A decade ago, I was a program manager for Microsoft SharePoint and Office 365. We were looking at the potential to empower more users via mobile + data +cloud, instead of focusing only on information workers Microsoft Office suites were targeting.
One area I looked into was AR glasses for frontline workers - I believe I was the first person to wear an AR Glass every day at the Redmond campus.
I was surprised when something happened to me. The Google Glass project was widely regarded as a failure (remember the glasshole?). The concept of AR + Data Experience gave me a glimpse at the future of digitalization. IT infrastructure will provide foundational support for frontline workers. Operation data will search for people in need, instead of waiting to discover them. This will maximize their ability to get the best results quickly. It will become the new face of production operation support. The platform will allow for the future workplace revolution.
Prior to the cloud transformation, which is now a mandate in the wake of the pandemic, IT was two distinct workloads. IT workloads were about daily IT support, capacity plan, high availability, cybersecurity, and compliance. IT Pros make sure information workers have the right tools and resources to create content. However, most content is not understood by IT Pros - this is the breaking point for IT and OT. Although IT-OT responsibilities are becoming more common for CIOs, it's still difficult to create a data-driven culture within an organization and make it data-driven.
Imagine a situation where maintenance workers need the BIM/IoT sensor data for a specific engine area. How does IT deliver this information immediately? This information is in the professional data silos, which aren't accessible to IT professionals or frontline workers. Although you can create custom solutions with IoT hubs and BIM engines, the maintenance costs of such systems become prohibitive over time. These solutions are more of a snapshot than a living document and don't adapt to your business. To solve this problem, we need a digital twin platform that focuses on dynamic processes.
Although it may not be easy to understand, Enterprise Metaverse is a fancy name. It doesn't really matter what the name is - what matters most is why Enterprise Metaverse or Digital Twin are needed to converge IT/OT.
What are the Motivations for TEMS?
The Motivation Principle. These are the four essential motivators for digital twin-based frontline solutions. They can be summarized as the TEMS Motivations.
Training and guidance: Using the digital twin, 3D instruction of equipment, IoT data, and the environment, it is possible to improve frontline workers' ability to operate, maintain and repair facilities, as well as increase productivity. We have seen a significant reduction in training costs and a 30% increase in productivity for many of our manufacturing customers compared to traditional operational training.
Experience: This new experience allows potential buyers to see the digital twin of equipment and facilities, allowing them to rapidly improve their understanding of unfamiliar environments without having to interfere with production.
Monitor and Control: An interconnected digital twin environment can allow for better operations that are based on real-time information. This includes remote monitoring, inspection, and maintenance. Although the concept of monitor and controller sounds simple, it is actually the most difficult work in the real world. Today's lack of meaningful data collection and control mechanisms makes this difficult.
Simulation: Simulation that uses the digital twin of equipment and facilities. It can be run like SimCity by using a gamified method of building and operating the digital twin environment. This simulation emphasizes the interaction and operation mechanism of equipment. Digital twin objects can be created using AI and behavior trees, so they act as NPCs in video games. This simulation runtime can also be used to inject production data, making it a living environment that allows for large-scale planning and training as well as remote management.
Once we have established the motivation goals, it is time to identify the adoption barriers. When it comes to digital transformation, there are two major barriers: the technology barrier as well as the data governance barrier. The digital twin and the enterprise metaverse are also subject to this same barrier. Is the data available? Is the data accessible only by those who have the appropriate permissions? Is the data type suitable for the purpose? Is the data comprehensible and interconnected? Are we able to understand the nature of our business? What data can we use to solve business problems?
Understanding the Right Enterprise Assets to Converge
To converge IT/OT, CIOs need to not only understand the development environment, ERP, and MES but also think about product and platform standardization. It is easy to get caught in the customization development trap, which can lead to failure after failure. We must use the correct digital twin platform and tools to process enterprise assets. This platform must be capable of providing standard digital transformation capabilities for different enterprise assets.
- Data assets: A well-established digital twin platform must have the ability to make effective use of an organization's data resources. Enterprise data governance is about ensuring that different types of data can be accessed at low costs and that these data are standardized and organized. The metaverse/digital Twin has the theoretical advantage of presenting 3D data in a structured format. This makes it easier to share data assets with non-professionals. Standardizing the transformation of existing 3D data such as CAD/BIM must be a priority. This will allow biz-app developers to have a standard method of accessing 3D assets, and they can concentrate on connecting IoT, businesses, and processes.
- Workflow assets and Process: The enterprise process are always a critical asset to an operation. These processes are the foundation of real business. The traditional enterprise process management focuses on document flow, approval, reimbursement, and document flow. These issues can be easily solved in existing collaboration platforms. In manufacturing, construction, maintenance, and facility operations, the operation process systems can be isolated making it difficult to reuse and describe these processes across different systems. The digital twin platform will allow process assets to be integrated and empower frontline staff by breaking down information silos.
- Collaboration assets: People and organizational relationships are key to quickly leveraging experts' capabilities and resources. These relationships and histories are essential for the digital twin platform. The platform must also be able to access and integrate with enterprise systems such as LDAP or people systems.
- Knowledge assets: The knowledge assets are knowledge that has been accumulated through the collaborative process. These knowledge assets can be found in knowledge management systems and work order systems as well as massive document archives. Future digital twin/enterprise platforms must have natural language processing and automated knowledge mining capabilities to process such data to generate knowledge graphs that can be automatically assisted by frontline staff.
For Enterprise Success, Converge
A "metaverse" that can only be rendered on large screens with high-grade GPUs won't help frontline workers take advantage of digital transformation. The platform must be easy to use in order for organizations to reach IT/OT convergence. It must simplify design processes, reuse digital resources, and offer a robust SDK that requires low or zero code capabilities. It is difficult to teach end users how to use Unreal and Unity3D to design enterprise processes. This blocks mass adoption. Adoption should aim to achieve the democratization of digital twins.