Читать книгу Profit Maximization Techniques for Operating Chemical Plants - Sandip K. Lahiri - Страница 50

The following facts regarding data have changed the business outlook in recent times:

 Rapid increase in data volume: The number of delivered sensors globally has increased sevenfold from 4 billion in 2012 to greater than 30 billion in 2016 (Mckinsey). Data has not only increased exponentially in volume but has also gained tremendous richness and diversity. In the chemical industry, data is not only generated from various flow, temperature, and pressure transmitters but also from cameras and analyzer to vibration monitors, enabling richer insights into process behavior.

 Falling IoT sensor price: There was a 50% reduction in IoT sensor price between 2015 and 2020.

 Cheap computational power: Better processors and graphics processing units increased investment in massive computing clusters, often accessed as cloud services, improvements in storage memory, etc., have recently increased computational power.

 New data analytic tools: In recent times, many new tools have been coming to market to convert this flood of raw data into insights and eventually into profit.

 Machine learning and artificial intelligence: These new generation algorithms are rapidly replacing the old method of calculations and emerge as new data analytics. Both data and computational power enable next‐generation machine learning methods, such as a deep learning neural network.

 Value creation: As a consequence, data has become the new oil of the chemical industry – and the best way for companies to generate and access is to digitize everything they do. Digitizing customer feedbacks provides a wealth of information for marketing, sales, and product development, while digitizing manufacturing processes generates data that can be used to optimize operations and improve productivity.

The confluence of data, storage, algorithms, and computational power today has set the stage for a wave of creative disruption in the chemical industry.