Zyfra: Leading the SCM Revolution

Zyfra: Leading the SCM Revolution

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Alexander Smolensky, Head of Zyfra Industrial AI, Zyfra Alexander Smolensky, Head of Zyfra Industrial AI
Alexander the Great was, without question, one of the greatest conquerors of all time. The transformative changes he introduced into the supply chain strategies played a critical role in empowering the Macedonian military system. The revolutionary logistics tactics enabled him to significantly improve the mobility of his army and thwart the competition, thus expanding his dominion across two continents. This strife for dominance that prevailed two thousand years ago can be compared to the competitive business environment of today. And like that era, logistics still plays a key role in determining the success of businesses across marketplaces. Hence, organisations need enhanced speed and mobility to operate efficiently. This is where Zyfra—a provider of digital logistics solutions—makes a mark, empowering its clients to step into the next stage of supply chain evolution with its AI, robotics, and IIoT-based products.

The company develops robust digital solutions for the heavy industry, including machinery, mining, metals, oil & gas, and chemical sectors. Zyfra leverages IIoT, big data, and artificial intelligence to facilitate digital transformation for its clients operating across industries. The company empowers enterprises in the heavy industry to augment their logistics capabilities in several countries, including Finland, Russia, India, France, Germany, Turkey, Chile, Peru, South Africa, and Morocco. Zyfra assists these industrial enterprises in using their data to enhance production efficiency and safety for the benefit of the people and the environment.

“Our primary goal is to help clients in enhancing the integrity and reliability of their industrial data, and using it to augment their overall workflow,” says Alexander Smolensky, head of Zyfra industrial AI. According to Smolensky, logistics processes require the management of supply chain components across a vast geographical area, which makes monitoring and controlling crucial equipment a difficult task. For instance, the logistics operations for manufacturing organisations comprise the movement of raw materials and finished products. In such cases, any inefficiency in the supply chain can lead to a significant loss of resources.

Many a time, the root cause of this issue is in the fact that organisations still leverage traditional systems that are hard to maintain. To overcome this, large enterprises are investing heavily in digitalisation.

However, small and medium-sized businesses often cannot afford to incorporate expansive technological transformations. Zyfra assists such organisations in seamlessly augmenting their workflow with its powerful and versatile IoT and AI solutions.

Our primary goal is to help clients in enhancing the integrity and reliability of their industrial data, and using it to augment their overall workflow


Zyfra’s offerings are designed to integrate with the digital elements of industrial production and business processes, thus enabling the automation of technology-based operations. By merging the siloed components of the workflow, Zyfra creates an integrated digital production space using AI. To illustrate the unprecedented value Zyfra brings to the SCM space with its robust production and shipping planning (PSP) solution, Smolensky highlights Zyfra’s association with one of the largest oil companies in Russia. This particular company had faced unsurmountable challenges in planning the production, shipping, and distribution of its petroleum products. The management of 60 different petroleum products, more 1000 varying factors affecting the process, and over 2000 points of sales, and the different methods of transportation had made planning a tedious task requiring the efforts of 20 high-skilled specialists. Even though the company conducted the planning process every month, the plans would become outdated during implementation due to the changing market conditions. Even with the integration of off-the-shelf optimization software, the company failed to meet several strict deadlines and incurred high penalties, which often comprised up to 5 percent of the total costs. That was when the company turned to Zyfra. To optimize the planning processes of the oil company, Zyfra implemented the end-to-end shipping a downstream supply chain optimal planning solution through its Zyfra PSP. Consequently, it accelerated the calculations (less than 1 minute instead of 5 hours) and automated planning and scheduling, thus significantly reducing human efforts that went into the planning. Equipped with Zyfra PSP, the oil company was able to create precise daily plans for the next 30 days and 10-day plans for the next 90 days. The resulting optimizations not only enabled the client to cut penalties and decrease overproduction, but also free up the excessively used storage facilities. Thus, Zyfra PSP empowered enterprise-wide cost optimization without long-term capital expenditures.

“We assist our clients in gathering relevant information on every piece of technology they have, and we do that with minimal investment from them,” says Smolensky. To consistently address the needs of clients, Zyfra is investing heavily in the utilisation of emerging data and information technologies. Considering the fact that the automation of the technological process remains low in the manufacturing landscape, Zyfra continues to work toward its goal of increasing the level of automation.

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Zyfra

Company
Zyfra

Headquarters
Helsinki, Southern Finland

Management
Alexander Smolensky, Head of Zyfra Industrial AI

Description
Zyfra specializes in the development of robots, AI, and IIoT-based solutions for the heavy industry, including machinery, mining, metals, oil & gas, and chemical sector. Zyfra leverages IIoT, big data, and artificial intelligence to facilitate digital transformation of the industry and overcome the prevalent operational challenges. Zyfra’s mission is to empower industrial enterprises in using their data to enhance production efficiency and safety for the benefit of the people and the environment. The advanced digital solutions offered by Zyfra are designed to enable a gradual shift toward greater levels of productivity with robotics and other emerging technologies

Zyfra News

Artificial intelligence to detect of metalworking machines anomalies

Zyfra, Finnish-Russian industrial digitalization leader, has developed predictive analytics solution powered by machine learning to enhance the capabilities of metalworking machines by detecting of anomalies in technological process and identifying their possible cause.

Zyfra PdA solution analyses the real-time data from CNC machines, alerts users whenever an anomaly emerges, and indicates the possible cause while giving recommendations for further actions. The system classifies a range of anomalies like tool quality, operator error in case of incorrect operating modes selection and machine failure.

Manufacturers of large-dimensioned products made of expensive materials face a detect defection problem. Defects are caused by many factors such as the quality of the cutting tools, technological faults, equipment wear, etc. There is a need for an intelligent system which will take into account all the necessary information from equipment monitoring systems, evaluate the impact of this information on defects and help operators and technologists to make decisions, said Alexander Smolensky, Business Development Director of Zyfra.

Metalworking machines failures might lead to defects in manufactured parts or cause equipment to break down. Implementation of the system results in cost reduction of manufactured parts, improvement in product quality and decline in spoiled products amount, as well as reduction of maintenance and repair costs and equipment downtime.

According to Vason Bourne independent research firm, over 80 percent of companies have experienced an unexpected outage within the past three years. Nearly three-fourths of organizations say zero unplanned downtime is now a top priority or the No. 1 priority for their company. The average cost of unplanned equipment downtime is $260,000 per hour, according to research conducted by Aberdeen.

Implementation of Zyfra PdA is envisioned for CNC machines embedded with MDCplus real-time machine monitoring and manufacturing data collection system. The operating principle of the equipment monitoring system is that each machine automatically transfers data about its own performance into a single digital system. Data about the equipments condition and workload, and its operating mode, are sent from the machines to computers and other devices equipped with special software, making it possible to promptly eliminate downtime and providing an objective evaluation of the quality of machine operators work.

Zyfra has connected 10,000 CNC Machines to its MDCplus real-time machine monitoring and manufacturing data collection system. The projects have been implemented in Bulgaria, China, Finland, France, India, Romania, Turkey and Singapore. India has become the key foreign market for Zyfra with more than 500 CNC machines connected to MDCplus system in 2019. By 2021 the company is looking at more than 2,000 MDCplus installations in India.