FLUTURA is an Artificial Intelligence solutions company, started with a vision to transform operational outcomes by monetizing machine data. It does so by leveraging Cerebra, its proprietary and award winning AI Platform for IIOT (Industrial Internet of Things), impacting business outcomes in the Energy and Engineering industries.

Flutura’ s Cerebra SignalStudio™ is an AI platform for IIoT, tuned to integrate and analyze machine data in a manner to drive business outcomes through pre-built verticalized apps. Cerebra’s ability to rapidly create analytical asset and process twins helps rapidly integrate machine data and to provide advanced diagnostics and prognostics solutions. It does so by seamlessly integrating physics based models with advanced machine learning capabilities. Cerebra and Flutura’ s extensive accumulated expertise in modeling, enable it to build applications in less than 90 days, what otherwise would have taken over a year to build.

The company (based in Bangalore & Silicon Valley)  is rapidly emerging as a leader in the Industrial IOT Intelligence space powering new business models in engineering and energy industries, with a focus on guaranteeing measurable impact to business outcomes with its patent pending machine learning algorithms tuned for Industrial assets and processes. This coupled with advancement in low-cost sensing capabilities and ubiquitous Internet connectivity is set to usher in a business revolution within the industry.

Flutura’s team of domain-centric data science experts, and their deep knowledge of specific industries such as Upstream Oil & Gas and Chemical process Industries makes this company the best positioned to build effective IIoT predictive solutions for clients in this specialized niche.

As we have written before, the real significance of industrial-IoT lies neither in sensor-data aggregation in cloud nor the analytics it generates. Industrial-IoT’s real monetizable value lies in enabling new fact-based business decisions which weren’t possible earlier, or were too dependent on gut-feel or random “tribal knowledge” among operations engineers. This is precisely where Flutura engineers and data scientists focus their solution building prowess, and excel in solving real world process issues, a very valuable outcome.

 

HITACHI’S VOTE OF CONFIDENCE

Hitachi High-Technologies Corporation Japan recently announced an equity investment in Flutura Business Solutions, and concluded a strategic partnership agreement. Hitachi’s  vote of confidence in Flutura follows its earlier agreement for commercial and technical cooperation includes sales and distribution rights for Flutura’s revolutionary IOT solutions Cerebra NanoApps™ and Cerebra SignalStudio™ (Cerebra) in the Japanese market as well as other geographic markets.

With their leading IT Solutions (IT), Operational Technologies (OT) and manufacturing machine and devices (Products), Hitachi High-Tech Solutions have a strong presence and a deep understanding in the industrial space, making them an ideal partner for Flutura.”  Hitachi’s equity participation in Flutura and conclusion of the global strategic partnership agreement will build an even stronger relationship between the two companies through strong business and technology collaboration. The synergy between these leading companies will power solutions in the rapidly expanding IIoT market, with an aiming to expand business globally.

Hitachi’s equity participation in Flutura and conclusion of the global strategic partnership agreement will build an even stronger relationship between the two companies through strong business and technology collaboration. Flutura already enjoys a deep operating experience in the Japanese industrial markets. Together, the companies will provide solutions in the rapidly expanding IIoT market, with an aiming to expand business in global markets.

 

TOWARDS REAL INDUSTRIAL VALUE DELIVERY

Here are some areas of industrial value that Cerebra’s platform enables for Industrial-IoT clients.

Product Quality Benchmarking
Before Cerebra, every product manufactured had its own quality measurements and was difficult to assess, benchmark and compare the quality across manufacturing batches, across production lines, and across factories to take corrective actions. Cerebra introduced a scientific way to measure product quality in a homogenous manner enabling measurement of performance at all levels.

Learning The Complex Interplay Of Process Variables In A Continuous/Batch Manufacturing Operation
Before Cerebra it was impossible to attribute causal factors for suboptimal batches due to the multitude and complex nature of data points available. Cerebra is now constantly learning the ever-changing complex interactions and inter-relationships between human, machine, environment, processes, and outcomes throughout the manufacturing process and helping operations and quality teams to intervene at the right time.

Root-Cause Analysis
Before Cerebra, root cause analysis was manual, highly time-consuming and many a time impossible to conduct due to the sheer complexity of the process. Cerebra is now able to isolate the needle in the haystack with ease; one of the manufacturing plants was able to isolate an issue related to the design of the blades used in the industrial mixer to be the cause for variance in viscosity of the manufactured product.

