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JUL-AUG 2017

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INTECH JULY/AUGUST 2017 15 COVER STORY autonomous equipment and complex expensive technology will need to be kept in the right hands. Intrusions need to have minimal impact, if only to keep public trust and the license to operate. It will be interesting to see how the adoption rate of ISA standards like ISA- 99 is combined with other cybersecurity and enterprise architecture standards and how IT and OT environments might merge into one seamless working en- vironment without any visible vertical layers or visible horizontal siloes. The awareness of the benefits is there, and these standards have now reached the boardrooms of most of the major organizations, where previously only a handful of subject-matter experts would have. The cloud by now has far matured, and more OT systems are cloud enabled, where IT systems have already gone this way in recent years. In this area, software vendors are leading the way, and clients are still playing catch up. It will not be decades before we see the first operations that leverage only one secure seamless and connected modular environment without all the layers that we need today to achieve real-time per- formance and security. Maybe ISA should create an initiative that aims for the next level in collaboration with software ven- dors, technology vendors, and end users. Until that time, I cannot wait to see the benefits of a truly connected and optimized enterprise. n ABOUT THE AUTHOR Bas Mutsaers (mutsaers.bas@gmail.com) has been an ISA member since 2005 and is a board member of the new ISA Mining and Metals Division. View the online version at www.isa.org/intech/20170801. that geologists, lab analysts, maintenance personnel, and operations teams deal with today. We will see central models and decentralized submodels just because vendors will want to differentiate their technology products and services. Therefore, investing in analytics and IoT technology (i.e., providing the sen- sors, the data, and sometimes the control) is investing in understanding the process before deciding how to ultimately model and automate it for improved productiv- ity, downtime, and cost reduction. Only companies that go all in on the analytics journey will find all these dimensions and will be able to run their operations at the lower cost percentile that this technology opportunity opens up. By defining realistic benefit targets and acceptable risk levels, companies will make the expected progress. Some will benefit significantly from their ad- justments and will define a low-cost and flexible operation that can respond to live commodity trading and risk man- agement market data. Currently it is only analytics technol- ogy that has the potential capacity to take those factors into consideration, so high- fidelity models can be put in place to react to any leading and lagging indicators of the enterprise for any time horizon—live. Does that put other current software vendors out of business? Absolutely not. The IT and OT processes still must be run and controlled, but it will be the vendors that have the flexible road maps, open software, and technology that clients will be looking for. These vendors can accommodate this new intelligence and help end users embed repeatable mod- els into their software libraries. This puts these vendors first in rank to be the pro- ductivity partners of the future. Keeping it secure Finally, mining will only be sustainable if current and new company intellectual property is protected. After all, mining involves significant money. With pro- duction highly affecting the daily share price, people will try to have an edge, and therefore mining systems have in- creasingly become a target for hackers. Miners cannot sit back and wait for this to pass, as their growing range of real savings, many projects only have achieved below-average results. Some other projects have been put on hold half - way through until more process and own- ership within the organization is defined. Starting with poor data has also been a major reason for this. Additionally, proj- ects like these are initially seen almost as technology projects "for vendors to prove" and the industry to benefit. After a vendor-led approach, the teams often go back to old habits when the project is finished without embedding the new processes and learning points into their business. Therefore, like with quality and safety, analytics capability will soon be a responsibility for many—not only for the team that gets to play with it through the first initiatives and PoCs. Companies will need to involve vendors that provide the technology, software, and methodology, but will have to put their own governance into place to make analytics part of their core operating model and business pro- cesses and systems. Not many resource companies are already at that level of maturity when it comes to analytics. Theoretical approach Another factor that slows down adop- tion and progress is that analytics is approached very differently from tradi- tional reporting and BI, so should not be treated the same. Unlike reporting that is often predefined and without too many surprises, analytics projects bring up many theoretical ideas and suggestions. Often suggestions that theoretically make sense do not make good business sense. Practically implementing findings in the current investment climate and brown- field environment to capture the poten- tial results is not always feasible. Some findings are likely to be more structural in nature. Through tradition- al reporting and BI, the "easy stuff" has already been found in this industry that has existed for many centuries. To make money in the mining industry, there has always been the need to truly understand the mining process. This has in the past lead to efficient mining opera- tions, and this will also be the case in the future. It is likely, though, that a higher lev- el of automation and machine-learning models will overtake complex functions RESOURCES • ISA95, Enterprise/Control Integration Committee • ISA99, Industrial Automation and Control Systems Security Committee • ISA100, Wireless Systems for Automation Committee • ISA88, Batch Control Systems Committee • ISA101, Human-Machine Interface Committee • ISA18, Instrument Signals and Alarms Committee • ISA108, Intelligent Device Management Committee

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