Smart Management: Predictive maintenance for better performance

Predictive maintenance for better performance

The uncertainty due to fluctuations in oil prices has played an important role in pushing the oil and gas sector towards application-based management. The introduction of these advanced solutions has significantly improved performance as well as reliability through better asset management. The use of intelligent predictive maintenance (IPM) with the help of internet of things (IoT) has provided better insight into the future of equipment. The sector has indulged in the use of industrial IoT to form an intelligent interconnected network spanning its entire value chain. This web-based system has ensured timely maintenance of equipment by efficiently identifying changes in the production process and predicting equipment failures.

Key concepts

A number of systems and concepts, such as IoT, smart solutions, cloud computing, internet of services and smart factory, have contributed to the development and success of IPM.  IoT is connecting people and devices to enable the collection and sharing of information on a real-time basis through common connectivity. The data is stored, processed and managed over the internet, instead of a local server, through cloud computing. It eases the process of sharing huge amounts of data that is generated through IPM. Internet of services, a next-generation technology, provides the infrastructure to support a service-oriented ecosystem for this online data. The web-based services interconnect people, processes and devices. They assist in providing maintenance-related decision support at one location based on data from another location. The data generated and collected by smart products and services form the basis of smart solutions in the era of IPM. Smart products and services provide new functions based on network connectivity and service assistance over the internet. Smart solutions such as sensors are successful in mitigating equipment failure through early detection of faults. A smart factory provides a digitalised and connected production platform wherein operations form part of an intelligent system and all equipment is integrated across an entire supply chain network. This concept is considered to be an important outcome of the fourth industrial revolution.

Application in the oil and gas sector

IPM technology is currently being used in all three business processes of the oil and gas sector, that is, upstream, downstream and midstream. The upstream process consists of exploration, development and production of crude oil or natural gas. The midstream activities include the processing, storing, transporting and marketing of oil and gas. The downstream activities include the refining of petroleum crude oil and the processing and purifying of raw natural gas, as well as its marketing and distribution. The data before generated from the IoT-based systems help detect and reveal abnormal patterns in the business activities on a real-time basis.

One of the key challenges faced by oil and gas companies is high operational cost because of wearing pipeline networks, and dated monitoring methods and devices. Large losses due to operational inefficiency have led to investment in data-enabled infrastructure. Oil and gas companies are increasingly using smart solutions which are highly effective in generating new data for IPM analysis. Smart technologies such as vapour sensing tubes, optic fibre cables, and other sensors hear the sound variations and detect pipeline leakages. The real-time data generated from these sensors is then used for evaluation, analysis and prediction. This data-enabled monitoring infrastructure has improved reliability and operational performance through better asset management.

Features of predictive maintenance

Predictive analytics: The use of predictive analytics in IPM helps in the identification of issues which are usually difficult to foresee. However, the comparison of historical operational data of assets to real-time operating data has made it possible to detect even minute changes in the workings of equipment. These behavioural changes predict the future course of assets accurately.

Optimised performance: Predictive analytics provide early warning against issues and potential failures of the asset. Timely action, thereafter, ensures smooth working of the asset at full efficiency.

Smart and easy maintenance: The management of oil and gas operations in remote areas is a key challenge as the deployment of traditional methods for inspection and monitoring is quite expensive. However, the use of web-based asset management systems has made it possible to effectively monitor the performance of these assets from far-off places. Besides, it has also made decision-making easier by comparing the performance of assets in remote and mainland areas on a real-time basis.

Advantages of IPM

Maintenance, being a recurring activity in the oil and gas sector, contributes to a large chunk of operational costs incurred. Besides, it leaves out scope for failure as it is conducted at a predefined time interval. The adoption of predictive maintenance reduces the possibility of failure through early detection of risks. It also cuts down the need to undertake periodic inspection and maintenance of assets, thus lowering operational expenses.

The approach to maintenance activities in the oil and gas industry has shifted from preventive to predictive, based on IPM technologies. The traditional maintenance approach was good at inspecting the equipment periodically and providing needed repairs. However, it did not completely eliminate the possibilities of machinery breakdown, leaving scope for failure. However, the introduction of predictive maintenance has streamlined maintenance activities. It identifies equipment that requires servicing and determines the exact cause of the problem. The accurate and timely diagnosis is what has made predictive maintenance more reliable.

The infrastructure in the oil and gas sector was put in place a long time ago, based on the requirements and technologies that were prevalent at that point of time. Without proper monitoring, the likelihood of the failure of this ageing-equipment increases multifold. The use of smart solutions such as sensors helps in avoiding potential threats due to the ageing infrastructure. Besides, the latest equipment comes with pre-installed sensors and cables for data collection for IPM.

The physical inspection of pipelines exposes personnel to a hazardous environment in the oil industry. At times, it is not even viable to access and examine the workings manually. However, IoT-based predictive maintenance ensures infrastructure is working efficiently at optimal levels without any health risks. Moreover, the increasing use of IPM in the oil and gas industry has increased the demand for a skilled workforce.

Conclusion

IPM systems with smart solutions have proven to be efficient in mitigating risks and improving productivity. According to the US Department of Energy, the implementation of predictive maintenance by oil and gas companies results in a reduction in maintenance costs by 30 per cent, the elimination of breakdowns by 70 per cent and a reduction in downtime by 40 per cent. Predictive maintenance techniques not only identify possible risks but also provide possible solutions. Therefore, with the use of predictive and prescriptive analytics, IPM determines future equipment failure and recommends actions. The oil and gas industry has been successful in increasing productivity by minimising its maintenance and operational costs with the deployment of IPM.