Remote Operations Centers: from vision to implementation

Considerations for designing what needs to feed into an Integrated Remote Operations Center (IROC) – part 2 of the blog “10 Lessons from 10 years of remote operations centers”.

In my previous blog I delved into the “people” and “process” sides of the famous business mantra and solutions dimentions1. We explored the first five lessons about the IROC vision and planning: remote work as a catalyst for innovation, practical ways to upskill existing talent, revisit work procedures, manage their constant evolution and anticipate the unexpected.

As we continue our journey through the “technology” and “information” components of the framework, here are the next five lessons we learned from the IROC implementation phase:
By Eduardo Lima LinkedIn
Global Mining Industry Consultant
Digital at ABB
About the author
Eduardo joined ABB Brazil - field service engineering - in 2005, where he supported the latest technologies in process and electrical automation, developed and implemented a remote diagnostic service center as well as a plant asset management solution. As a global product manager at ABB Switzerland since 2016, he developed and launched the Operations Management System for mining and was responsible for ABB's digital mining portfolio globally. Currently, as a Global Industry Consultant, Eduardo collaborates with mining customers and an ecosystem of partners to advance mining digital maturity by building digital roadmaps, implementation strategy and business case evaluation.

6. Laying the groundwork

Implementation of any kind of remote operations begins with solid communications network within and between sites to reliably transmit voice, video, data feeds – including the use of satellite internet for inaccessible areas. Industrial-grade cyber security measures are a must. There are many other considerations for designing what needs to feed into an ROC, depending on your priorities.

For instance, in process industries, the initiative is often triggered by the need to consolidate different system HMIs in a Central Control Room. ABB provides a unique way to seamlessly run a mix of multi-vendor systems from one operator station (DCS, SCADA/PLC, electrical equipment, video surveillance, with interfaces for MES, CMMS, ERP, mobile apps to read / write data from/to the control system).  

Remote supervision across five pulp mills in Chile

In another example, a mining company first moved the trucks dispatcher into an IROC and hired analysts to support the dispatcher and find opportunities for improvement. Then, together, we investigated ways to automate some of the insights delivered by those analysts (production not going in the direction it should in terms of recovery, the cycle time going up – trucks are taking longer to reach the crusher, etc.). This helps determine the infrastructure required to receive the data.

A step further is to look beyond the process, e.g. start monitoring the information about the environment, safety, contractors violating speed limits and other areas. We are already building the Edge/Cloud infrastructure supporting such approach for GoldFields greenfield operations. It means constructing a comprehensive data lake that consolidates information from diverse sources, bringing real-time analytics to visualize trends, detect signals and automate various KPIs.

GoldFields Salares Norte

As I could see though my personal engagement in five mining IROCs (ArcelorMittal, Teck QB2, AngloAmerca Escondida, Antofagasta Los Pelambres and GoldFields Salares Norte), collaborating with a diverse ecosystem of partners enriches the quality of insights and many other aspects of managing remote environments. E.g. At the early stages of IROC design using ABB’s control room solutions it brings a lot of value to also involve ergonomics experts, focusing on human factors such as optimum seating distance, information presentation, task simplification, noise and light optimization. This increases the number of systems a single operator can manage, improving situational awareness and hand-over, reducing risky situations associated with telepresence, change blindness, workload, etc.

Ergonomic design of central control rooms (CCR) / ISO 11064

7. Vigilance against issues

Digitally connecting the organization with a remote support team presents an immediate opportunity to change how issues are detected, diagnosed and solved in the field. A more proactive approach to Asset Health and Performance across multiple sites is a good example of problem-solving on scale – already happening in the pulp and paper, mining, metals industries. e.g., A team of reliability experts located in a remote support center conduct the analysis of plant-wide vibration data received through remote monitoring of site assets. They follow up with the assigned plants and respective equipment manufacturers on the recommended actions and conduct further analysis as required.

Since Covid-19, our customers started using augmented reality glasses to facilitate issue resolution, carry out remote inspections, installations and Factory Acceptance Tests (FAT). We see a growing interest in recording such remote visual support sessions to safeguard and reuse the knowledge.  e.g., This will facilitate the creation of more immersive augmented and mixed reality training courses for new recruits.

If site personnel still use paper manuals for troubleshooting, central teams of subject matter experts can adopt  ABB’s no-code tools to convert paper or PDF files into a more appealing mobile app for rich digital work instructions with pictures and videos. The same app can be used to simplify collaboration between the on-site and remote teams - to improve adherence to safety procedures, report incidents, collect witness statement records, perform root cause analysis and track corrective actions “on the fly”.

You can also connect CCTV cameras in the control room to video analytics, e.g. use image detection to identify the number of people inside a substation, field operators without a helmet, dust accumulation, spills, etc.

