Industry Leading Tools for Solving Business Problems

The software that Digital Twin Analytics uses has been chosen based on our market research of the best and most appropriate tools for use in optimisation and simulation analytics.

Our core suite of tools and their role in the delivery of our engagements is described below.

Industry Leading Tools for Solving Business Problems

The software that Digital Twin Analytics uses has been chosen based on our market research of the best and most appropriate tools for use in optimisation and simulation analytics.

Our core suite of tools and their role in the delivery of our engagements is described below.

AnyLogic

Our digital twin simulation models are written in the AnyLogic™ software package. AnyLogic is the global leader in multi-method simulation software (specifically discrete event and agent-based simulation). With a long development history and a large user base it is our preferred simulation modelling tool. Our team has used AnyLogic for the development of a large number of models in industries ranging from mining through to defence. The software has the ability to scale from small models to models of size limited only by the hardware system resources utilised.

AnyLogic presents the modeller with a graphical model development environment but also has the ability to write more detailed simulation code and algorithms in its native Java programming environment. This provides our consultants with both efficiency and depth of capability ensuring that we are never “painted into a corner” as can be the case with less functional simulation modelling tools. The use of AnyLogic provides us with the ability to generate an executable version of the model that individuals in the client team can use to run their own simulations (subject to licensing and minimum system requirements being met).

AnyLogic

Our digital twin simulation models are written in the AnyLogic™ software package. AnyLogic is the global leader in multi-method simulation software (specifically discrete event and agent-based simulation). With a long development history and a large user base it is our preferred simulation modelling tool. Our team has used AnyLogic for the development of a large number of models in industries ranging from mining through to defence. The software has the ability to scale from small models to models of size limited only by the hardware system resources utilised.

AnyLogic presents the modeller with a graphical model development environment but also has the ability to write more detailed simulation code and algorithms in its native Java programming environment. This provides our consultants with both efficiency and depth of capability ensuring that we are never “painted into a corner” as can be the case with less functional simulation modelling tools. The use of AnyLogic provides us with the ability to generate an executable version of the model that individuals in the client team can use to run their own simulations (subject to licensing and minimum system requirements being met).

Optimisation Solvers

When working on optimisation-based digital twins Digital Twin Analytics use a variety of tools depending on the objective being investigated. For supply-chains our preferred software is anyLogistix. anyLogistix provides optimisation, based on CPLEX, and simulation, based on AnyLogic, in an easy-to-use supply chain modelling framework. By leveraging both simulation and optimisation methods it is possible to gain deeper insights into complex supply chains which are not possible with traditional solutions.

Digital Twin Analytics also has access to solves such as IBM CPLEX and Gurobi. Both of these solvers are high-performance solvers for linear, mixed-integer and quadratic programming problems. Both of these can be integrated into optimisation applications using a variety of application programming interfaces (APIs) such as C, C++, C#, Java and Python.

anyLogistix - GUROBI - IBM CPLEX

Optimisation Solvers

anyLogistix - GUROBI - IBM CPLEX

When working on optimisation-based digital twins Digital Twin Analytics use a variety of tools depending on the objective being investigated. For supply-chains our preferred software is anyLogistix. anyLogistix provides optimisation, based on CPLEX, and simulation, based on AnyLogic, in an easy-to-use supply chain modelling framework. By leveraging both simulation and optimisation methods it is possible to gain deeper insights into complex supply chains which are not possible with traditional solutions.

Digital Twin Analytics also has access to solves such as IBM CPLEX and Gurobi. Both of these solvers are high-performance solvers for linear, mixed-integer and quadratic programming problems. Both of these can be integrated into optimisation applications using a variety of application programming interfaces (APIs) such as C, C++, C#, Java and Python.

Microsoft Azure

Cloud computing is a big shift from the traditional way businesses think about IT resources and provides significant opportunities for the delivery of computing services including servers, storage, databases, networking, software, analytics and intelligence. It provides many benefits including cost, speed, scale, productivity, performance, reliability and security. Historically the ability to run scenarios in the usage phase has been limited by the number of available CPUs but with cloud computing Digital Twin Analytics can provision vast amounts of computing resources in minutes which means results and insights are delivered consistently and rapidly.

