Digitalisation Streamlining the Process Industry Operations
Published on : Wednesday 01-12-2021
Modern process manufacturing units are increasingly becoming capable of converting the existing challenges into opportunities with the help of digital technologies.
Process manufacturers face a stiff competition to boost production and efficiency using innovative technologies and competitive strategies. Over the last couple of years, digitalisation has made its way through most of the process operations. Digitalisation has transformed from a mere buzzword to actual practices paving ways for better process innovation.
Nuances of process industries
The use of big data analytics, Internet of Things (IoT), Artificial Intelligence (AI) and machine learning is propelling a new wave of opportunities to remain competitive in the process manufacturing segment. Ranging from autonomous industrial vehicles such as drills or loaders, digital fleet, and site optimisation solutions, or real-time production diagnostics, a wide avenue of technologies and solutions are being proliferated in process plants.
Some of the core processes that characterise the current state of process industries and also represent the prevailing challenges are:
a. Complex Supply Chains: Long supply chain causing communication bottlenecks, reduced visibility into processes and therefore increased complexities.
b. Ineffective Data Strategies: Ineffective data strategy causes a lack of information available on all the levels of the plant architecture. This creates roadblocks in streamlining the operations and hence it is difficult to introduce process innovation.
c. Lack of Standardised Practices: No standardised practice in place for change management. Implementing new processes does not comply with the latest best practices.
With prevailing challenges, process industries are lagging behind to become Industry 4.0-ready. In order to keep pace with the changing face of industrial processes, process manufacturers are swiftly getting acquainted with modern-age technologies.
How are Process Industries using Digitalisation?
Process industries are usually called laggards in terms of their IT affinity. However, a sweeping wave of changes has been witnessed since the rise the digital technologies. The digital-maturity of process industries decides their preparedness to adopt digital transformation.
Nevertheless, there is a growing inclination towards modern-age technologies. Some underlying digital technologies proliferating in process industries are:
1. Automation: The existence of the 4th industrial revolution has allowed technologies to go beyond the conventional definition of automation. The face of process industries is gradually transforming with the advent of Cyber Physical Systems (CPS). Intelligent networking coupled with smart machines and cloud storage makes the process production facilities more cohesive and capable of autonomously exchanging real-time data independently. Such as a pump or a compressor can have a sensor embedded into it and connectivity modules can be self-regulating and enable autonomous operations.
2. Internet of Things (IoT): Process industries, similar to discrete industries, deal with greater inflexibility. “How to use the industrial assets effectively to cut down the operational cost and increase productivity?” is still an unanswered question. This is even more challenging with yesteryear technologies in the plants. Imagine, the installation of wireless sensors on pumps that are connected with intranets and then with high-speed public networks to form a complete architecture. The sensors would tell the operators when a pump needs service. Monitoring hundreds of pumps digitally can be easier and less expensive than manually checking every pump.
3. Cloud Computing: The use of cloud computing is inevitable in every facet of an enterprise. Connecting a plant floor to the IT layers of the hierarchy requires storing, processing, and analysing a lot of northbound data originating from the field devices. With intelligent IIoT devices becoming popular, cloud platforms are used for deploying and running the machine learning models on them to enable real-time decision-making capability. Cloud platforms are also used in process plants for developing customised industrial applications on a range of smart devices.
4. Simulation: Some processes like mixing, granulation, etc., are quite critical in the process manufacturing operations. In order to improve these critical processes inside the equipment like reactors, mixers, granulators, etc., the engineers require clear visibility into the ways to execute the processes differently. By using simulations, engineers can clearly understand and analyse the other possible scenarios and opportunities to introduce new processes. Simulations are considered to be especially important for process industries than the discrete industries as process flows are connected in one stream and even a minute failure/error may cause severe damage to the entire operation.
5. Big Data: Process manufacturing operations are subject to inconsistencies even after applying lean techniques. Given the sheer number of complex operations on the plant floor, manufacturers require a granular approach to diagnose and eliminate the flaws in the processes. This is possible by big data analytics. Using streams of previously isolated shop floor data, the operations managers can use statistical assessments to identify patterns. This data can provide smart insights to improve operational efficiency.
6. Artificial Intelligence (AI): Modern process manufacturers are paying attention to introducing the latest technologies to improve the production processes. Using AI techniques in process modelling, optimisation, debottlenecking, troubleshooting, etc., has become quite common nowadays. For instance, plant owners can use AI models to learn the normal behaviour of the plant using historical data and detect the anomalies during operation. A root-cause analysis can be carried-out to draw inferences that can be used to implement in actions.
7. Augmented Reality (AR): Augmented Reality is comparatively a newer technology and industries are not yet prepared to adopt this rising trend. However, AR has a vast range of applications that can prove to be beneficial for the process industries. Whether it is managing their warehouse for object recognition or to check the system failures. Imagine, diagnosing a boiler with the help of AR glasses. This can be really helpful in minimising the time consumed in inspecting the machines and equipment.
8. Advanced Robotics: Introduction of robots into conventional labour is gradually transforming the process industries. Many of the manual processes are executed with the help of robots. This not only improves operational efficiency but also reduces time consumed in the process. For instance, a pharmacy manufacturing industry can use robots to produce customised medicines. Robotics and automation can help reduce complexities in analysing the gene sequences. Robots are also effectively being used to address material shortages.
