The adoption of digital business trends has brought Industries to the doorstep of radical change, popularly called Industry 4.0. Process plants and manufacturing sites are now closely coupled to consumer demands and market dynamics. Every part of business is informed by the consumer e.g. unlimited choices in the paints industry, customizable options for automobiles even on entry level vehicles, commodity markets driving energy production, solarification of households and electrification of vehicles affecting carbon driven energy production. In this fast moving ecosystem, process plants seek ways to quickly reduce costs, optimize design and production process, improve operations, and avoid critical and costly downtime.
Operational Technologies and the Untapped Data potential
Traditionally, in the Process Industries (Continuous and Batch), Process Automation and Optimization has largely been the realm of Distributed Control Systems and Programmable Logic Controllers. These applications focus on Operations Process Control and range from batch software to planning and scheduling, simulation, optimization, plant asset management, and more. This operational Intelligence layer dominated by proprietary hardware and software stacks are more focussed on reliability, accuracy, and safety as they handle critical equipment which have financial and human costs.
There is a vast reserve of untapped data generated by process plants which hitherto was trapped in operational technology silos. Be it continuous or batch process industries, the process plants typically consist of complex equipment. For example, for a petroleum plant there are many reactors, pumps—these are monitored by instrumentation which track process variables (pressure, temperature, flow, concentration) in real-time and the entire process is controlled by actuators. In some of the plants the scale involved is large— say a refinery, which consists of several thousand instruments and actuators with process variables for some critical loops monitored as frequently as 20 times a second. The amount of data processed by these automated systems in process plants can be huge but is used primarily to achieve production, ensure product quality but also to ensure safe operations. With the voluminous amount of data being generated each day, industries are highly challenged on how to utilize the generated data beyond these traditional use cases of process automation, reliability, and safety.
Internet of Things (IOT) for Operational Technology and Information Technology Convergence
The connected systems of the Internet era has introduced the need for processing cross-contextual events from remote monitoring, alarm management and predictive maintenance. Also, integrated supply chains demand that operations are managed within a globalized context and not independent sites. The proprietary process control stacks are unable to handle the deluge of data generated by these operational and information technology sources. This is because Operational Technology (OT) systems such as DCS, PLCs, and Scada deal mainly with machinery, plant information, control systems, and are geared more towards safety, availability, integrity and confidentiality. The priorities of Information Technology (IT) systems are basically inverted and geared more towards volume processing. However, advances in networking and computing technologies have blurred the lines between OT and IT. This blurring of lines has emerged as a new breed of systems called Industrial IOT, which based on the adoption of new technologies for the process automation and intercommunication of the production process, are bringing with it the world of Big Data and Analytics to create Smart Factories.
Industrial IOT technologies supported by cloud computing brings the promise of decoupling operational intelligence from the process control applications, to help organizations develop new analytics capabilities, that deliver business objectives of reduced downtime and maximised production operations. IIoT enables connected operations, giving process industries the ability to combine sensor data with external (e.g. weather data) and business systems (asset management). Such visibility allows for real-time process optimization through comparison with other plant sites. Also, plant performance dashboards can be delivered anywhere in the world through web dashboards/mobile apps. Examples of such new capabilities enabled by IIOT are:
Smart Pharma manufacturing: Pharma companies can optimize production plans, batch recipes by bringing together all different types of data from many sources including plant data, analyzers, building management systems, hospital treatment and diagnostic systems and laboratories. IoT could therefore become a catalyst for paperless production enabling moves towards individualized production or diagnostic-focused therapies.
Connected Oil fields: Another example is the oil and gas industry, where most oil wells are measured by barrels per day. IoT is changing that game, since you can pipeline real-time monitoring using wireless networks. These production wells are now able to produce more or turn up or down production depending on the market needs.
In Part 2, I will discuss additional use cases enabled by the IOT and in Part 3 address some of the issues around getting the data out of the process automation silos.