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Graham Cochrane has over 4 years of experience in foundry engineering and manufacturing. He currently works as a Foundry Process Engineer at D.W. Clark in Taunton, MA where he designs 3D models, engineers tooling and simulations, manages the 3D sand print department, and serves as a liaison between the company and equipment developers. Previously he held co-op positions as a Foundry Process Technician and Quality Assurance Technician where he assisted with casting design, tooling, quality control, and CNC machining. He has a B.S. in Mechanical Engineering Technology from Wentworth Institute of Technology and is a Certified Manufacturing Technologist through SME.
BlueBRIDGE: Cloud infrastructure serving aquafarms and supporting modelsBlue BRIDGE
Presentation held during the NKUA postgraduate course “DATA BASES MANAGEMENT SYSTEMS” on 6th of December 2016 at National and Kapodistrian University of Athens.
Gerasimos Antzoulatos, i2S
Charalampos Dimitrakopoulos, CITE
Dimitris Katris, UoA
Giota Koltsida, UoA
Nikolas Laskaris , UoA
Eleni Petra, UOA
Stella Tsani, Prof. Phoebe Koundouri, ICRE8
http://bit.ly/2hEkn3G
This document introduces new features for Production Workspace in April 2016. It describes features such as probabilistic decline curve analysis, group and aggregate technology with bar charts, and well cards. These features allow users to analyze production data, compare operator performance, and access well information. The document provides examples of how reservoir engineers, geologists, financial analysts, and other roles might use the features to benchmark performance, analyze correlations, and monitor company activity. It highlights the new probabilistic decline curve analysis tool, which automatically fits decline curves and forecasts reserves to improve accuracy and manage risk in estimates.
Saurabh Kale is a Master's student in Industrial Engineering at the University of Houston with relevant work experience. He has interned at Piping Technology and Products assessing manufacturing software and implementing process improvements. Additionally, he has worked as a Teaching Assistant and Mechanical Design Engineer. Kale is pursuing Six Sigma Green Belt certification and skills in analytics software like R, Solidworks, Excel and simulation tools.
Tanmay Srivastava has over 2 years of experience in mechanical engineering, including internships doing thermal analysis, fluid flow simulation, CAD modeling, and piping design. He has skills in CAD software like CATIA, SolidWorks, and Creo as well as analysis tools like ANSYS and MATLAB. His academic projects involved design optimization and he has published research on experimental flow visualization around cylinders.
This is the presentation for his admission to the third year of his Ph.D.. It talks about the several direction his work had taken and look forward to the conclusion of some task in form of code release and published papers.
Graham Cochrane has over 4 years of experience in foundry engineering and manufacturing. He currently works as a Foundry Process Engineer at D.W. Clark in Taunton, MA where he designs 3D models, engineers tooling and simulations, manages the 3D sand print department, and serves as a liaison between the company and equipment developers. Previously he held co-op positions as a Foundry Process Technician and Quality Assurance Technician where he assisted with casting design, tooling, quality control, and CNC machining. He has a B.S. in Mechanical Engineering Technology from Wentworth Institute of Technology and is a Certified Manufacturing Technologist through SME.
BlueBRIDGE: Cloud infrastructure serving aquafarms and supporting modelsBlue BRIDGE
Presentation held during the NKUA postgraduate course “DATA BASES MANAGEMENT SYSTEMS” on 6th of December 2016 at National and Kapodistrian University of Athens.
Gerasimos Antzoulatos, i2S
Charalampos Dimitrakopoulos, CITE
Dimitris Katris, UoA
Giota Koltsida, UoA
Nikolas Laskaris , UoA
Eleni Petra, UOA
Stella Tsani, Prof. Phoebe Koundouri, ICRE8
http://bit.ly/2hEkn3G
This document introduces new features for Production Workspace in April 2016. It describes features such as probabilistic decline curve analysis, group and aggregate technology with bar charts, and well cards. These features allow users to analyze production data, compare operator performance, and access well information. The document provides examples of how reservoir engineers, geologists, financial analysts, and other roles might use the features to benchmark performance, analyze correlations, and monitor company activity. It highlights the new probabilistic decline curve analysis tool, which automatically fits decline curves and forecasts reserves to improve accuracy and manage risk in estimates.
