Bosch Digital Twin - IAPM

Digital Twin IAPM - Creating a Unified Digital Enterprise

Inspiration

Technology has touched nearly every aspect of life. The change in technology is people's desire to make their lives better and easier. The world of predictability created by engineers is never the same. It’s changing day by day!

We are witnessing a revolutionary & Remarkable level of innovation.

Finding innovations and technology will always enable big environmental impacts going forward.

It’s very clear that global climate change is one of humanity’s greatest threats in the current scenario.

World today aspires to promote a sustainable development for the areas of Industrial & Energy infrastructure.

The need of the hour is to have resilient & inclusive overall development, harnessing both combinatorial & frugal innovation.

Organizations aspire to have a working model which will help them bring in diversity, cultivate a learning culture, improve efficiency, eliminate stress, and conserve time for innovation. All these elements make it a chain of close loop.

The strength of this entire chain is equal to the strength of the weakest link!

What it does

Can you imagine scenarios where in a Machines call you when they need help.

A Scenario where a machine interacts with you like a human being and comes to your place instead of you going to the machine

A scenario where the machine tells you what can be potential bottle necks and limitations that could hit your business operations and shield your business from unwanted disruptions

Now imagine situations a s below: A chief engineer at a power plant that feeds power to large process industry receiving a priority alert to immediately inspect high furnace exit temperature indicating a possibility of excess heat pickup in the super-heater and pre-heater sections of the power plant boiler.

An OEM of a windmill receiving actual field performance inputs from thousands of machines across a wide geographic area directly connected with their PLM that could guide them to upgrade specific designs for product improvement and provide insights on possible cost-reduction options.

Digital Twin enables you to run your plant operations in optimal cost mode & optimal efficiency mode. With this, manufacturing companies can now simulate and test all aspects of production even before the start of actual production. This enables them to increase the productivity, flexibility, and efficiency of the manufacturing systems.

A Digital Twin brings all the experts together on a collaborative platform, enabling helpful analyses, diagnostics and prognostics. This facilitates a seamless interconnect of everything and everyone by onboarding them on a comprehensive communication network called the Digital Highway.

And many more…

How we built it

A Digital Twin is a dynamic software model of a physical asset or process that relies on sensor and instrumentation data to understand its state, respond to changes, predict outcomes, improve operations, and aid judgments for business decisions.

Has four layers: Connect - Collect - Consume - Cognitive AI-powered IAPM that relies on natural intelligence and first principles

The solution simplifies complex automation for customers by harvesting machine generated data, helping customers to run their production environment in optimal cost mode or optimal efficiency mode.

The solution also creates a Digital Highway, where, personalized insights are made available to the right person, at the right time, at the right instance to drive the business outcome. This creates an ecosystem where every individual in the organization is enabled for data driven business decisions.

The solution also features a multi-algorithm analytics engine with AI and physics modeling to detect issues, validate them, and suggest possible causes & effects based on symptoms.

Azure IoT components, such as Azure IoT Hub, allows you to build highly scalable and reliable solutions to modernize your industrial operations to a smart factory. Azure IoT Edge on a VM or server collects data from sensors and systems, tags it, and filters it for the important pieces. Data is uploaded to Azure IoT Hub and stored in a Data Lake with Data Explorer and in a Cosmos DB. Data Lake drives Azure ML for inferences while Azure Kubernetes manages micro-service containers that perform deeper data analysis and integrate with Dynamics 365 for systems management. Azure App Services powers the web-based management experience with optional Power BI visualizations, and HoloLens 2 AR support.

With the introduction of Azure ARC, the solution has the potential of massive scalability that allows you to build applications and services that could operate across data centers, at the edge, and in multi-cloud scenarios.

Digital Twin IAPM has the Microsoft Sustainability Manager Framework which takes care of data ingestion, analysis, reporting and sharing the insights using the tools – PowerBI, PowerApps, Dynamics 365 Field Service and Power Automate – creating a sustainable value chains.

The learning's from below sources are being incorporated: Microsoft Cloud for Sustainability: Get started with Microsoft Cloud for Sustainability - Training | Microsoft Learn

Challenges we ran into

1st, Field Data Sanctity: This practically decides the degree of success of a Digital Twin. You need to be very clear, which sensing mechanisms are relevant, its sampling frequency, quality of data, comprehensiveness of telemetry etc. This is one of the greatest challenges that we face when we start building a Digital Twin, and any gaps in this, needs to be addressed at the very initial stages itself.

