The far-reaching impact of digitalisation on the fertilizer industry
Fertilizer use has increased by almost 6X over the past four decades, keeping pace with a population that has increased from 3.1 billion to 7.4 billion over the same period. Fertilizers actually feed about 50 % of the world 's population, which amounts to about 20 billion meals a day.
The combined value of the production of raw materials from nitrogen, phosphate and potash was estimated at $500 billion in 2020, while the market value of goods sold by fertiliser firms exceeded $300 billion. Compared to projected current sales levels of global crop defence at about $80 billion, crop seed and biotech at $60 billion, and biologics at $10 billion, fertilisers are by far the largest segment of the input industry. It is projected that the global fertiliser industry has invested between $86 and $91 billion in new mines and fertiliser-producing facilities between 2015 and 2019, with a comparable amount of investment between 2010 and 2014.
The Need
Internet of Things (IoT) and M2M communication is yet to mark its anchored presence in fertilizer production, though these are commonly observed buzzwords circumrotating around fourth industrial revolution. Over the last decade, chemical industry is observed to be lagging behind on digitalization issues in comparison to other important industrial sector, and fertilizer industry is not even awaken to adopt disruptive transformation. The question then surfaces as to how the fertilizer industry can succeed in the transformation to 4.0, and leverage its benefit in amplifying plant efficiency?
The efficient future of the fertilizer industry is yet to be materializing. Plant operators must meet the ongoing need to integrate cutting edge technology with production cycles. In parallel, they need to develop new value-added propositions, often with innovative service elements, and often in specialist target markets.
Companies are likely to pour money into the Internet of Things (IoT), and one area of particular interest to investors is IoT connected factories. Fact.MR expects smart factory set-up in fertilizer sector has potential to bring down risks related costs down by almost 18%, and increase plant efficiency by over 14%, just by utilizing existing proven technologies, The pressure to drive down costs through the processing and storage of raw materials to the supply chain phase in the fertiliser industry is unrelenting, but there can be no compromise in reaching the highest standards and future-looking technology adoption in this impeded industry for both proven and creative product lines.
The introduction of predictive maintenance models into the production cycle of a fertiliser manufacturing plant may be a first step to be taken in this process.
The Explanation
Diverse raw materials are used in the production line of a fertiliser plant. In order to form an individual product, these raw materials should be transported through pipelines and combined in precisely weighed quantities at the correct moment. An empty material storage tank can have serious effects on the entire manufacturing process. Only in the case of a "sudden" failure will faults or missing services be identified retrospectively. Sometimes, the resulting downtime could mean substantial increased costs for the operator of the chemical plant. "As a result," traditional "maintenance comes either too early (i.e. the components do not need replacement yet) or too late (the component is already worn down).
The more efficient way – predictive maintenance
A different direction is taken by predictive maintenance. In contrast to reactive maintenance, "on-demand" predictive maintenance is carried out based on the components' real-time performance data.
The fertiliser plant is fitted with sensors that are connected to a local network or the internet (so-called cyber-physical device chips). Once this data is processed, a real-time image of the fertiliser plant (digital twin) can be generated by the fertiliser plant operator. If the data is evaluated over a period of time or compared with data from other plants with similar components, the operator may make assumptions as to the remaining life of a particular component. As a key advancement, predictive maintenance offers that a feature can be managed "precisely" based on the available real-time data due to its maintenance requirements. This will reduce the total cost of the chemical plant 's operation as well as improve the productivity of the plant.
TInfrastructure as a service
A fertiliser plant operator can subcontract the data analysis and maintenance of a fertiliser plant to an IoT service provider. Given the current useful know-how from the manufacture of the machines used in the chemical plant, the manufacturer of the machines should in particular be regarded as an IoT service provider. If more than one chemical plant is subcontracted to the IoT service provider, the combined data of all chemical plants will help to further enhance the accuracy of the forecasts. The IoT-service provider might also consider offering their machinery as a service to the chemical plant if they felt secure enough. The IoT-service provider is therefore liable for the "delivery and operation" of the plant and thus assumes the risk of defects.
TChallenges of implementation and operation
The large amount of data generated and collected in real-time that can become almost unmanageable is one of the key challenges of incorporating predictive maintenance in the operation of a fertiliser plant. In order to be analysed, this information needs to be of good quality. Therefore, storing, upgrading, processing and transferring this information is a key challenge for applications for predictive maintenance and requires a secure and efficient network link.
Moreover, it is becoming increasingly important to have effective security against cyber-attacks. Successful cyber-attacks in the past have demonstrated that businesses should not underestimate this risk and should adopt state-of-the-art standards and precautions. A pillar of IoT and digitalization in the chemical sector is the effective implementation of predictive maintenance business models. With the right know-how, tremendous potential for added value can be exploited, despite initial costs. In this respect, creative companies will play an important pioneering role and establish standards themselves, thus helping to shape the chemical industry 's future.