Saurabh Kale is a Master's student in Industrial Engineering at the University of Houston with relevant work experience. He has interned at Piping Technology and Products assessing manufacturing software and implementing process improvements. Additionally, he has worked as a Teaching Assistant and Mechanical Design Engineer. Kale is pursuing Six Sigma Green Belt certification and skills in analytics software like R, Solidworks, Excel and simulation tools.
Tanmay Srivastava has over 2 years of experience in mechanical engineering, including internships doing thermal analysis, fluid flow simulation, CAD modeling, and piping design. He has skills in CAD software like CATIA, SolidWorks, and Creo as well as analysis tools like ANSYS and MATLAB. His academic projects involved design optimization and he has published research on experimental flow visualization around cylinders.
This is the presentation for his admission to the third year of his Ph.D.. It talks about the several direction his work had taken and look forward to the conclusion of some task in form of code release and published papers.
This document summarizes the data requirements and modeling efforts for the OptEEmAL project. It discusses how data needs were collected from each work package and process. Global requirements were defined to unify different templates. Challenges in mapping between data models like IFC and SimModel were addressed through ontology alignment and identifying structural differences. The document concludes that data integration requires iterative refinement and simulations have detailed requirements not fully represented in tools. Mappings between models are also needed to transform data between domains.
The document discusses two case studies, NRG4Cast and SUNSEED, that use big data approaches for energy efficiency. NRG4Cast monitors, analyzes, predicts, and optimizes energy usage in districts, buildings, and households. It integrates different data sources to model energy consumption and production. SUNSEED develops advanced sensor networks and analytics to provide monitoring, forecasting, and control of smart energy distribution grids. Both projects address technical challenges around data integration from various sources and aim to reduce energy costs and environmental impact through optimized energy management.
This document is Sarvesh Satam's design portfolio, which provides information about his education, skills, experience, and projects. It summarizes his Masters in Mechanical Engineering and Bachelors in Mechanical Engineering. It also lists his technical skills in engineering software, programming languages, and computer skills. His professional experience includes mechanical engineering roles at Knorr-Bremse and Godrej & Boyce, where he worked on product design, development, testing, and analysis. His portfolio highlights several educational projects focused on mechanical design, optimization, and additive manufacturing.
INCEPTION enriches the European identity through the understanding of how European Cultural Heritage continuously evolves over long periods of time. INCEPTION’s Inclusive approach introduces novel solutions of 3D digital modelling:
1 - forever: INCEPTION “Time Machine” that represents an innovative use of timescale for dynamic 3D reconstruction;
2 - for everybody: portable, user-friendly and cost-effective hardware and software instruments for 3D capturing, modelling and analysis;
3 - from everywhere: INCEPTION’s proposed standard procedures for data acquisition and open-standard format for Cultural Heritage Building Information Modelling.
For further information visit the website: www.inception-project.eu
Dear Colleagues,
Call for papers for another Machine Learning special issue of SEG/AAPG Journal of Interpretation focusing on the Seismic Data Analysis has been announced.
We look forward to your contribution.
Vikram Jayaram
Special Section Editor
Interpretation
This document presents a methodology for using 3D scanning and software tools to reverse engineer geometric shapes. The methodology involves scanning primitive objects and test parts, extracting scan data, and using CAD tools and 3D printing to recreate the objects. Accuracy is determined by comparing key dimensions of the original and reverse engineered parts. The methodology was developed to efficiently and accurately reproduce mechanical components through reverse engineering.
Tanya Cashorali gave a presentation on using R for data science applications across industries. She discussed how R can be used for data manipulation, dashboards, machine learning, migrating from other tools to R-based workflows, integrating with APIs, rapid prototyping, and training. She highlighted examples of using R in industries like pharmaceuticals, hospitals, telecommunications, and more. Cashorali concluded by discussing future trends in R adoption and suggestions for organizations looking to use R.
