IDC Events - Technical Conferences and Workshops

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AI and Machine Learning in Engineering Conference
Data Science for Mining, Industrial Plants, Oil & Gas and Utilities

Are you involved with artificial intelligence (AI) and machine learning in an industrial setting? We are looking for a number of speakers to present papers at this important industry event. Join your peers, enhance your career, share your knowledge and strengthen your public profile while networking with your industry. 

This conference has been created to meet and exchange ideas with those who want to start with the basics of machine learning, develop their understanding of the technology involved, listen to up-to-date case studies, meet subject matter experts, gain actionable insights and finally set a clear and informed plan to implement and invest in predictive technology in their workplace.

“As artificial intelligence (AI) becomes a vital technology for all enterprises, its usage within enterprises has witnessed a tremendous growth. To reap the complete benefits of AI, organisations today need a deeper understanding of machine learning (ML) algorithms, data integration, business processes, and strategies. Although these tasks may seem uncomplicated, most companies lack time, resources, or ability to implement AI that aligns with their core business objectives, data management, and IT strategies.”

(Source: https://artificial-intelligence.apacciooutlook.com/vendor/actionx-achieving-maximum-business-value-with-ai-cid-3632-mid-189.html)

Mainstream examples of this technology are the self-driving Google car, automated recommendations on your favourite websites and fraud detection. What you may not realise is that this technology is used widely in the mining, oil & gas, manufacturing and utilities industries to analyse the huge swathes of data now encountered daily in workplaces. The mining industry is already taking advantage of algorithms by using real-time data to warn operators and maintenance crews of downtime hours in advance. Geologists are using data to discover minerals more effectively and automatically assessing ore fragmentation in less than a minute. Algorithms are being used to monitor machine health, automate tasks in a factory and improve workplace safety in all industrial settings. It is important to note that machine learning has moved on significantly and there is unprecedented value to be gained from quality data in mining and industrial plants.

What is machine learning?

Machine learning is a subset of artificial intelligence (AI) in the field of computer science that often uses statistical techniques and algorithms so computers have the ability to "learn" from data, identify patterns and make decisions with minimal human intervention and without being explicitly programmed. It’s not a new science, but one that has gained fresh momentum with many amazing advancements in data science platforms. While many machine learning algorithms have been around for a long time, the ability to automatically apply complex mathematical calculations to big data is becoming easier. 

There is great value to be derived from machine-learning and artificial intelligence. Many Australian companies are embracing machine learning in their day-to-day operations enterprise wide. We now have access to an abundance of data and more computer power. Local industry needs to take advantage, as small improvements to large industrial operations can have a significant impact on profits and efficiencies. This is an opportunity to turn those large volumes of data into actionable insights. Some companies are in the early stages of implementation, others are exploring how to get started, and others have established on-going projects. At any stage, it is important that companies understand how they can maximise the value of machine learning applications in their operations. It is important to point out that there is a high rate of project failure when it comes to big data, as high as 85%. Without good data, up-to-date technology and company wide project support machine learning can be unsuccessful. 

Speaking at the conference 

As a speaker at the event, you will be sharing your experience and know-how with engineers, technicians and other technical professionals who are all eager to learn more about the benefits of Data Science, Machine Learning and Artificial Intelligence (DSMLAI). The conference will present an industry-wide forum to examine and discuss the latest local and international practices and standards in AI and machine learning. 

Presentations at this conference should allow attendees to:

•    Start with the basics and develop their understanding of the topic by the end of the conference
•    Learn how to apply machine learning techniques and get the most out of their data
•    Be exposed to real applications of machine learning
•    Discover how machine learning principles and predictive data can improve efficiencies, reduce downtimes, lengthen out maintenance times and increase safety. 
•    Learn how to train and educate their staff on the key elements of machine learning
•    Gain actionable insights of the emerging technology and learn real world applications
•    Hear industry case studies and learn from the trial and error and experiences of others
•    Network with experienced industry experts and your peers
 
The overall objective of this conference is to share best practices and new technologies in Data Science, Machine Learning and Artificial Intelligence. We are especially seeking papers on case studies and practical applications.  

This conference is emphatically not aimed at allowing vendors to “sell” their products but rather on real-life industry studies, practical applications and solutions – probably the best way to showcase your technologies and engineering skills.

Data Science, Machine Learning and Artificial Intelligence - Suggested technology, solutions, applications and case study topics:
 
•    Automation and robotics
•    Geology - 3D mapping, geophysics, hyperspectral imaging, geochemistry and mineralogy
•    Environmental monitoring
•    Asset management
•    Industrial inspections, assessment and maintenance planning
•    Facial recognition
•    Coding machine-learning algorithms into fixed plant control systems (e.g. DCS and PLCs)
•    IoT data used in industrial settings
•    Algorithms – Neural networks, decision trees, recommender systems, decision processes, multi-armed bandits, bayesian methods, graphical models
•    Potential problems with algorithms – can we blindly trust them?
•    Augmented reality/virtual reality
•    Automation safety – protecting workers from crush, trapped and caught injuries and fatalities
•    Measuring different industrial variables e.g. electricity and water consumption, waste flow, emissions, processing quantities.
•    Predictive maintenance
•    Cognitive processing
•    Image processing and computer vision
•    Deep learning / neural networks
•    Document recognition and understanding 
•    Intelligent information processing
•    Intelligent modeling and control theory
•    Intelligent vehicles – autonomous vehicles in mining
•    Intelligent video surveillance
•    Mass information processing/GPU processing / parallel computing / quantum computing
•    Natural language processing
•    Pattern recognition
•    Speech and character recognition
•    Signal processing
•    Unmanned aircraft/drones
•    Word recognition/text analytics 
•    Abnormality and data detection
•    Algorithms for new, structured, data types, such as arising in chemistry, biology, environment, and other scientific domains
•    Big data analytics and high performance implementations of data mining algorithms
•    Developing a unifying theory of data mining
•    Distributed data mining and mining multi-agent data
•    Mining high speed data streams
-    Real-time data analysis 
-    Productionising developed models
-    Intergrating models with dashboarding tools
-    Data fusion
•    Mining in networked settings: web, social and computer networks, and online communities
•    Mining sequences and sequential data
•    Mining sensor data
•    Mining spatial and temporal datasets
•    Mining textual and unstructured datasets
•    Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis)

All Submissions Welcome 

What is required from you?

