have and in which technologies they are planning to invest over the next two years.

Areas of analysis include:

Mining companies intentions for investments in the coming two years across a range of mine-site technologies including UAVs/drones remote control/machine automation tire monitoring collision avoidance/proximity detection energy management and predictive maintenance.

Comparisons of investment intentions across segments including four commodity groups three mine types five mine-size categories and company revenues.

Comparison of the penetration of technologies in 2014 with current investment levels.

Specific insight into the software platforms each mine site is using across five different mine departments outlining details of market leaders and their software products.

Scope
The report is based on responses from a survey of over 110 senior decision makers at operating mines in Asia-Pacific, responsible for the purchase of equipment for plant and mine operations, along with its consumables and services. Survey respondents came from 8 different countries including: India, Indonesia and the Philippines. This included four different commodity groups and a range of surface and underground mining operations.

Reasons To Buy
Understand which technologies have and are attracting the most investment and how this varies by commodity group mine type and size global company revenue and country.

Target the segments with the greatest opportunity for your technology products and services.

Segment the market according to those fully invested and those planning to make new investments into each technology.

Key Highlights
Over 60% of mines have already invested in tire monitoring fleet management shift optimization energy management predictive maintenance and environmental monitoring technologies.

The greatest increases in penetration over the last two years have been in real-time video training and environmental monitoring technologies.

The technologies with the greatest increases in penetration over the next two years are UAVs/drones and remote control equipment/machine automation with 40% and 39% respectively.

UAVs/drones currently have the lowest penetration of the technologies examined with only 17% of mines having invested to date however a significant increase is expected over the next two years.

The commodity sector expected to have the greatest increase in technology penetration over the next 2 years is the precious metals sector whilst India offers the best opportunities for vendors as does the largest company segment with revenues greater than US$10 billion.

Surpac is by far the most used software nominated by 29% of the mines. This was followed by Minex with 15% and MineScape with 10%.
Table of Contents
1 Executive Summary
2 Technology Investment Trends in Asia-Pacific
2.1 Technology Investment Comparison and Trends
2.2 Scheduling and Shift Optimization (Including Haulage and Dynamic Dispatching)
2.2.1 Mine type
2.2.2 Commodity group
2.2.3 Country
2.2.4 ROM size
2.2.5 Company revenue
2.2.6 Raw data table
2.3 Fleet Management and Vehicle Monitoring
2.3.1 Mine type
2.3.2 Commodity group
2.3.3 Country
2.3.4 ROM size
2.3.5 Company revenue
2.3.6 Raw data table
2.4 Tire Monitoring
2.4.1 Mine type
2.4.2 Commodity group
2.4.3 Country
2.4.4 ROM size
2.4.5 Company revenue
2.4.6 Raw data table
2.5 Environmental Monitoring and Emissions Management
2.5.1 Mine type
2.5.2 Commodity group
2.5.3 Country
2.5.4 ROM size
2.5.5 Company revenue
2.5.6 Raw data table
2.6 Collision Avoidance and Proximity Detection
2.6.1 Mine type
2.6.2 Commodity group
2.6.3 Country
2.6.4 ROM size
2.6.5 Company revenue
2.6.6 Raw data table
2.7 Fatigue Management
2.7.1 Mine type
2.7.2 Commodity group
2.7.3 Country
2.7.4 ROM size
2.7.5 Company revenue
2.7.6 Raw data table
2.8 Real-Time Video Training
2.8.1 Mine type
2.8.2 Commodity group
2.8.3 Country
2.8.4 ROM size
2.8.5 Company revenue
2.8.6 Raw data table
2.9 Remote Control Equipment and Machine Automation
2.9.1 Mine type
2.9.2 Commodity group
2.9.3 Country
2.9.4 ROM size
2.9.5 Company revenue
2.9.6 Raw data table
2.10 UAVs/Drones
2.10.1 Mine type
2.10.2 Commodity group
2.10.3 Country
2.10.4 ROM size
2.10.5 Company revenue
2.10.6 Raw data table
2.11 Predictive Maintenance
2.11.1 Mine type
2.11.2 Commodity group
2.11.3 Country
2.11.4 ROM size
2.11.5 Company revenue
2.11.6 Raw data table
2.12 Energy Management and Optimization
2.12.1 Mine type
2.12.2 Commodity group
2.12.3 Country
2.12.4 ROM size
2.12.5 Company revenue
2.12.6 Raw data table
3 Preferences for Software Platforms
3.1 Top Software by Commodity Group
4 Priorities For Future Technology Investments
4.1 Priorities for Technology Investments by Commodity Group
4.2 Priorities for Technology Investments in India, Indonesia and the Philippines
5 Summary
6 Appendix I
6.1 Selected Data Tables
7 Appendix II
7.1 Survey Background
7.2 Analysis of the Survey Sample
8 Appendix III
8.1 What is This Report About?
8.2 Methodology
8.3 Definitions
8.4 Contact Timetric
8.5 About Timetric
8.6 Disclaimer

