Moving from the lab to the process
A fundamental shift is occurring in heavy industry, with a focus on bringing lab data into the process, incorporating real-time information and online measurement. As ore grades decline and extraction becomes increasingly difficult, continuous processing optimisation becomes not only a ‘nice to have’, but a ‘must have’ for operations to become profitable, particularly with the current challenging global situation.
With various innovations such as digital twins, AI and other Industry 4.0 tools for the optimisation of processes available, there is a plethora of cutting-edge systems that can optimise operations beyond anything we have witnessed before. It makes sense that with faster, more detailed information about the process, coupled with raw material feed characteristics available in real time, effective automation can be implemented.
We have seen a small number of mining or oil and gas sites embrace this mind-shift transformation and generate excellent ROI on their initial investment. These novel optimisation systems are very effective when implemented correctly; however, there is a catch: these are only value multiplier systems and can only deliver value if there is informative and integral baseline process data. Without accurate and reliable lab data, most operators would agree it would be like running blind — it’s only a matter of time before you run into something.
Innovative instrumentation businesses have identified this gap in the market and invested a significant proportion of R&D expenditure into bringing additional quality parameters to be available in real time for operators. These days, instrumentation suppliers have managed to gain additional process-related data from existing devices; for example, a Coriolis meter when first manufactured in the 1970s could only determine mass flow. Now, there are some models that can determine physical fluid properties in addition to mass flow, such as viscosity, density, temperature, concentration, volume flow, pipe build-up and abrasion/corrosion. Not you can now get several variables from a single instrument. This additional information, coupled with big data analytics, can bring huge value to previously optimised processes.
In addition to an expansion of information available from traditional instrumentation, there are also new types of inline instruments available on the market to deliver critical process insights that would normally be derived from lab testing. This family of instrumentation includes gas analysers for industrial processes (particularly the oil and gas industry), liquid analytical devices and other field quality measurement devices that really bring lab capability into the heavy industrial environment. Not only do these novel instruments minimise complexity and reduce capital cost in gaining information from the process, but they can also deliver additional process information in real time — a real game changer for process optimisation.
Traditionally lab measurements have had the disadvantage of being slow and unreliable (transportation of samples, time taken to analyse sample and then manual data entry into control system). Continuing with these lab measurements continues to expose operations to unnecessary hazards, with lab technicians being in the field conducting manual handling of samples, analysing samples that could involve high temperatures and harsh chemicals. Elimination of these hazards and a reduction of labour costs by implementing instrumentation have delivered operations tangible benefits while conducting brownfield and greenfield projects.
The untapped value from optimising processes with additional online data previously only available from the lab is enormous. On one iron ore site, a great example of this was the utilisation of new, reliable technology such as an online moisture sensor. Mines normally sell their final ore product to customers at a specific moisture, with contract penalties imposed for all shipments above the quality parameters for moisture. If the operation delivers final ore product significantly below the quality moisture specification, the operation could miss out on that proportion of revenue. For example, the ore has a higher moisture limit of 9%, and in order to stay under the limit, typical shipments are exported at around 7% moisture. A 1% increase of moisture in the final product would not trigger any penalties from the customer; however, it would increase revenue by 0.7%. For an operation producing 10 Mtpa, that translates into a large revenue increase (in this example, over $8 million). This revenue increase stems from an improvement of online measurement being incorporated into the process control philosophy of the processing plant.
Bringing process data into your operation can bring your site into a safer, more profitable and efficient future — a direction that all shareholders would like to see their assets move towards. These online instruments are a catalyst for effective AI and other digital tools to really bring value to operations.
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