Saurabh Saksena has over 15 years of experience in the oil and gas industry working in roles involving reservoir characterization, petrophysics, and geoscience analysis. He has worked for BHP Billiton for the past 3 years as a senior geoscience analyst and has also worked for Weatherford International and as an implementation consultant. He is proficient in various geoscience applications and well logging concepts.
Gemcom Surpac is geology and mine planning software that provides efficiency and accuracy through ease-of-use, powerful 3D graphics, and workflow automation. It allows for increased sharing of data, skills and project knowledge between teams. All tasks can be automated and aligned to company processes. It also ensures quick understanding of the system and project data through its ease-of-use. Surpac supports geological and resource modeling, data management, estimation and modeling, mine planning, mine production, mine survey and ore control with automated workflows.
The document describes an architecture for semantically integrating enterprise data lakes. It proposes a knowledge graph that links metadata, data models and key performance indicators to provide a common meaning for data. Raw data is stored in a data lake and ingested from various sources. A metadata layer captures dataset metadata, ontologies and integration rules to link disparate data. An interface allows users to access consolidated views generated by executing queries on Hadoop. The process involves cataloging, discovering, lifting, linking and validating datasets to integrate them based on rules into the knowledge graph.
Automating Regional Data Integration with Python & ArcPy (Heather Widlund)GIS Colorado
The document discusses automating the integration of regional GIS data using Python and ArcPy. The current process of manual data updates is arduous and results in infrequent updates. The proposed solution is to use scripting tools to automate the standardization, integration, and updating of key GIS datasets such as street centerlines, addresses, and emergency service boundaries. This automation will improve emergency response by ensuring up-to-date mapping and address verification. The project involves developing Python scripts to regularly integrate source data according to standardized schemas and push updates to dispatch software.
The document is a resume for Junhong Lin that provides details about their education, skills, experience, projects, and awards. It summarizes that Lin is expected to graduate in May 2016 with a Master's in Mechanical Engineering from USC with a 3.933 GPA. They have experience with internships in strategy engineering and research, and have led projects involving 3D sand printing, self-folding structures, finite element analysis, and vehicle/bridge system modeling. They received several awards for mathematical modeling competitions from their undergraduate institution in China.
Introduction to DI Engineering Explorer for Exploration and Production Drillinginfo
DI Engineering Explorer is a proprietary tool that allows users to visualize completion and production data from over 130,000 wells to identify correlations and best practices. It saves customers over $800,000 and a year of work. The tool analyzes engineering and production data to help users optimize production, stay ahead of competitors, and uncover insights to make better decisions. Regular updates ensure users have access to the latest data and analytics.
The document provides a framework for capacity analysis with 5 essential steps: 1) define scope and questions, 2) identify servers and measurements, 3) analyze historical data, 4) analyze tests, 5) project future capacity. It then applies this framework to analyze the capacity of 3 applications, Apps A, B, and C, migrating from one location to another virtualized location. For App A, the analysis finds the proposed virtual configuration is adequate based on historical usage but risks from memory leaks and unbalanced loads are highlighted. For App C, it determines the current CPU capacity is inadequate and capacity must be increased. An executive summary is recommended to communicate these findings and capacity recommendations.
Vivek Adithya Mohankumar has a Master's degree in Information Systems from the University of Texas at Arlington. He has work experience as an Information Developer at SAP where he gathered requirements and helped translate them into user stories. He also has experience analyzing business transactions using Apache Spark and building predictive models with Python. His areas of expertise include data analysis, machine learning, business intelligence, and agile methodologies.
This document summarizes the data requirements and modeling efforts for the OptEEmAL project. It discusses how data needs were collected from each work package and process. Global requirements were defined to unify different templates. Challenges in mapping between data models like IFC and SimModel were addressed through ontology alignment and identifying structural differences. The document concludes that data integration requires iterative refinement and simulations have detailed requirements not fully represented in tools. Mappings between models are also needed to transform data between domains.
