Dr. Pratap Nair, President & CEO, Ingenero Technologies (India) Limited
Dr. Pratap Nair, President & CEO, Ingenero Technologies (India) Limited spoke exclusively to Rahul Koul, Associate Editor, Indian Chemical News on data analytics market trends and related solutions from the company besides wide range of products offerings for decision engineering, steam management, heat integration, digital twins, anomaly detection and improvement. Excerpts of the interview:
How big is the data analytics market in India and globally, especially in the context of the chemical sector?
India is currently among the top four big data analytics markets in the world and NASSCOM has set a target of making the country one among the top three markets in the next three years. The data analytics market in India is currently valued at US $2 billion and is expected to grow at a CAGR (compounded annual growth rate) of 26 percent, reaching approximately US $16 billion by 2025, making India’s share approximately 32 percent in the overall global market, including exports.
While India’s analytics market though majorly dominated by BFSI, marketing and e-commerce sector, the chemical industry is not far behind with cumulative contribution from pharma, FMCG and energy of 22% of the total revenue generated. Globally, the data analytics market is about US $20 billion and estimated to grow to US $68 billion by 2025, up at a CAGR of 28.9%.
Role of Ingenero Technologies in providing data analytics solutions to the chemical industry?
Ingenero has been providing Advanced Analytics as a service to chemical industry manufacturers globally, since 2001, through Ingenero’s Intelligent Process Operations Guidance (IPOG). Advanced Analytics based on applying first principles fundamental analytics combined with statistical techniques like AI/ML (artificial intelligence and machine learning) to live and historical data from the manufacturing facility, is regularly used by Ingenero to provide continuous support to chemical manufacturers in the USA, Middle East, Europe and Asia Pacific, with the help of a remote team, from the technology center in Mumbai. The objective is to help improve production, efficiencies and safety while better adhering to regulatory compliances.
Automated analytics solutions that were developed over time, to execute IPOG projects, gave Ingenero a jump start to being able to successfully deploy software solutions, as part of the digitalization initiatives over the past six years. Ingenero typically deploys data Analytics solutions on a Build-Operate-Transfer model and implements both on-premise and cloud deployment versions, based upon client requirements.
Clients that are availing your data analytics solutions globally and how are they benefiting from the solutions?
Ingenero is currently in discussions with clients in India on deploying Advanced Analytics solutions as part of digitalization initiatives, most of the continuous applications have been global with companies like Chevron Phillips, SABIC, Sasol, Total, DCP, to name a few.
A facility for Long-Chain Alcohols production in Louisiana, USA was able to enhance capacity by 30% without CAPEX, improve first-pass quality by 11% and stop external tolling, through the continuous use of Ingenero’s advanced analytics on their operations data.
An Integrated chemicals company in Belgium was able to develop a strategy and execute it, using Ingenero’s corporate decision support digital twin model covering all of their facilities, thereby hiving certain businesses at Euro 110 million and growing to Euro 400 million quickly after turning profitable.
Two Ethylene facilities in the Middle East of a major US Petrochemical major were able to improve yield, plant availability, throughput and efficiency, saving US $250 mn over a five-year period, through the utilization of Ingenero’s Hybrid Digital Twin using fundamental models and Machine Learning along with remote tracking.
A midstream company in the USA, operating the largest NGL pipeline network in the USA, was able to increase profitability by 22%, using Ingenero’s Digital Twin deployed over 40 facilities, providing centralized asset visibility, allowing a systematized identification and prioritization of process requirements and optimization capabilities.
In the Indian context, who are the clients that have availed your data analytics solutions and how have they benefited?
In the Indian market, other than Cairn India, Ingenero has mainly worked on snapshot static engineering design analysis, performance improvement consulting, and troubleshooting analysis with companies like BPCL, HPCL, MRPL, Nayara, RIL, Sun Pharma, Pidilite, Vinati Organics, Jubilant Life Sciences, Aarti Chemical, Mangalam Organics, Deepak Fertilizers, etc.
Ingenero has helped minimize Ethylene losses in a process at a Petrochemical facility in India, addressing cyclic Ethylene use and batch process challenges that the manufacturer was facing through concept development and follow through cost-effective engineering and implementation, providing an annual savings of US$ 650,000. 1.5 tons per day of Ethylene loss was reduced to 100 kgs/day. A pacesetter audit for optimization of crude, overall operational philosophy, power plant operations analysis, shutdown analysis helped a 15 MMTPA Refinery in India identify 2.3 US$/bbl of potential GRM improvement.
Analysis of past operations data, F&L reports and SOPs for a 7.5 MMTPA refinery in Mumbai, helped identify 0.6% un-identified losses.
