Many resources companies still rely on static, error prone data sources to estimate production costs, operating capacity and yields, however this method is no longer adequate to compete in today’s market.
Given that the resources industry faces volatile market prices, increased costs for operations and new competitors, the Internet of Things (IoT) can leverage real-time insight, and in the process create new business models, and products and services.
According to a whitepaper by IDC, The IoT Imperative for Energy and Natural Resource Companies, the worldwide IoT market will represent more than $1.3 trillion in 2020, supporting 30 billion connected endpoints.
At the heart of IoT-enabled digital transformation is the connection of devices and the use of digital technologies, as well as the generation and analysis of data that is used to derive meaningful intelligence across the business. Resources companies can be a part of this transformation and achieve significant returns by developing an IoT strategy from the field to the office.
Since resources companies are asset-heavy operations, the natural place to see value in IoT is how assets in the field and plant are arranged. IoT can also be used for monitoring asset health, tracking costs, managing the portfolio, identifying activities, and reducing risks and constraints. Some North American oil and gas companies have seen improvements in utilisation and yields by 20-30% via IoT.
For individual companies, there are three major benefits:
- Increased revenue: Agility in product change-overs and plant turnarounds can lead to increased revenue. Proof of concept projects in several investor-owned utilities have shown that even new revenue models, like reliability as a service in utilities, can lead to revenue growth in the 20-25% range.
- Higher levels of productivity: The ability to combine IoT enabled instrumentation with machine learning models will lead to optimised and, in some cases, self-healing processes over time.
- Asset utilisation: The combination of IoT-enabled instrumentation and machine learning will also enable the ability to preempt failures and improve process changes. While the benefits will manifest differently by industry, other ENR companies can lower inspection costs, increase uptime, and manage change overs with a 40% improvement in asset utilisation, based on application of operational excellence and IoT technology in oil and gas companies.
Examples of where IoT and the resources sector can thrive
- Resources companies often deliver products that they typically lose sight of. But a key part of an IoT strategy is to better connect to a customer’s process to get the real-time feedback that is needed. This closed feedback loop between the product ‘in use’ and operations creates an opportunity to quickly act to improve performance or satisfy customer needs.
An example is a petrochemical company working with a chemical/refiner company to monitor performance of a new blend. The chemical company’s process feeds sensor data directly back to the petrochemical company which in turn allows the petrochemical company to make blending adjustments in near real-time. One oil and gas company that integrated formulation directly with the refining operation experienced up to 30% yield improvements combined for both companies.
- Digital twins are used today to manage the performance, effectiveness, and quality of fixed assets such as utility grids, refineries, plants, and mining equipment. Advanced visualisation, IoT, and analytics applied to these assets enables companies to take a strategic approach to asset management, where potential problems and maintenance are predicted, leading to a reduction in downtime, greater productivity, and improved customer satisfaction.
An example of this is a mining company which uses sensors on its assets to feed data back to a detailed digital twin of the excavation site. The model is used to adjust feeds and pressures on equipment to develop asset performance and maintenance scenarios. These scenarios are used to balance asset life, yield, and site performance. One iron-producing company in Latin America has seen 25% improvement in asset utilisation through asset performance management.
Key considerations for resources companies
Focus on business goals: Digital transformation with IoT is not ultimately about technology, but about the greater business outcomes enabled by the technology: how companies can innovate new/simplified processes and new business models, and consequently improve products and services.
Plan and invest now: Resources companies must develop a plan and invest now to improve ‘insight to action’ for operations. By utilising new and innovative IoT technologies, companies can reduce costs, increase quality, improve compliance, and lower operating risks.
Embrace and utilise innovations: New technology investments are driving convergence of processes, thereby collapsing the value chain of enterprise activities. These are investments that are not just proof of concepts or pilots; they are taking existing IoT-type technology, applying new concepts, and delivering the results expected of IoT. Companies that quickly embrace and deploy these innovations will improve their performance and competitive advantage.
Change operations with business applications: Companies will require both their existing and new business applications to support new and innovative ways of operating in the future. These applications should be built on top of new capabilities enabled by IoT and complementary technologies.
Transform the organisation: Resources companies must transform their organisation to support increasing IT/OT convergence and increasing use of mobility and analytical capabilities to streamline business processes.
Trends in the adoption of IoT
- In 2018, companies investing in IoT-based operational sensing and cognitive-based situational awareness will see 30% improvements in the cycle times of impacted critical processes. This is based on IoT projects currently in operation at mining operations, electric utilities, and oil and gas upstream operations.
- By 2020, nearly 20% of operational processes will be self-healing and self-learning, minimising the need for human intervention.
- By 2020, 25% of utilities will integrate asset performance management investments with sensor data and cognitive capabilities, boosting asset efficiency and reducing maintenance costs.