Knowledge-Capture From Real Process (Not “As-Designed”) To Reframe Standard Operating Procedures
Before Cerebra, process effectiveness and continuous improvement to the standard operating procedure were subjective and reactive. Cerebra is now helping monitor compliance to standard operating procedures, the effectiveness of standard operating procedures and helping question status quo; Cerebra helped narrow down more-than-a-decade-old quality threshold established for a specific product’s BOM and in turn, helped change the product development formulation.
Cerebra IIoT intelligence platform was initially deployed to gain basic visibility into product quality deviations on the manufacturing line; has now
1. Transformed Production Planning
2. Transformed Machine Resource Planning
3. Transformed Supplier Performance Assessment
4. Transformed Product Development
5. Transformed Manufacturing Process Optimization, and
6. Transformed Operator Training.
Many plans and blueprinting are underway to leverage Cerebra in multiple areas; next being Supply Chain Optimization.
Cerebra is serving as THE operating system on which Man-Machine interactions are being orchestrated. It has become the Central Nervous System for plant operations.

Enable Detection Of “Unknown-Unknown” Environmental Variables
Cerebra Pre-Diagnostics, which enabled operational process changes and modifications to their industrial equipment.
A leading industrial glove manufacturer discovered unusual changes to sensor behavior affecting product quality with Cerebra’s Swarm Algorithm. Pollen pollution in the shop floor was ascertained as the root cause for this issue and extensive changes were done to set right the ambient operating conditions for the plant. Continuous monitoring of ambient conditions has now been institutionalized
A process chemicals manufacturer discovered deviations to the composition of the end product while it was manufactured with a particular industrial mixer. This was a decade old problem which had gone unnoticed. On further investigation it was ascertained that the type of blade used in the industrial mixer was leading to deviations in viscosity of the product. The machine resource allocation process has now been changed to add constraints related to product – machine mix
A gas processing plant had frequent failures on its valves resulting in periodic unplanned downtimes. The discovery process lead to surfacing insights related to non synchronized feedback loop from the control systems to the valves leading to friction. The plant is replacing its control systems architecture to prevent issues
A leading mining company discovered failure patterns on their milling machines when certain load thresholds were breached consistently over a period of time. New alarms were designed and put in place to detect progressive failure paths

Detecting Critical Subliminal Step-Changes In Manufacturing Processes
Before Cerebra, macro deviations or step change in operations were difficult to detect. Cerebra is now helping detect macro shifts in processes; a manufacturing plant was able to detect a change in product quality due to a change they made to a supplier of a critical raw material several months before.

Before Cerebra, repetitive & seasonal patterns were difficult to detect. Cerebra is now helping unearth unforeseen changes to environment leading to undesirable impact; Cerebra detected a peculiar pattern related to variance in quality from a particular shift, on the investigation, the training process was relooked into and operators are now being trained on the new process.

NEW MONETIZABLE VALUE CREATION

Cerebra’s rapid implementation approach, alignment to the engineer’s thinking process and focus on business value makes it truly unique among industrial-IoT analytics players, which remain obsessed with putting out generic solutions without any serious domain expertise built into them. Additionally Flutura’s  ‘scale-as-you-go’ pricing model allows its customers to start small with initial pilots before scaling the solution.

In its initial days, Flutura faced several value delivery challenges.
1. Access: Access to business users/Operational heads who would benefit from Applied AI instead of meeting IT teams
2. Tangibility: The industrial world is used to tangibility; Digital AI solutions are typically very intangible in the electromechanical world
3. Dollar-Impact: Creating value calculators which linked AI outputs to operational outcomes and resulting dollar  value.

Its response was to adapt the Cerebra platform, the foundational bedrock for creation of new digital business models, to support a variety of business model configurations as outlined below

• Task-based pricing model – Diagnostic tasks, Prognostic tasks, Advanced state assessmen
• Asset complexity – Nodal vs “Non-Nodal” asset
• Breadth & depth of electro-mechanical & hydraulic signals in scope
• No of subsystems

The final outcome was the Unit pricing model – Per asset per year, Per asset per app, Per asset per month, Per asset per app per month.

One such business model is the pay-according-to-use model, where customers won’t need to pay to keep a physical item, but rather can pay for the time they use a product, like renting a library book. It will unlock whole new types of rental systems.