Continuous proactive operations data analysis and decision support for an Oil & Gas producer in India (150,000 BOPD oil production facility asset sites), helped enhance asset availability and achieve US$ 6.5 million savings through the determination of root causes and suggested remedies for off-spec production that were leading to quality issues and lost profit. Pinch analysis of the Phenol, Cumene and OSBL units of a Petrochemical facility in Mumbai, helped optimize utility consumption, lowering steam consumption and realizing 14 MW energy savings.
How is your key product, Intelligent Software Solution for Process Decision Excellence (I-SSPDE) helping in digital transformation?
Having worked with a few of the early adopters of the digital transformation initiative and also have seen mixed results from other initiatives in the market around us, we have learned along with our clients in the chemical process industry, that the key to success and extract benefits from digitalization initiatives is to clearly understand the business applications or use cases upfront for the Industry 4.0 implementations.
The business applications to focus on, the relevant IIoT data necessary, whom to connect with what, who all collaborate, the dashboards, the type of information and how it is processed and analyzed, where streaming data is required and where batch data is better, cloud computing vs on-premise vs hybrid, etc. are important aspects that are handled by the “Decision Engineering” process. Decision Engineering requires a coherent team with domain experts in chemical process manufacturing, first principles modelers, data science specialists and software engineers. It helps convert technology tools to solutions that directly address use cases for manufacturers, providing them with Augmented Intelligence and insights, to be able to make faster, more timely and quality decisions (whether operations, planning or scheduling) based on data rather than intuition alone.
I-SSPDE is a package of solutions for chemical process manufacturing that has Advanced Analytics algorithms at its core, carefully tailor made, with in-built intelligence, for the chemical process industry, connected to IIoT sensors, historians, databases and providing intuitive visualization of the predictions and prescriptions. It is typically deployed on a Build, Operate and Transfer mode. It is utilized to improve asset reliability, optimize operations and planning and better comply with safety, environment and sustainability parameters.
Info on Ingenero’s solution with respect to heat integration? Clients who are availing this facility?
The heat integration solution is a combination of a Digital Twin model based on first principles tuned to existing plant data, to mirror the plant behavior. This is then utilized to analyze using Pinch and other engineering analysis to see whether there are possibilities for better integration between the process and utility with respect to matching heat generation and heat consumption, to save energy usage. The analysis also includes a review of what it will cost to do the heat integration versus the savings.
Some of the clients who have availed this from Ingenero in the recent past: HPCL, Mumbai Refinery; BP Petrochemical facility in Alabama, USA; LAB facility and utility networks at Farabi Petrochemicals, Jubail, KSA; Saudi Chevron, Jubail, KSA; Deepak Phenolics, Mumbai.
How is Ingenero helping companies in steam management and clients who are availing this facility?
Steam management is a direct application and use of the Digital Twin models that optimize steam usage when viewed in conjunction with the main process performance. This has been an application utilized in most of the sites where Ingenero has provided Advanced analytics as a service or a software solution. Westlake, Lake Charles, USA; RLOC, Qatar; SABIC, KSA are cases in point.
Solutions offered by the company with respect to digital twins and clients who are availing this facility?
A Digital Twin is a digital replica of the physical manufacturing facility or the performance characteristics of the facility, whereby the behaviour of the facility or the physical facility itself can be mimicked by the computer program or visualized on the computer. The Digital twin mirrors the operation and what-if scenarios can be run offline, predicting the impact of a change, without disturbing the operation, before implementing a change in the operation. The type of Digital twin model depends on the application for which it will be used.
Ingenero specializes in Digital twin models that mimic the performance of the manufacturing facility and is able to track, predict, and prescribe, for improved Asset and equipment Reliability, Production, efficiency. These models are based on a combination of first-principles models and AI/ML models, with data from the manufacturing operations being the key input.
This has been availed by several of our clients in the USA and the Middle East, as mentioned in an earlier answer, for continuous advanced analytics applications. Cairn India uses it for continuous application and such types of models have also been used offline by Ingenero to provide engineering analysis services indicated in earlier answers, to refiners and chemical plants in India.
Ingenero’s solutions with respect to anomaly detection and improvement and clients which are availing this facility?
Automatic anomaly detection is a solution that utilizes Machine Learning models that have been trained on relevant data from the history of the equipment or sections of the manufacturing process and then used to predict the process or equipment behavior, to detect anomalous operation early. The early warning helps find and fix a problem before the problem finds you. To minimize false positives, the model has to be instilled with intelligence from fundamental models, instead of just the data.
These models are self-learning and adaptive in nature. This is a solution that Ingenero has been using internally to provide the IPOG service to several customers in the USA and the Middle East and has now deployed it as an automated solution for Chevron Phillips, Phillips 66, Westlake, to name a few.
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