2nd, Clear Business problem narrative: This is a major bottle neck, where majority of our customers struggle. Before you plan for Digital Twin, it is mandatory for you, to have a clear vision of the expected business outcome. If this aspect is missing, we end up building solutions that don't fit the actual need.

3rd Missing or invisible data narrating an incomplete picture: The success and the life- cycle of a Digital Twin will entirely depend on the quality of the available & usable data at your end. Point to be noted here is success of these systems, entirely depends on how comprehensive your data bank is, as simple as that.

4th Rare Class Faults: The funny part here is, even though the name says, “rare class fault”, this scenario is very common. These faults cannot be modeled in the Twin right at the initial stages. These are called black swan events which needs us to train the twin manually.

5th The Human Factor: One of the most important part of this solution is, the mindset of the people who use this Digital Twin solution. So, to make this long story short, we need to have a holistic mindset when we are working with such solutions & not reductionist mindset. Now, why I am bringing up this point here is, there are lot of apprehensions around digital transformation solutions. Many a times, people are of the opinion, that, these digital solutions will result in cutting down the jobs. No. This is not true in case of a Digital Twin. All a Digital Twin will do is to work along with you, like your Digital Assistant, helping you to complete your work efficiently, this fact needs to be imbibed by the people.

Accomplishments that we're proud of

Removal of Cloud skepticism – Myth and belief of having large & complex machines can’t be cloudified. Now with digital twin this is easily doable.

Gender equality: Both men & women could now safely & collaboratively work equally when dealing with maintenance of complex assets operating in hazardous operating conditions, which once were exclusively handled by men.

Sustainability: Today, you can comprehend the efficiency levels of assets in various forms to comprehensively understand their impact on the energy ecosystem, operate them in optimal cost mode & optimal efficiency mode which enable them to run their plant operations sustainably.

Enabling differently abled: Retired industry veterans, domain experts who had been the victim of events which imposed accessibility & mobility challenges on them will now be able to ingest their knowledge into the plant operations, R&D, employee training etc. via Azure and earn for the data exchanged & knowledge imparted.

Strengthening educational institutions: educational organizations can now harvest the same & train their students for real life industrial scenarios by utilizing Hololens2 & make them more practical by offering exposure to the actual field challenges. We empower the students to question knowledge & this transforms them to be competent, industry relevant & desirable by the potential employers.

Improving quality of life: Organizations can now eliminate stress from their employees to the best possible extent by creating a collaboration between humans & machines. With stressful maintenance tasks now getting automated, machines can now create tickets for themselves on Dynamics 365, provide situational awareness to their care takers on Microsoft teams & can go to their care takers virtually through the immersive visualization enabled by Hololens2.

Work life Balance: With this digital effectiveness kicking in, people spend less time with the machines performing mundane tasks & spend qualitative time with their families. This positively impacts the health of the people & creates collectively resilient communities.

What we learned

Now when we build this solution for the 1st time & deploy it, it is as good as a newborn child, as the child grows up & evolves into an adult, the Digital Twin also matures over time. Like how our parents brought us up with all the good values & helped us in becoming street-smart, this Digital Twin solution also needs hand-holding from the users when it is evolving.

This reflection can be seen on those operating parameters & we could collaboratively decide the most appropriate operating conditions for our assets that helps the customer to best optimize the manufacturing processes or power generation systems or sustainable transportation for a given load cycle.

The learning's from below sources are being incorporated: The Principles of Sustainable Software Engineering - Training | Microsoft Learn https://learn.microsoft.com/en-us/azure/architecture/framework/sustainability/

What's next for Bosch Digital Twin – IAPM

What will customers want in the future?

They will demand a wider range of variants and more personalized products. Thus, future production must be able to adapt quickly to changing market requirements.

Industry 4.0 (I4.0) is the answer to this challenge. Digital Twin is being deliberated as a significant enabler for I4.0 initiatives. While Digital Twin has made visible inroads into the industry as a standalone solution, the concept of it being pivoted as a critical element of I4.0 is sprouting and yet to reach its pinnacle.

As we speak, it is already making its impact felt across diverse businesses worldwide. Forward-thinking companies representing automobile, healthcare, process industries like oil and gas, and other large industries have already started harvesting the economic value of Digital Twin.

Today, Digital Twins are built mainly for intra-organizational consumption, however, in the future, Digital Twins would be built for inter-organizational consumption as well.

It can drive companies, industries, and societies, to become safer, smarter, and greener.

It can transform organizations into a digital enterprise that assures a smart future, eventually improving the business results.

We strongly believe that building a comprehensive solution is one side of the coin; a collaborative mindset of people who use this as a medium to solve a business problem is what completes the other side of it.