9. Blockchain: Blockchain is still a new technology concept for most of the industries. While blockchain is usually considered the technology behind cryptocurrency, there is more to it. Discrete and process industries are using blockchain technology to streamline operations, gain better visibility into the supply chain, and track the assets with unprecedented precision.
With the growing importance of digitalisation, process industries are capable of cutting down the operational cost and improving the production efficiency.
Positives due to process innovation
Some of the benefits that are driven by digitalisation of process industries are:
i. Real-Time Capabilities: Digitalising the plants enables the process manufacturers to extract a vast amount of operational data straight from the process sensors. This allows them to improve on-site efficiency and monitor the health status of the machinery.
ii. Intelligence: Modern-age technologies like IIoT allow gathering intelligence that allows solving complex issues, improving process understanding, offering alternatives to proactively improve the process design, and enabling better predictions by analysing the extensive historical datasets.
iii. Interoperability: A gradual migration from legacy systems to modern-age technologies enables smooth data transmission between heterogeneous devices. This improved interoperability facilitates sharing data in real-time and also integrates the process field devices with the IT layers.
iv. Virtualisation: Process engineers frequently face the challenges associated with obsolete plant architecture. Plant operators do not want to be tied to one hardware type for long due to challenges with software incompatibility, security threats, etc. These changing demands can be met using virtualisation of assets. Virtualisation allows the process applications to be hardware-independent by decoupling the hardware from its OS and software applications. This in turn allows the virtual machine to extend the software lifecycle by more than 10 years.
v. Connectivity: Industry 4.0 technologies like edge computing, cloud computing, and 5G enable smooth integration of process plant layers. It also facilitates the plant operators to realise improved connectivity and in turn enhanced productivity.
With an ever-increasing digital footprint, process industries are increasingly becoming technology adopters creating an avenue of opportunities to bridge the prevailing gaps.
Emerging trends in process industries
Some of the emerging technologies that are increasingly being used in process industries are given below:
Speech, Image, and Video Recognition
With the increased use of smart sensors, it has become easier for process engineers to keep track of the production processes. Keeping a close eye on the process assembly lines, quality of the production, possible intrinsic safety threats, and maintenance of machines is going to become more convenient.
Natural Language Processing
Process industries are prone to have sensitive areas that are threatening to human lives and organisational infrastructure. Conventionally, process plants are observed and maintained manually with process operators deriving the critical machine insights. However, there can be loopholes that cannot be observed with human eyes.
An IIoT-enabled sensor or camera can be coupled with Natural Language Processing capabilities to send voice or text alerts to the operator when the chemical in the boiler falls or exceeds a threshold. This will not only reduce dependency on manual inspections, but will also bring more precision and reliability into the process.
Autonomous Objects
To deal with the inflexibilities in the process plant floor, the deployment of flexible autonomous systems is required. It reduces physical structure complexities and streamlines the information system. Examples like Radio Frequency Identification (RFID), sensor technologies, wireless communication networks, robots etc., enable high flexibility and manage the rising production demands.
It is difficult to understand the context of technology trends without looking at real-world use cases. Let’s take a look at the use cases.
Use cases of digital technologies in process industry operations
Two of the prominent use cases of digital technologies in the process industries are discussed below!
1. Transformation of Energy Value Chain
With the explosion of latest technologies, the process plant floor data does not necessarily originate by conventional means. These data originate with the help of blockchain, IIoT devices, drones, and Cyber Physical Systems.
Digital transformation is aiding the energy industries by introducing smart technologies like sensors. Intelligent sensors can be embedded into turbines, dams, or pipes to collect real-time data which can then be transferred to a centralised control room. This data can then be used to detect anomalies and identify potential risks. This can be beneficial for predictive maintenance and repairs.
Unlike conventional flow of energy from the producer to consumer, modern consumers and producers can be geographically distributed which can be managed through smart metering systems that can be deployed on smart grids to generate automated bills and regulate consumer billing cycles.
2. Oil and Gas
The world is going through immense technological advancement, and Oil & Gas industry is no exception. Digitalisation can bring a huge amount of benefits in day-to-day operations. Big data analytics is being used to improve CO₂ sequestration and carry out data modelling for reservoir management. Similarly, IIoT sensors are used to gather data from oil wells and provide real-time actionable insights.
Not only this, Robots and drones are also used for detecting leakages, environmental monitoring, and inspecting offshore rigs and pipelines.
Endnote
The intrinsic inflexibilities and inefficient processes are a thing of the past. Modern process manufacturing units are increasingly becoming capable of converting the existing challenges into opportunities with the help of digital technologies. Garnering the benefits of operational, maintenance, and informational efficiencies is going to be possible through industry 4.0 technologies. The impact of disrupting innovations is far-reaching and is soon to be realised in every facet of process manufacturing.
Article courtesy: Utthunga
Utthunga, a product engineering and industrial solutions company, engineers industrial-grade digital products and solutions for industrial OEMs, Industries, ISVs, and Service Providers. It provides software development, firmware and hardware development, IIoT applications, IT-OT integration, field device integration, industrial communications, security engineering and testing services to global industrial OEMs and manufacturers.