List of Tables
Table 1: Scheduling and Shift Optimization Investments and Intentions by Segment (%), Q2 2016
Table 2: Fleet Management and Vehicle Monitoring Investments and Intentions by Segment (%), Q2 2016
Table 3: Tire Monitoring Investments and Intentions Raw Data (%), Q2 2016
Table 4: Environmental Monitoring and Emissions Management Investments and Intentions Raw Data (%), Q2 2016
Table 5: Collision Avoidance and Proximity Detection Investments and Intentions Raw Data (%), Q2 2016
Table 6: Fatigue Management Investments and Intentions Raw Data (%), Q2 2016
Table 7: Real-Time Video Training Investments and Intentions Raw Data (%), Q2 2016
Table 8: Remote Control Equipment and Machine Automation Investments and Intentions Raw Data (%), Q2 2016
Table 9: UAVs and Drones Investments and Intentions Raw Data (%), Q2 2016
Table 10: Predictive Maintenance Investments and Intentions Raw Data (%), Q2 2016
Table 11: Energy Management and Optimization Investments and Intentions Raw Data (%), Q2 2016
Table 12: Main Technology Categories with Responses, Q2 2016
Table 13: Top Software Platforms in Use in Different Departments (%), Q2 2016
Table 14: Priorities for Technology Investments by Commodity Group, Q2 2016 (number of mentions)
Table 15: Priorities for Technology Investments in South Africa and Zambia, Q2 2016 (number of mentions)

