From Sensing to Sensemaking: Converging Big Data with Plant AI

As process industries across the world become more connected, networked, and integrated, there has been a consistent surge in the volume of data generated across the manufacturing value chain. The high-fidelity data that is generated by sensors and other wireless devices, however, currently yields inadequate insights for value creation. This makes a case for digitalizing plant operations in a way that meticulously leverages the plant’s digitized sensor data.

Frost & Sullivan finds that less than 5% of a plant’s generated data is used. The primary reasons for this gap are improper data management strategy, limited application expertise, missing data, and a sheer lack of resource availability. As customers realize the benefits of co-relating different types of data using combinational analytics, they can achieve new outcomes. This will encourage process industries to significantly increase their digital spending. Already, more than 50% of customers claim they will invest two times more in analytics over the next two to three years.

Frost & Sullivan’s unique thought leadership paper, Yokogawa‘s Synaptic Business Automation —Converging Intelligent Sensing with Plant AI, will assist you in unpacking the value levers of digital transformation, understanding the power of melding sensing with plant artificial intelligence (AI), and evaluating high-potential application areas.

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“The blurring of traditional automation boundaries is steering the development of innovative business models. Edge computing platforms are resulting in democratization of analytics and near-real-time interfaces with sensing systems,” said Muthuraman “Ram” Ramasamy, Automation & IIoT Industry Director at Frost & Sullivan. “The industry understands the imperatives of digital, but the challenge resides in the ‘how’ of digital. This will require customers to partner with accomplished domain experts who can not only help structure a digital roadmap but also have strong AI application capabilities over plant data and comprehensive expertise over a manufacturing value chain.”

Yokogawa delivers solutions that support improved productivity across the plant life cycle, from the management level to the operations level. Its industrial automation (IA) business concept, Synaptic Business Automation, leverages the company’s business and domain knowledge to drive sustainable value creation by blending intelligent sensing and advanced analytics. The shift from sensing to sensemaking allows customers to realize a closed loop from data extraction to value creation, fully utilizing the gathered high-fidelity plant data. Yokogawa’s practical approach of Observe, Orient, Decide and Act (OODA) improves customers’ outcomes from data that is captured from the plant.

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Currently, more than 90% of plant data contains noise, which obscures patterns that could otherwise be discovered in the raw data. However, analyzing these large volumes of raw data is not cost-effective and, alone, does not provide new information. A clear understanding of the plant can emerge only by focusing on the most relevant data and understanding plant processes. This can be achieved by:

• Understanding the principles of physics and the AI algorithm to interpret the data and reveal the plant’s problems.
• Synaptically synthesizing diverse elements such as people, systems, data, services and supply chains.
• Nurturing a relationship between OT, IT, business, and domain knowledge to achieve true digital transformation.

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