Digital Twin Analytics’ preferred cloud computing provider is Microsoft Azure. Microsoft Azure is a global cloud platform that is available in many regions around the world. A region represents a specific datacentre where applications are run or where data is stored. Digital Twin Analytics works with its clients to select the most appropriate region to meet specific compliance or data-residency requirements. Our default locations are Australia Southeast, Australia East and Australia Central.

Microsoft Azure

Cloud computing is a big shift from the traditional way businesses think about IT resources and provides significant opportunities for the delivery of computing services including servers, storage, databases, networking, software, analytics and intelligence. It provides many benefits including cost, speed, scale, productivity, performance, reliability and security. Historically the ability to run scenarios in the usage phase has been limited by the number of available CPUs but with cloud computing Digital Twin Analytics can provision vast amounts of computing resources in minutes which means results and insights are delivered consistently and rapidly.

Digital Twin Analytics’ preferred cloud computing provider is Microsoft Azure. Microsoft Azure is a global cloud platform that is available in many regions around the world. A region represents a specific datacentre where applications are run or where data is stored. Digital Twin Analytics works with its clients to select the most appropriate region to meet specific compliance or data-residency requirements. Our default locations are Australia Southeast, Australia East and Australia Central.

Microsoft Azure DevOps

Engagements of this nature are typically complicated in that there are multiple stakeholders and information flows.  Digital Twin Analytics uses Microsoft DevOps for issue tracking and engagement management as well as for day-to-day issues relating to the management and operation of DTA.  It draws on the principles of agile project management to create an agile delivery as these engagements inevitably change through their lifecycle as insights and discoveries are uncovered.

Optimisation and simulation analytics engagements have a tendency to evolve as modelling and analysis uncovers insight and understanding that was not available at the commencement of the engagement.  As new understanding is uncovered during an engagement, it is often desirable to change the engagement objectives and along with it, the structure of the model and the analysis direction.  To accommodate this “journey of discovery” we recommend engagements be executed using an agile project management philosophy.  Engagement execution activities are usually performed based on two week “sprints”.  At the start of a sprint, key representatives from the Engagement Team collaboratively determine the target outcomes to be achieved by the end of the sprint and the tasks that will be undertaken to achieve these outcomes.

Microsoft Azure DevOps

Engagements of this nature are typically complicated in that there are multiple stakeholders and information flows.  Digital Twin Analytics uses Microsoft DevOps for issue tracking and engagement management as well as for day-to-day issues relating to the management and operation of DTA.  It draws on the principles of agile project management to create an agile delivery as these engagements inevitably change through their lifecycle as insights and discoveries are uncovered.

Optimisation and simulation analytics engagements have a tendency to evolve as modelling and analysis uncovers insight and understanding that was not available at the commencement of the engagement.  As new understanding is uncovered during an engagement, it is often desirable to change the engagement objectives and along with it, the structure of the model and the analysis direction.  To accommodate this “journey of discovery” we recommend engagements be executed using an agile project management philosophy.  Engagement execution activities are usually performed based on two week “sprints”.  At the start of a sprint, key representatives from the Engagement Team collaboratively determine the target outcomes to be achieved by the end of the sprint and the tasks that will be undertaken to achieve these outcomes.

Version Control

Building a digital twin model is only one part of an engagement. There are masses of files to manage through the entire engagement life cycle, some of which are static and some of which change over time.

Regardless, they each need to be managed in an appropriate way to ensure their integrity and traceability. Digital Twin Analytics uses GIT for repository management and version control of these files throughout the development process.

Version Control

Building a digital twin model is only one part of an engagement. There are masses of files to manage through the entire engagement life cycle, some of which are static and some of which change over time.

Regardless, they each need to be managed in an appropriate way to ensure their integrity and traceability. Digital Twin Analytics uses GIT for repository management and version control of these files throughout the development process.

R & R Studio

Digital Twin Analytics’ preferred tool for producing output dashboards and associated reports is R/R Studio. It is used for all data analysis tasks (both input data analysis and output data analysis) and the reporting functionality of this tool is used to generate HTML based interactive reports and dashboards.