The document discusses two case studies, NRG4Cast and SUNSEED, that use big data approaches for energy efficiency. NRG4Cast monitors, analyzes, predicts, and optimizes energy usage in districts, buildings, and households. It integrates different data sources to model energy consumption and production. SUNSEED develops advanced sensor networks and analytics to provide monitoring, forecasting, and control of smart energy distribution grids. Both projects address technical challenges around data integration from various sources and aim to reduce energy costs and environmental impact through optimized energy management.
This document is Sarvesh Satam's design portfolio, which provides information about his education, skills, experience, and projects. It summarizes his Masters in Mechanical Engineering and Bachelors in Mechanical Engineering. It also lists his technical skills in engineering software, programming languages, and computer skills. His professional experience includes mechanical engineering roles at Knorr-Bremse and Godrej & Boyce, where he worked on product design, development, testing, and analysis. His portfolio highlights several educational projects focused on mechanical design, optimization, and additive manufacturing.
INCEPTION enriches the European identity through the understanding of how European Cultural Heritage continuously evolves over long periods of time. INCEPTION’s Inclusive approach introduces novel solutions of 3D digital modelling:
1 - forever: INCEPTION “Time Machine” that represents an innovative use of timescale for dynamic 3D reconstruction;
2 - for everybody: portable, user-friendly and cost-effective hardware and software instruments for 3D capturing, modelling and analysis;
3 - from everywhere: INCEPTION’s proposed standard procedures for data acquisition and open-standard format for Cultural Heritage Building Information Modelling.
For further information visit the website: www.inception-project.eu
Dear Colleagues,
Call for papers for another Machine Learning special issue of SEG/AAPG Journal of Interpretation focusing on the Seismic Data Analysis has been announced.
We look forward to your contribution.
Vikram Jayaram
Special Section Editor
Interpretation
This document presents a methodology for using 3D scanning and software tools to reverse engineer geometric shapes. The methodology involves scanning primitive objects and test parts, extracting scan data, and using CAD tools and 3D printing to recreate the objects. Accuracy is determined by comparing key dimensions of the original and reverse engineered parts. The methodology was developed to efficiently and accurately reproduce mechanical components through reverse engineering.
Tanya Cashorali gave a presentation on using R for data science applications across industries. She discussed how R can be used for data manipulation, dashboards, machine learning, migrating from other tools to R-based workflows, integrating with APIs, rapid prototyping, and training. She highlighted examples of using R in industries like pharmaceuticals, hospitals, telecommunications, and more. Cashorali concluded by discussing future trends in R adoption and suggestions for organizations looking to use R.
Saurabh Saksena has over 15 years of experience in the oil and gas industry working in roles involving reservoir characterization, petrophysics, and geoscience analysis. He has worked for BHP Billiton for the past 3 years as a senior geoscience analyst and has also worked for Weatherford International and as an implementation consultant. He is proficient in various geoscience applications and well logging concepts.
Gemcom Surpac is geology and mine planning software that provides efficiency and accuracy through ease-of-use, powerful 3D graphics, and workflow automation. It allows for increased sharing of data, skills and project knowledge between teams. All tasks can be automated and aligned to company processes. It also ensures quick understanding of the system and project data through its ease-of-use. Surpac supports geological and resource modeling, data management, estimation and modeling, mine planning, mine production, mine survey and ore control with automated workflows.
The document describes an architecture for semantically integrating enterprise data lakes. It proposes a knowledge graph that links metadata, data models and key performance indicators to provide a common meaning for data. Raw data is stored in a data lake and ingested from various sources. A metadata layer captures dataset metadata, ontologies and integration rules to link disparate data. An interface allows users to access consolidated views generated by executing queries on Hadoop. The process involves cataloging, discovering, lifting, linking and validating datasets to integrate them based on rules into the knowledge graph.