Embracing Machine Learning (ML) algorithms for anomaly detection as well as “codifying expert knowledge” will enable earlier identification of irregularities and preventing potential downtime.  Transforming reliability experts into "citizen data scientists" will empower them to utilize AI/ML tools for predictive maintenance, introducing a new dimension of data-driven vigilance against issues.

The goal is not only to enhance situational problem-solving, but also recognize when an issue calls for a well-thought out, systematic solution and a more strategic approach. 

8. The heart of efficiency and speed

With the appropriate data infrastructure and technologies, you will be able to apply the same problem-solving approach to the end-to-end value chain, providing more efficient ways to run, improve and change your business practices. Increasing the speed at which you identify and respond to changing conditions is at the heart of IROC’s “raison-d’être”.

You only centralize functions when it actually speeds up decentralized teams and supports their innovation - without administrative overhead. 

Pulp & paper example: Unifying the approach to manufacturing execution across the entire production fleet: “How do we gain competitive advantage in the areas of operational excellence and agility?”

Cement example: Bringing Process and Production Information Management (PIMS), Manufacturing Execution System (MES), Laboratory Information Management System (LIMS) into the same platform, with consistent, validated data across multiple plants all over the world. Making financial numbers from ERP tightly connected to the operations, giving a dollar value of each production plan: “If I follow this sequence, this is the cost of energy. This is the production scenario I must follow today not to exceed the emissions limit and to avoid penalties. “

Mining example: Maximized productivity and focus on mobility: “I can reduce extra-hours of people on-site because I planned jobs and resource allocation in a better way”.  “I can model the stockpile and change the sequence of jobs to move the material with the right quality - depending on the required grade “.

Metals example: Adding more intelligence on the top of the data from various metals sites or process areas, e.g. in a smart melt shop: “How should my crane be positioned to make things faster and reduce thermal losses?”  It’s a real milestone towards steel melt shop autonomy.

9. The path to autonomy

Gradual transition towards autonomous operations is a carefully calibrated process. It starts with specific areas.  e.g. In mining, you could start with remote charger robot for blasting, autonomous haulage systems or stockyard management, and incrementally expand the scope as technology matures. An Integrated Operations Center plays an important role in analyzing various aspects of operating a mine, a crusher, a mill, a flotation plant, tailings and comparing that with different types of ore that a particular plant receives, the variations in grades. This is how you start seeing patterns, identifying the best set points for each of the areas depending on the type of the material.

The same applies to any industry-specific process. Humans are actually doing quite a good job through automation and advanced process control – driving the most important quality parameters to target. Having operators working in the same operations center has an impact on their decisions and real-time process optimization.

According to EY, just by letting people sit together, discuss and compare, there is a space to remove the silos and improve how they are running different sites by about 20%.

Because autonomy involves much more than technology. It involves continuous learning, adapting to evolving roles, building trust in data and willingness to “teach” machines. Exploiting more data sources and ML/Deep Learning algorithms will offer opportunities for AI systems to learn from experts and start assisting operators in making optimization more:

  1. Adaptive: Dynamically adapt highly variable processes to a wider range of scenarios and helping less experienced operators
  2. Strategic: Advise operators in case of competing optimization goals and strategies
  3. Creative: Quickly learn how to respond to unknown system conditions or changing behaviors difficult even for experienced users

Process area models will evolve to continuously retrain themselves based on outside disturbances. This will give confidence to companies, making them more comfortable with having fewer human operators in plants through more autonomous operations.

10. Simulating excellence and decarbonization

Finally, the move towards a centralized control tower is about bringing the ability to anticipate changes, test operational excellence and decarbonization strategies, realize them across various functions and sites - consistently and reliably.

The art of simulation will play a pivotal role here.  Starting from control system simulator for design,  configuration data transfer, operator training, process design modifications and upgrades. Through establishing a modern energy management system orchestrating supply and demand optimization for all energy types and emissions tracking. To creating a digital twin of your operations, starting with a specific area, e.g. a stockyard in mining and metals.

With the rapid development of AI assistant / co-pilot solutions you’ll gain the ability to simulate a myriad of scenarios. Digital Twins will not only help optimize strategies but also let you anchor expert knowledge to 3D models to prevent the loss of skills, facilitate new people onboarding, training and support. As data analytics gets easier to implement, more companies will embrace AI to reach sustainability targets, since there is no way to reach those targets with manual setpoint adjustments alone. AI will help process industries reduce their carbon footprint and improve their reputation.

As we conclude this exploration of ten lessons gleaned from a decade of participation in Remote Operations Centers, the path to success becomes clearer. Embracing the interplay of people, processes, data, and technology lays the foundation for transformation. Collaboration, adaptability, and a resolute commitment to continuous improvement steer us towards operational excellence, safety, and strategic foresight. These lessons are more than just insights—they serve as a practical roadmap backed by first-hand experience of industry leaders and innovators. What opportunities do you see for your company? Use the Contact Us form below to start a conversation or post your comments on LinkedIn .

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