Due to the highly numeric nature of the outputs from DTA’s analytics studies, browser-based reports provide significant advantages due to their ability to enable the reader to interact with the reports in ways that are not possible in traditional reporting formats. Users can filter / drill down / zoom into the data as the dashboards contain all of the data for a given scenario. Being able to interact in this way allows users to investigate hypothesis and develop deeper understanding of the results and why they have occurred. This analytics medium can also be configured to produce reports in .pdf, Word and PowerPoint formats as required.

R & R Studio

Digital Twin Analytics’ preferred tool for producing output dashboards and associated reports is R/R Studio. It is used for all data analysis tasks (both input data analysis and output data analysis) and the reporting functionality of this tool is used to generate HTML based interactive reports and dashboards.

Due to the highly numeric nature of the outputs from DTA’s analytics studies, browser-based reports provide significant advantages due to their ability to enable the reader to interact with the reports in ways that are not possible in traditional reporting formats. Users can filter / drill down / zoom into the data as the dashboards contain all of the data for a given scenario. Being able to interact in this way allows users to investigate hypothesis and develop deeper understanding of the results and why they have occurred. This analytics medium can also be configured to produce reports in .pdf, Word and PowerPoint formats as required.

Python

When working with complex data pipelines, automation is crucial to speed up workflows and minimise crucial errors. With an extensive range of powerful libraries, Python is Digital Twin Analytics’ preferred automation tool.

Able to connect with Azure services, databases, spreadsheets, and any other data sources, Python enables a highly automated pipeline connecting human-readable controls and results.

Python

When working with complex data pipelines, automation is crucial to speed up workflows and minimise crucial errors. With an extensive range of powerful libraries, Python is Digital Twin Analytics’ preferred automation tool.

Able to connect with Azure services, databases, spreadsheets, and any other data sources, Python enables a highly automated pipeline connecting human-readable controls and results.

PostgreSQL

Organisation is key when working with large, complex networks of data as both inputs and outputs to simulations.
PostgreSQL, often abbreviated as “Postgres,” is a powerful and open-source relational database management system (RDBMS). It is known for its robustness, extensibility, and adherence to SQL (Structured Query Language) standards.

PostgreSQL is designed to handle a wide range of workloads, from small single-user applications to large enterprise-level systems. PostgreSQL databases hosted through Azure provides Digital Twin Analytics with a rapid and scalable platform to manage information.

PostgreSQL

Organisation is key when working with large, complex networks of data as both inputs and outputs to simulations. PostgreSQL, often abbreviated as “Postgres,” is a powerful and open-source relational database management system (RDBMS). It is known for its robustness, extensibility, and adherence to SQL (Structured Query Language) standards.

PostgreSQL is designed to handle a wide range of workloads, from small single-user applications to large enterprise-level systems. PostgreSQL databases hosted through Azure provides Digital Twin Analytics with a rapid and scalable platform to manage information.

Microsoft Teams

Digital Twin Analytics are strong believers in the value of face-to-face meetings and collaboration however our use of video conferencing and desktop sharing tools has often led to significant savings in travel costs and time – be those meetings across the country or just across town.

We frequently present our analysis remotely using a variety of collaboration tools and even find clients preferring this technique due to the spontaneity that it affords the meeting process.

Microsoft Teams

Digital Twin Analytics are strong believers in the value of face-to-face meetings and collaboration however our use of video conferencing and desktop sharing tools has often led to significant savings in travel costs and time – be those meetings across the country or just across town.

We frequently present our analysis remotely using a variety of collaboration tools and even find clients preferring this technique due to the spontaneity that it affords the meeting process.

Ready to talk about your decision-making challenges with us?

Give us a call on 1300 341 747 or fill in our contact form and we will get back to you as soon as possible.

Contact us here

Contact Us Front Page

Ready to talk about your decision-making challenges with us?

Give us a call on 1300 341 747 or fill in our contact form and we will get back to you as soon as possible.

Contact us here

Contact Us Front Page