Automating Regional Data Integration with Python & ArcPy (Heather Widlund)GIS Colorado
The document discusses automating the integration of regional GIS data using Python and ArcPy. The current process of manual data updates is arduous and results in infrequent updates. The proposed solution is to use scripting tools to automate the standardization, integration, and updating of key GIS datasets such as street centerlines, addresses, and emergency service boundaries. This automation will improve emergency response by ensuring up-to-date mapping and address verification. The project involves developing Python scripts to regularly integrate source data according to standardized schemas and push updates to dispatch software.
The document is a resume for Junhong Lin that provides details about their education, skills, experience, projects, and awards. It summarizes that Lin is expected to graduate in May 2016 with a Master's in Mechanical Engineering from USC with a 3.933 GPA. They have experience with internships in strategy engineering and research, and have led projects involving 3D sand printing, self-folding structures, finite element analysis, and vehicle/bridge system modeling. They received several awards for mathematical modeling competitions from their undergraduate institution in China.
Introduction to DI Engineering Explorer for Exploration and Production Drillinginfo
DI Engineering Explorer is a proprietary tool that allows users to visualize completion and production data from over 130,000 wells to identify correlations and best practices. It saves customers over $800,000 and a year of work. The tool analyzes engineering and production data to help users optimize production, stay ahead of competitors, and uncover insights to make better decisions. Regular updates ensure users have access to the latest data and analytics.
The document provides a framework for capacity analysis with 5 essential steps: 1) define scope and questions, 2) identify servers and measurements, 3) analyze historical data, 4) analyze tests, 5) project future capacity. It then applies this framework to analyze the capacity of 3 applications, Apps A, B, and C, migrating from one location to another virtualized location. For App A, the analysis finds the proposed virtual configuration is adequate based on historical usage but risks from memory leaks and unbalanced loads are highlighted. For App C, it determines the current CPU capacity is inadequate and capacity must be increased. An executive summary is recommended to communicate these findings and capacity recommendations.
Vivek Adithya Mohankumar has a Master's degree in Information Systems from the University of Texas at Arlington. He has work experience as an Information Developer at SAP where he gathered requirements and helped translate them into user stories. He also has experience analyzing business transactions using Apache Spark and building predictive models with Python. His areas of expertise include data analysis, machine learning, business intelligence, and agile methodologies.
Similar to Datamine Solutions for DS and IM, mining,block (20)
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The cherry: beauty, softness, its heart-shaped plastic has inspired artists since Antiquity. Cherries and strawberries were considered the fruits of paradise and thus represented the souls of men.
1. STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
Datamine Solutions for Industrial Minerals and
Construction Materials, including Dimension Stones.
2. Datamine Overview
Global Presence
• 250 staff in 12 countries
• Canada, USA, Peru, Chile, Mexico,
Brazil, Australia, South Africa, India,
UK, Russia
Extensive Customer Base
• Spans large and small mining
companies and service providers in
more than 90 countries
• Added 200 sites in year to March
2014
Comprehensive Solution
Footprint
• Geology, mine planning and
operations
• Trusted technology with a 30 year
heritage in resource and reserve
assessment
Complimentary Service Offerings
• Implementation
• Training
• Technical consulting
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
3. Software & Services Landscape
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
4. Datamine: Industrial Minerals and Construction Materials,
including Dimension Stones
Function Product
Exploration and Resource Modelling &
Estimation
Studio EM
Mine Design and Production Scheduling
Studio OP
Studio 5D Planner (Underground)
Visualisation InTouch Go or 3D PDF
Geotechnical Modelling Sirovision
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
5. Solution : Exploration, Resource Modelling &
Estimation
Datamine’s resource modelling systems deliver robust geological models for large and small
mines across the full range of commodities and deposit types. These flagship products set the
industry standard in this field with proven algorithms developed and refined over 30
years. Utilized by the world’s major mining houses and consulting firms for the public reporting
of resources and reserves, our resource modelling systems are robust, reliable and trusted
globally.
