India, Russia favour digitalisation to mitigate Covid impact on industry
NEW DELHI: Finnish-Russian industrial digital solutions provider Zyfra has said in a report on Wednesday that companies in the field of machinery, metallurgy, mining and oil and gas from Russia and India should focus on speeding up their digital transformation.
Zyfra also called upon the companies to jointly develop industrial digitalization technologies and share best practices to minimise the negative consequences of the COVID-19 pandemic on their businesses and the supply chain.
“This logic suggests that companies which have aimed for efficiency are constantly involved in organizational changes, anyway. In the context of a crisis they will continue doing it, but we must not expect significant economic effects from these changes. Comprehensive and clear solutions in the field of Internet of Things and artificial intelligence have the potential to come to the fore,” said Igor Bogachev, CEO of Zyfra, told ET.
Remote IOT System For Machines
In a joint project launched in September 2019 MDCplus real-time machine monitoring and manufacturing data collection system developed by Zyfra – has generated a 20 per cent increase of production efficiency at different manufacturing facilities operated by Indian Railways.
The solution has been implemented at 10 factories and workshops in different regions of India. Zyfra has deployed the system, trained personnel, and is now providing technical support.
MDCplus collects overall data from all types of machines and monitors energy consumption, which results in substantial increase in machine utilisation and energy saving.
Since implementation, a 9 per cent increase in machine utilisation has been achieved immediately post-deployment. Further productivity growth was generated thanks to reducing unplanned downtime and due to the transparency of the process, increasing the level of overall production culture.
In context of the ongoing coronavirus (COVID-19) pandemic raging globally, Zyfra has announced the release of a cloud-based version of its MDCplus system designed for the industrial facilities to remotely monitor CNC machines.
The MDCplus can be reached at the edge, using an application programming interface in the cloud and an operator interface. Machines are connected with an edge software adapter. Cloud access to the data is available with web desktop, tablet and mobile devices. Servers provide reliable data storage in local locations, as well as guarantee maximum stability in accordance with the highest requirements.
The installation of the cloud-based version takes around 30 minutes and it eliminates the need to purchase and maintain expensive servers, with no support, training or integration service required. The solution allows access to the data from anywhere from a mobile phone or desktop machine.
“One of our European customers, a haulage and transport equipment manufacturer, has managed to reduce the negative effect of the COVID-19 pandemic with the help of a monitoring system to complete strategically important orders in time. The company has managed to set priorities and redistribute its orders depending on their urgency, while also keeping some machines off. It has helped to move 25 per cent of the workers to remote work without sacrificing total output,” said managing director at Zyfra, Pavel Rastopshin.
Digitalization of oil and gas companies
According to the report, the global oil industry is experiencing the biggest shock in its history, so oil and gas companies should implement solutions for automated adaptive planning and scheduling of production, logistics and service processes.
Production and Shipping Planning (PSP) includes production planning, shipment, warehouse and procurement planning and operations, as well as maintenance planning. The solution builds a complete digital twin of the planning process. It allows different deployment configurations: on-premises, cloud and hybrid. Cloud and hybrid deployment options are preferable when simulation and optimisation are computation intensive.
“Machine learning could leverage existing data to create finer and more precise business models. It could predict profits and losses in detail. This prediction happens in a timely manner up to real-time. So, the traditional 'produce at all costs' model could be altered or replaced by a 'produce in context' model. This shift allows energy companies to be more flexible and able to deal with low oil or gas prices,” Rastopshin added.
"Oil companies need to consider key task dependencies, priorities and constraints for decision-making. Thereafter, a machine learning model chooses an optimal scenario for the current situation. About 50 scenarios are assessed to choose one. This comes along with regular recommendations on plan execution and process improvement,” said Alexander Smolensky, artificial intelligence director at Zyfra.
According to International Energy Agency (IEA) projections, as demand plummets, the entire supply chain of oil refining, freight, and storage is starting to seize up, making it increasingly difficult to push new supply into the system.
The IEA has highlighted the risks posed by today’s market conditions for vulnerable producer economies. The organization’s initial estimates of 50-85 per cent drops in net income for selected producer countries in 2020, compared with 2019, were dramatic. But these declines could be even greater depending on the final extent of the demand drop and the economic slowdown. Even among the countries of the Gulf Cooperation Council, some of which still have a degree of financial cushioning against worsening market conditions, fiscal deficits are now projected to reach 10-12 per cent of GDP this year, implying additional financing needs of around USD 150 billion to USD 170 billion.
“Companies face an increased competition, which causes strict deadline clauses in the contracts. The volatility of commodity prices also require more frequent plan adjustment. Production and Shipping Planning (PSP) aims to automate the decision-making process with identifying statistically significant factors and model constraints for scheduling,” said Dmitry Lukovkin, international sales director for artificial intelligence at Zyfra.
All the real-life operations come with uncertainty in terms of time, resources, failure risk. Existing solutions often do not consider this uncertainty and provide plan, which is not only non-robust to changing constraints and conditions, but even the level of their robustness is obscure. To tackle this challenge. PSP offers a dynamic planning horizon (as opposed to static in most of the planning tools), considering uncertainties in timing of operations. Dynamic pricing and risk-margin control allows having a complete digital twin of the planning process, offering fully automated calculation of optimal prices for customers.
Scottish law firm Brodies LLP expects that a lack of on-site personnel will lead to delays and interruptions to supply and service delivery, and platform operations. Logistics providers may be delayed, or unable to, send supplies to offshore platforms. This could result in various platform operations, such as fabric maintenance, inspection, repair and replacement of equipment and drilling activities, being delayed or suspended. This presents significant consequences in respect of health and safety compliance and ultimately, energy production.
“The stimulus measures launched by the government to develop the digital economy in the country currently present a perfect opportunity to do this and implement these projects, given that, compared to the total investment volume, the cost of introducing digital technologies is small, yet they can yield results in just six months. What’s more, these results will be quite significant, resulting in up to a 10–15 per cent increase in labor productivity,” added Bogachev.
Source: The Economic Times