List of Figures
Figure 1: Investment Trends and Intentions in a Range of Technologies Over the Next Two Years (%), 2016
Figure 2: Comparisons of Penetration of Four Technologies (%), 20142016
Figure 3: Scheduling and Shift Optimization Investments and Intentions by Mine Type (%), Q2 2016
Figure 4: Scheduling and Shift Optimization Investments and Intentions by Commodity (%), Q2 2016
Figure 5: Scheduling and Shift Optimization Investments and Intentions by Country (%), Q2 2016
Figure 7: Scheduling and Shift Optimization Investments and Intentions by Company Revenue (%), Q2 2016
Figure 8: Fleet Management and Vehicle Monitoring Investments and Intentions by Mine Type (%), Q2 2016
Figure 9: Fleet Management and Vehicle Monitoring Investments and Intentions by Commodity Group (%), Q2 2016
Figure 10: Fleet Management and Vehicle Monitoring Investments and Intentions by Country (%), Q2 2016
Figure 12: Fleet Management and Vehicle Monitoring Investments and Intentions by Company Revenue (%), Q2 2016
Figure 13: Tire Monitoring Investments and Intentions by Mine Type (%), Q2 2016
Figure 14: Tire Monitoring Investments and Intentions by Commodity Group (%), Q2 2016
Figure 15: Tire Monitoring Investments and Intentions by Country(%), Q2 2016
Figure 16: Tire Monitoring Investments and Intentions by ROM Size (%), Q2 2016
Figure 17: Tire Monitoring Investments and Intentions by Company Revenue (%), Q2 2016
Figure 18: Environmental Monitoring and Emissions Management Investments and Intentions by Mine Type (%), Q2 2016
Figure 19: Environmental Monitoring and Emissions Management Investments and Intentions by Commodity Group (%), Q2 2016
Figure 20: Environmental Monitoring and Emissions Management Investments and Intentions by Country(%), Q2 2016
Figure 21: Environmental Monitoring and Emissions Management Investments and Intentions by ROM Size (%), Q2 2016
Figure 22: Environmental Monitoring and Emissions Management Investments and Intentions by Company Revenue (%), Q2 2016
Figure 23: Collision Avoidance and Proximity Detection Investments and Intentions by Mine Type (%), Q2 2016
Figure 24: Collision Avoidance and Proximity Detection Investments and Intentions by Commodity Group (%), Q2 2016
Figure 25: Collision Avoidance and Proximity Detection Investments and Intentions by Country(%), Q2 2016
Figure 26: Collision Avoidance and Proximity Detection Investments and Intentions by ROM Size (%), Q2 2016
Figure 27: Collision Avoidance and Proximity Detection Investments and Intentions by Company Revenue (%), Q2 2016
Figure 28: Fatigue Management Investments and Intentions by Mine Type (%), Q2 2016
Figure 29: Fatigue Management Investments and Intentions by Commodity Group (%), Q2 2016
Figure 30: Fatigue Management Investments and Intentions by Country (%), Q2 2016
Figure 31: Fatigue Management Investments and Intentions by ROM Size (%), Q2 2016
Figure 32: Fatigue Management Investments and Intentions by Company Revenue (%), Q2 2016
Figure 33: Real-Time Video Training Investments and Intentions by Mine Type, Q2 2016
Figure 34: Real-Time Video Training Investments and Intentions by Commodity Group, Q2 2016
Figure 35: Real-Time Video Training Investments and Intentions by Country(%), Q2 2016
Figure 36: Real-Time Video Training Investments and Intentions by ROM Size (%), Q2 2016
Figure 37: Real-Time Video Training Investments and Intentions by Company Revenue (%), Q2 2016
Figure 38: Remote Control Equipment and Machine Automation Investments and Intentions by Mine Type (%), Q2 2016
Figure 39: Remote Control Equipment and Machine Automation Investments and Intentions by Commodity Group (%), Q2 2016
Figure 40: Remote Control Equipment and Machine Automation Investments and Intentions by Country(%), Q2 2016
Figure 41: Remote Control Equipment and Machine Automation Investments and Intentions by ROM Size (%), Q2 2016
Figure 42: Remote Control Equipment and Machine Automation Investments and Intentions by Company Revenue (%), Q2 2016
Figure 43: UAVs/Drones Investments and Intentions by Mine Type (%), Q2 2016
Figure 44: UAVs/ Drones Investments and Intentions by Commodity Group (%), Q2 2016
Figure 45: UAVs/ Drones Investments and Intentions by Country(%), Q2 2016
Figure 46: UAVs/ Drones Investments and Intentions by ROM Size (%), Q2 2016
Figure 47: UAVs/ Drones Investments and Intentions by Company Revenue (%), Q2 2016
Figure 48: Predictive Maintenance Investments and Intentions by Mine Type, Q2 2016
Figure 49: Predictive Maintenance Investments and Intentions by Commodity Group (%), Q2 2016
Figure 50: Predictive Maintenance Investments and Intentions by Country(%), Q2 2016
Figure 51: Predictive Maintenance Investments and Intentions by ROM Size (%), Q2 2016
Figure 52: Predictive Maintenance Investments and Intentions by Company Revenue (%), Q2 2016
Figure 53: Energy Management and Optimization Investments and Intentions by Mine Type (%), Q2 2016
Figure 54: Energy Management and Optimization Investments and Intentions by Commodity Type (%), Q2 2016
Figure 55: Energy Management and Optimization Investments and Intentions by Country(%), Q2 2016
Figure 56: Energy Management and Optimization Investments and Intentions by ROM Size (%), Q2 2016
Figure 57: Energy Management and Optimization Investments and Intentions by Company Revenue (%), Q2 2016
Figure 58: Top Software Platforms in Use in Different Mine Site Departments (%), Q2 2016
Figure 59: Top Software Platforms in Use Across Different Commodity Categorys (%), Q2 2016
Figure 60: Priorities for Technology Investments (%), Q2 2016
Figure 61: Priorities for Technology Investments by Commodity Group (%), Q2 2016
Figure 62: Priorities for Technology Investments by Country(%), Q2 2016
Figure 63: Asia-Pacific Mines by Major Country (%), Q2 2016
Figure 64: Asia-Pacific Mines by Type (%), Q2 2016
Figure 65: Asia-Pacific Mines by Commodity (%), Q2 2016
Figure 66: Asia-Pacific Mines by Company Revenue (%), Q2 2016
Figure 67: Asia-Pacific Mines by Mine Size (%), Q2 2016

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