The chemical industry is highly diverse. The industry is also highly regulated as it deals with substances that may be hazardous & toxic and production processes that are polluting and susceptible to catastrophic accidents. Additionally, the manufacturing process, which may involve a complex combination of reaction, distillation, extraction and such other operations, needs close monitoring and control, not only to ensure that operations are efficient & productive, but also to address the environment, health & safety concerns, traceability issues and compliance requirements.
Because of the nature of the production operations one encounters in a chemical plant, often it becomes necessary to select the optimal operating conditions so as to reduce waste & energy consumption and maximise profits. Also, it is not uncommon for the quality of the final product to vary from one batch to another. Therefore, a chemical firm inherently is on the lookout to generate additional production & operational data and analyse them to uncover patterns and gain valuable insights, which can then be used to make better & speedier business, production and operational decisions.
It is no wonder therefore, to find companies in the chemical sector seeking ways to transform their business and production processes & operations, so as to increase efficiency & revenues, drive growth, become more profitable and enhance shareholder value & customer satisfaction. At the overarching level, they aim to realise these goals by focusing on improving overall productivity, efficiency and their agility to adapt to the market dynamics & enhance customer experience. At the level, their objectives are to improve plant availability, reduce waste generation & energy consumption and such others. What contributes to the success of the company’s efforts in achieving transformation is its ability to capture information, contextualise, analyse & share the same among stakeholders and use the same in decision-making.
Digital transformation and industrial internet technologies
Digital technologies/industrial internet technologies are excellent tools for data mining and, therefore manufacturing companies deploy them to achieve desired changes. The methodology that involves the use of industrial internet technologies to bring about changes effectively & comprehensively in a company’s business and production processes & operations is digital transformation. Through digital transformation, a company aims at achieving the desired goals.
Industrial internet technologies facilitate data or information to be generated, collected and analysed cost-effectively & efficiently. These technologies also help the sharing of information among different applications, databases, automation systems and enterprise solutions, without having to adhere to the traditional hierarchical architecture for information flow. Manufacturing companies, by using these technologies, can comprehensively marshal and analyse data/information and generate business intelligence & insights. Often, a combination of industrial internet technologies is used in conjunction with traditional industrial automation systems and enterprise solutions, such as the distributed control systems, enterprise solutions planning, etc, for achieving the objectives of transformation. Digital transformation is a prerequisite for a company to make a transition from the third era and become future-ready for the fourth era of industrialisation.
When a physical entity in the value chain is embedded with internet connectivity enabled sensors, it becomes a cyber-physical system or Industrial Internet of Things and gets vested with the ability to generate information & share the same with other cyber-physical systems, including on-premise & cloud computing resources. When embedded with edge computing, the physical entity gets empowered to process data that demands lower latency and faster responses. While the internet empowers communication capability, cloud computing enables more complex tasks associated with the physical entity to be performed. Internet-enabled and networked cyber-physical systems and computers can efficiently & cost-effectively collect, process, analyse, share & store massive amounts of information. Data analytics helps companies examine the real-time or historical set of information to uncover patterns & relationships and thereby, extract valuable insights from them. While descriptive analytics helps study information to describe what is happening, predictive analytics forecasts what will happen under a set of conditions. Artificial Intelligence technology, with its cognitive capabilities, helps predict potential outcomes under a set of plausible conditions; hence, it can be useful for problem-solving and decision-making. Digital twin technology is another powerful tool that can be used to create a digital representation of a physical object, such as a turbine or a boiler; with its help, one can imitate the working of the physical object so as to study & improve its performance. Augmented and Virtual Reality technologies can be of great use in training people and impart industry-specific knowledge in operational procedures and health & safety requirements.
How chemical companies are leveraging industrial internet technologies
Industrial internet technologies offer opportunities for a chemical company to digitally transform many of its production, operational and business processes. While some companies adopt a ‘big bang’ approach while pursuing transformation others take a ‘step-by-step phased’ manner approach with proven applications acting as guideposts.
Many chemical plants still have local panels for ancillary equipment such as compressors & pumping stations, and many valves that are manually operated. With the help of these technologies, some of the manually or locally operated equipment/devices can be cost-effectively connected to the central control room so that they can be monitored, shut down and opened remotely.
Typically, ancillary equipment is periodically inspected and maintained, involving downtime & loss of revenue. Some companies have embedded some of the critical pumps and compressors with internet-enabled sensors, edge computers etc, that sense and process parameters, such as mounting frame vibration, alignment and temperature of a pressure-packing case & bearing and communicate the information to the cloud. Using the analytics software that resides in the cloud, the performance of the equipment such as the pump/compressor is monitored to detect its deterioration and foresee possible failures. Based on the information generated and its analysis, plants decide on whether and when maintenance needs to be scheduled, what kind of work needs to be done on the equipment etc. Through predictive maintenance, companies save time & money and eliminate unnecessary work that results in enhancing the plant’s profitability & performance.
On similar lines, some companies are gathering control valve related data with the help of smart positioners for diagnostic & predictive maintenance purposes and for studying control valve response characteristics. If data from the control valve’s smart positioner are accessed, friction analysis can be done to determine the amount of friction present in the valve assembly that can make the valve more difficult to travel. Air consumption analysis can reveal whether the valve assembly is using an excessive amount of air. Excessive air usage can be caused by wear or damage to the pressure retaining portions of the actuator assembly and/or to the instrument tubing. With wireless vibration or acoustic transmitters embedded at the right locations on a control valve assembly, a centralised monitoring system can gather data and perform trend analysis to assess the possibility of leaks. Such IIoT-enabled applications can result in improving the performance & uptime of control valves and their failure reduction & reliability improvements. Based on the analyses, one can determine proper maintenance scheduling.
Addressing more intricate issues
Some chemical companies have applied industrial internet technologies for solving more intricate issues. According to a McKinsey article, “Using advanced analytics to boost productivity and profitability in chemical manufacturing,” one specialty chemical company was having problems in its furnace in the production line. It undertook an advanced analysis of the data the furnace’s sensors had collected over 615 days of production, comprising 600,000 samples, each with 63 tags. The analysis helped the company identify critical throughput drivers and made it possible to build a model of the production process. The model quantified the interdependence of key variables, where the company had previously only been able to see qualitative correlations, and this provided a more accurate understanding of the process; a test run of the furnace confirmed the model’s findings.
Digital transformation roadmap
Companies operating the chemical sector are leveraging industrial internet technologies and have taken the path of digital transformation to evolve their business and production processes & operations effectively & comprehensively for marketplace success. The company that wants to take the path of digital transformation has to draw up its own roadmap driven by its objectives and priorities. Industrial internet technologies are ready for deployment, especially for applications where the availability criterion of the technologies is not critically important. The way forward for a company is to begin the journey by identifying areas that hold significant payback potential and take the path of digital transformation. It has to set achievable milestones, with each milestone having a specific objective, pursue them, evaluate the achievements, make course corrections as the journey continues, and set new objectives and pursue them.