-    A 100 word abstract, which outlines the topic you would like to present. This needs to be submitted electronically as soon as possible, to secure your place. 

-    Once your topic is approved, your technical paper and PowerPoint slides will be due six weeks prior to the event. 

-    Speaking slots are allocated on topic suitability and on a first come first served basis, so please register your interest today by emailing This email address is being protected from spambots. You need JavaScript enabled to view it. 

For further information on this event or to discuss sponsorship opportunities contact: 

Sarah Montgomery
Conference Manager
IDC Events
www.events.idc-online.com  
T: 1300 138 522 



Covering AS 2067 and High Voltage Design, Installation and Maintenance for Mining, Industrial Plants, Oil & Gas & Utilities

Are you an electrical engineer, technologist or technician working with high voltage systems from the mining, industrial plants, oil and gas or the utilities industry?   We are looking for a number of presenters to submit a topic idea and present their papers at the upcoming conference which has been developed to promote best practice in this area.

This conference will cover the AS 2067:2016 HV standard which provides minimum requirements for the design and installation of high voltages above 1kV (ac) so as to provide safe functioning in operation. The newest edition of AS 2067 was released in 2016 and the significant amendments have proved to be a continuing interest to anyone involved in high voltage substations and installations.  

Most sections of AS 2067 have changed. These include issues associated with developments in the Building Code of Australia, closer alignment with the work of EL23 which deals with Mining Standards, and substation installation earthing. Significant changes have been made to the sections on access areas, protection against fire and explosions and earthing. The earthing section in particular is being considerably expanded and amended to cover all industry sectors, including that of mining.  

The Victorian Labor government has announced Victorians will be able to save up to $890 per year on their power bills under the new Solar Homes program, if re-elected. 

Under this $1.24 billion program, 650,000 homes will see half-priced solar panels installed over 10 years. It’s expected to save the typical household up to $2225 off the installation of an average 4kW solar system. From July next year, there will be no upfront cost and Victorians will be able to pay off the rest of the interest-free loan over four years. 

Premier Daniel Andrews announced the government will immediately invest $68 million into the launch of the program.   

“We know the cost of living is going up and it’s getting harder to make ends meet. That’s why Labor is helping families with their energy bills. Only Labor will help put solar panels on your roof to cut your electricity bills by around $900 a year,” he said.

This investment is expected to bring the number of homes in Victoria with solar panels to one million within the next decade. Once the project is complete, the government said Victorians will collectively save approximately $500 million per year on electricity. 

The program is also expected to lead to the reduction of almost four million tonnes of carbon emissions and generate 12.5 per cent of the state’s 40 per cent target for renewable energy by 2025. 

The rebate is available to all Victorians with a household income of up to $180,000 who live in their own home, which is valued at up to $3 million. This means nine out of 10 Victorians who own their own home will be eligible. 

Steps towards energy self-sufficiency at your workplace

Installing a ‘stand alone’ renewable energy system in an off-grid location may be a necessity or a sustainable choice at your workplace. Either way you have much to gain from today’s increasingly efficient and affordable solar panels, turbines, inverters and batteries.

Renewable energy generation such as solar and wind power not only helps you create a sustainable power source but benefits the environment, reduces noise, reduces air pollution, and cuts diesel transport costs to save you time and energy.

Whether you are trying to power a chicken farm, a communications tower on a mine site or a private house in a remote location an important first step towards energy self-sufficiency is to minimise any unnecessary power use. If you think your site may suit a wind power or micro-hydro power system, this is also an option.

What is IECEx?

IECEx is a voluntary system which provides an internationally accepted means of proving compliance with IEC standards. IEC standards are used in many national approval schemes and as such, IECEx certification can be used to support national compliance, negating the need in most cases for additional testing.

The Benefits of IECEx

The fact that many countries operate under different standards means that Ex equipment often needs to be re-tested and re-certified to the appropriate standards of that country, adding to the cost of the equipment. The IECEx scheme significantly reduces the need for re-testing and certification by conforming to international IEC standards, and therefore makes international trade easier, quicker and more cost effective.

The objective of the IECEx System is to facilitate international trade in equipment and services for use in explosive atmospheres, while maintaining the required level of safety:

  • reduced testing and certification costs to manufacturer

  • reduced time to market

  • international confidence in the product assessment process

  • one international database listing

  • maintaining International Confidence in equipment and services covered by IECEx Certification

What is an Ex area?

Ex areas can be known by different names such as “Hazardous Locations”, “Hazardous Areas” “Explosive Atmospheres”, and the like and relate to areas where flammable liquids, vapours, gases or combustible dusts are likely to occur in quantities sufficient to cause a fire or explosion.

The modern day automation of industry has meant an increased need to use equipment in Ex areas. Such equipment is termed “Ex equipment”

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