Digitisation of chemical manufacturer will drive a huge wave of innovation

Author : tomlee03
Publish Date : 2021-04-14 06:30:28
Digitisation of chemical manufacturer will drive a huge wave of innovation

The implementation of digital technology can improve the cost-effectiveness of chemical manufacturer by improving flexibility, productivity and innovation. For example, by using complex analytical tools for collaborative research and development, companies can quickly accelerate innovation to gain competitive advantage. Many companies are turning to predictive models to make hypothetical simulations based on data to achieve strategic agility and operational brilliance. In addition, big data analysis plays a huge role in managing the continuous fluctuation of energy and raw material prices and catering to the changing needs of customers. Digital transformation enables companies to simulate the impact of price changes on consumer demand and final profits, which enables them to make real-time quotes for their prospects. In addition, they can share data with suppliers to cope with price and supply fluctuations.

Digitization will drive a huge wave of innovation. The latest development of digital technology provides unprecedented connectivity, granularity and speed for accessing, processing and analyzing large amounts of data. In addition to mobility, cloud computing and memory computing, the industrial Internet of things, machine learning and blockchain will also start to become game changers for chemical manufacturers. These three trends are jointly challenging the existing strategy and creating a perfect storm for the chemical industry. Proximity of customers and raw materials, intellectual property and know-how may no longer ensure sustainable competitive advantage. Early adopters of innovative business models have the opportunity to become digital disruptors.

As the chemical industry is an asset intensive industry with advanced capabilities of capturing, storing, processing and analyzing data, a large number of factory, asset and operation data can be combined with advanced algorithms to simulate, predict and regulate maintenance, so as to increase the availability of assets, optimize normal operation time, improve operation performance and prolong service life.

In addition, new industrial Internet of things and machine learning technologies still have a lot of untapped potential in the supply chain. Consider the use of advanced analysis to improve the accuracy of forecasts, thereby improving the overall sales and operations planning process and related KPIs. Advanced analysis and machine learning can also be used to reduce the risk of supply chain disruption. For example, in the case of natural disasters, goods can be automatically rerouted to achieve the goal of on-time delivery and customer commitment at the lowest cost.

From a supply chain perspective, some parts of chemicals (such as pesticides) are threatened by counterfeiting. Blockchain single ledger verifies the integrity of the product, because the records can be traced back to the manufacturer of the product, or even the manufacturer of its predecessor agent. In addition, blockchain can help ensure the physical integrity of products. BASF last year launched a pilot project for "smart trays" (trays with embedded active, battery powered, wireless transceivers). These systems can record and transmit the location and movement of all pallets, as well as physical conditions, so as to seamlessly track the "accidents" that may occur when pallets and their products arrive at the final destination.

Big data challenges for chemical manufacturers

BDA provides an obvious way to simplify and guarantee the management of chemical supply chain. When we say "big data", we are talking about being able to effectively process it, efficiently process it in real time, understand it, and use it to influence decision support. Other industries have developed best practice models, but we can see some key ways to benefit chemicals:

By shortening the product life cycle, mass customization and expanding the regulatory framework for product innovation and R & D

Analyze valuable data generated by manufacturing and asset management to predict model performance

Handle complex transportation and logistics transactions in supply chain management, track and track goods, and respond to any potential problems in real time

Understand pipeline, customer and product profitability of any granularity in sales and marketing. With the right tools, you can simulate, focus on or commit to the most profitable deals, and respond quickly to customer needs

Proper management of big data can not only make decisions faster and more effectively, but also realize business transformation or innovate business models through previously impossible processes. That's what drives demand.

Category : business

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