Function Product
Exploration and Resource
Modelling & Estimation
Studio EM
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
6. Solution : Studio EM
Datamine Studio EM is tailor made to meet the needs of exploration geologists. Leveraging the base
technology of Datamine’s hugely successful Studio software series, Studio EM includes point and
string editing, wireframing, basic block modelling and estimation functionality as well as the ability to
dynamically link to an existing drillhole database. Studio EM also has a full set of plotting functionality
for producing section plots, plan plots, strip logs and reports as well as comprehensive 3D viewing and
the option to publish 3D pdf files.
• Resource and reserve modelling is the process of using geological and assayed data from
a mineral deposit to determine its prospects for economic extraction.
• The data available to a resource modelling study often comes from a variety of sources,
can be disparate in its nature and has frequently been obtained at different times.
• Studio provides a rich environment within which to manage this data.
• Studio contains many useful functions; it is not practical to describe all of these in a single
presentation.
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
7. Resource Modelling
• The main phases of a resource modelling study typically include:
• Drillhole and Sample Processing
• Statistical and Geostatistical Analysis
• Geological Interpretation and Structural Modelling
• Grade Estimation and Validation
• Resource Classification and Reporting
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
8. Data Import
Studio’s drillhole data import is fast and flexible
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
9. Drillhole Processing
An easy to use wizard allows data to be
imported from a wide range of file and
database formats
Matching the imported data to required
information is straightforward
Alternative options for desurveying
(locating hole samples in 3D space) are
available
More tables can be defined as required
Studio’s drillhole data import is fast and flexible
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
10. Drillhole and Sample Processing
Simultaneous ways of visualizing and dynamically selecting
data allows for rapid visual analysis
Data is shared between 3D views, sections and logs
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
11. Statistical Analysis
Easy to produce charts such as scatter
plots and histograms help you to
quickly understand the raw data’s
characteristics
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
12. Statistical Analysis – Linked Windows
Select data dynamically in either 3D or chart views to see the
highlighted data in the other view.
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
13. Image Draping and Registration
Correlation of data with surface imagery is easy. Studio automatically
recognises a wide range of geo-referenced image formats or an easy to use
tool is available for manual image registration.
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
14. Structural and Volumetric Modelling
An accurate resource model will include boundaries of different geological structures and
features, particularly those that affect the economics of its extraction or processing.
Boundaries can be used to model:
• Surface topographies
• Mineralization
• Structures (faults, dykes etc.)
• Lithology
• Weathering
• Existing voids
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
15. Structural and Volumetric Modelling
For continuous properties such as grade to be modelled accurately in the same object as structure
block models are used.
Where required sub cells are used to accurately model boundaries.
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
16. Grade Estimation
In addition to structure, the cells in a resource model contain values of other parameters.
Parameters can be text or numeric and can represent almost anything …:
• Grades
• Material Qualities
• Geotechnical parameters (e.g. blastability)
Studio contains a range of geostatistical functionality for
interpolating values of parameters into models
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
17. Grade Estimation
The following estimation methods are available:
• Nearest Neighbour
• Inverse Power of Distance
Available variogram models are:
• Spherical (single or multiple structures)
• Exponential
• Gaussian
Multiple grades can be interpolated in a single estimation run
using multiple methods and multiple dynamically expandable
search volumes
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
18. Model Validation and Reports
Interpolated model grades can be
compared with sample data using
graphical and tabular options
Comparisons can be made either globally
or for selected subsets of the data
Comparison of Fe and Al2O3:
Correlation coefficient
Samples: 0.848
Model: 0.852
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
19. Resource Evaluation
• Once you have a resource model it can be used to determine the economic viability of different
extraction strategies
• Boolean and solid manipulation commands can be used to generate possible mining shapes.
Evaluation of these can be done interactively or procedurally
• Processes also exist to slice models on key fields and output results tables that can be further
processed.
Studio has a wide range of functionality for evaluating the
contents of resource models and for considering alternative
mining strategies
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
20. Dynamic Evaluation
Evaluated results using any
legend are updated
dynamically as multiple
outlines are selected and
edited.
One example of evaluating shapes is to use outlines
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
21. Dynamic Evaluation: Example
Any set of 3D shapes defined by
open or closed wireframes and/or
outlines can be evaluated against a
block model.
This example shows how 3D shapes
defined by outlines together with
up and down projection distances
can be evaluated.
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
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22. Results Analysis: The Mining Power Pack
Studio comes with a powerful Excel plug in for analysing results files in more detail
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
23. Presentation
Studio has completely integrated plotting functionality. Templates for layouts and
default formatting makes it easy to use plotting for operational output as well as during
resource and reserve studies.
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
24. Solution : Mine Design and Production
Scheduling
Datamine provides a full range of Mine planning applications from strategic long term
optimization, Mine design and reserve generation through to short term material destination
and operational equipment scheduling. This integration ensures robust strategic plans are
executed reliably on the ground. With powerful animations and a range of other visual and
numerical output formats, communicating plans throughout your organization is a breeze.
Function Product
Mine Design and Production
Scheduling
Studio OP
Studio 5D Planner (UG)
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
25. Open Pit Solution Overview
Datamine Software open pit planning solution incudes the following desktop and web
based applications:
• Complete strategic pit planning package covering pit optimization, pushback
generation, cut-off grade optimization, scheduling, haulage optimization and stockpile
management
• Highly visual and interactive complete design and scheduling package for medium to
short term planning
• Strategic risk analysis package understanding the main economic drivers by performing
sensitivity analysis and the probability of achieving certain economic and mining
outcomes using simulation
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
26. Deriving from strategic / long term schedule (for example NPV Scheduler or RM Scheduler)
Added Values
• Easy to use and flexible detail
• Emphasis on interactive graphics
• Results are practical/realistic
• Easy to detect bottlenecks
Activity Based Planning
Equipment allocation and tracking
Detailed haulage analysis
Dump & Stockpile design, sequencing and scheduling
Stockpile management
3D graphical presentation tools
Charting tools to monitor results
Export to Excel, CSV and EPS
Gantt chart reporting in EPS
StudioOP Functionality Overview
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
28. Reporting includes plans, sections, tables, animations,
Gantt charts, and output to reporting tools such as Excel
Reporting
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
30. Adjust Schedule in EPS
– Real-time selection and filtering of tasks
– Animation showing current sequence and schedule
– Create dependencies in either Gantt chart or visualizer
Scheduling: EPS & InTouch
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
31. Function Product
Visualisation InTouch Go or 3D PDF
Solution : 3D Visualisation
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
32. Export VR Window to Interactive PDF Document
The Export to PDF3D command allows you to save the content of the VR window to an
interactive 3D document, which can then be used for publishing, sharing and viewing
project data:
• export formats include *.pdf, *.u3d and *.prc
• an exported file which can be viewed using any PDF viewers e.g Adobe Reader
• file content which allows the interactive 3D viewing of data
• retention of labels, the VR folders and object names in the exported document
• a file which can be embedded in Word documents and PowerPoint presentations
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
33. Function Product
Geotechnical Modelling Sirovision
Solution : Geotechnical Modelling
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
34. Sirovision
3D Model Generation:
Generates accurate, scaled 3D
images of rock faces from stereo
photographs taken in open pit and
underground environments.
Geological & Geotechnical Mapping &
Analysis
Enables structural mapping directly on
to 3D surfaces with immediate
geotechnical results.
Discontinuity Set and Slope Stability
Analysis
Seamless export of 3D images and
structural data.
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
35. Analysing Discontinuity Sets
Add your own custom data.
Define Analysis Sets using
queries.
Analyse sets on Spherical
Projections and 3D Images
simultaneously.
Slope Stability Analysis tool
detects wedges between
joint sets.
Display charts, histograms,
tables and 3D models in
reports.
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016
36. Slope Stability Analysis
Inputs
Domain characteristics:
Rock Density
Cohesion
Pore Pressure
Angle of internal
friction
Outputs
3D visualization of the
wedge in real space.
Mass in kgs
Volume in m3
Sliding Vector
STONECHANGE 2016 - STONE SECTOR and CHANGING TRENDS
Carrara 16-17 June 2016