- An overview: Digital twinning definition and its main features
- How to deploy digital twins for warehouse management?
- Benefits of digital twins for Warehouse Management
- Remaining challenges of Digital Twin for Warehouse management
- Why choose GEM as your digital twin partner in Vietnam?
Digital Twin promises several advantages for Warehouse management, but what is this concept? Can it apply to your business?
Digital Twin, a concept that originated in the space industry, is gaining attention due to its vast potential in various sectors, including Logistics. This series of articles will go through Digital Twin’s application in several aspects of Logistics, starting from Digital Twin for Warehouse Management.
An overview: Digital twinning definition and its main features
According to DHL, a digital twin is defined as “A unique, virtual model of a physical thing. It typically connects to the thing, updates itself in response to known changes to the thing’s state, condition or context.”
The origin of the concept dates back to 2002 when Dr. Grieves from the University of Michigan gave a presentation called “Conceptual Ideal for Product Lifecycle Management.”
The concept in this paper contains all the key elements of Digital Twins which are:
- a real entity,
- a virtual entity,
- data flow from the real entity to the virtual entity, and vice versa
- virtual sub-entities.
Afterward, NASA adopted and developed the theory. Using paired simulations, it refined and selected the optimal solutions for the Apollo 13 spacecraft repair in 1970. The technique continued to evolve and became digital twining since the early 2000s but only gain popularity when key supporting technologies reached a certain maturity. Some of those are:
- low-cost data storage and computing power
- fast wired and wireless networks
- affordable and proper sensors
The main goal of a digital twin is to create, build and test equipment in a virtual environment before applying changes to the real entity. In that sense, creating a digital twin not only help cut prototyping or construction cost but also predict failures. Hence, it can reduce both maintenance costs and downtime.
A digital twin comprises of several elements:
- manufaturing simulations
- 3D CAD models
- real-time data from sensors that are incorporated into physical operating environment.
DHL also indicates that digital twinning is much more complex than other pre-existing 3D modeling methods, and there are numerous contributors to this advanced simulation model. However, the majority of experts agree on five key factors below that distinguish digital twining:
How to deploy digital twins for warehouse management?
According to SAP, the implementation of a digital twin depends on the intended business outcome and sophistication of business logic. For most connected products and assets scenarios, there are four scenarios for digital twin implementation as follows:
- Twin-to-device integration: The real entity needs to be securely connected and managed. Streams or batches of live data require protocol conversion, semantic mapping and transformation before ingesting into a big data store infrastructure. This allows to query object state and history information captured as time series.
- Twin-to-twin integration: If the physical object is not managed by the provider of the digital twin, an optional twin managed by a service provider or by a supplier may be needed.
- Twin-to-system-of-record-integration: Integration with business information and engineering systems provides essential context along the lifecycle of the physical object:
- PLM for engineering bill of material, components and spare parts, software versioning (for embedded systems)
- CAD/CAM/CAE for 2D and 3D models, layouts, assembly information
- Manufaturing systems for product tracability, serialization, manufacturing bill of material
- ERP for product variants and financial information, equipment and spare parts inventory
- ERP/CRM and supplier networks for service contracts, bussiness partners and rolls, SLAs
- Twin-to-system-of-intelligence integration: Most digital twins interact with systems of intelligence through evetns and notifications while exposing condition monitoring and historic information; rule handling, data science algorithms and machine learning create insights from streams of live data and provide predictions on future states.
Implementing digital twin will largely be managed from the cloud to facilitate the above network-centric engagement model. However, not all data is relevant to be transmitted. In many cases, only events and change information will be sent into the cloud as a stream while data locally and temporally persisted can be replicated to resolve underlying issues and to evolve algorithms.
Benefits of digital twins for Warehouse Management
According to McKinsey, the global budget spending on warehousing is around $350 billion, and it keeps increasing each year. With digital twin applications, warehouse efficiency is predicted to rise by 20-25%. This improvement is likely to bring about a notable saving on operating and capital expenses.
Digital twinning allows the companies to gain a bigger picture of warehouse operation and make drastic changes, rather than settling for partial enhancements of the current layout and process.
This technology enables better estimation of potential effects of mechanization and automation possibilities, covering all the spectrum of vendors and products available.
Firms can resort to digital twins in VR/AR personal training. For instance, DHL deploys AR/VR picking systems training with wearable equipment gadgets such as Google Glass Enterprise Edition or Microsoft HoloLens to help employees practice vision picking tasks on simulations before actually delivering the job.
The following section discusses the details of the major benefits of building a digital twin.
First of all, warehouses generally operate 24/7, and it is very costly to shut them down for rearrangement and optimization. However, it would be detrimental if companies weren’t to seek renovations. Because the complexity of stock-keeping units (SKUs) classification (due to the rapid expansion of e-commerce) is increasing, and the competition of providing faster delivery is on the rise.
Digital Twinning can generate virtual avatars of every asset of the warehouse and conduct simulations on floor plans, workflows, SKU mix, and shipment profiles, McKinsey indicates. This approach could be more cost-effective than shutting the warehouse to run tests in the long term.
Various factors in the warehouse can impact assets’ conditions
Secondly, various factors in the warehouse can impact assets’ conditions. Given the fact that Digital Twin represents an entity at one specific condition, companies can examine different possibilities of an item in other situations without the risk of damaging it.
Improve Quality control procedures
Thirdly, current quality control procedures require a large amount of manual work. Meanwhile, Digital Twin can update the host object’s status continuously. We can also save more human capital if assets’ conditions are supervised automatically and only need manual checks in specific cases.
Solve difficulties in micro and macro governance
Finally, the nature of warehouse complexity creates difficulties in micro and macro governance. Thus, the ability to simulate different parts and functions of the warehouse both mutually and individually would facilitate experts to see issues both holistically and in detail.
Suppose digital twinning is correctly integrated with other advanced techs such as intelligence (AI), machine learning, and augmented/virtual reality (AR/VR). In that case, managers can gain insights and teach the system to solve similar problems next time they arise.
Remaining challenges of Digital Twin for Warehouse management
Despite such promising advantages, manufacturers still face difficulties developing and integrating digital twins into Warehouse Management’s current operation. DHL analyses seven main obstacles that are worth considering:
- Cost: considerable initial investment in platforms, model development, and maintenance.
- Precise representation: impossible perfect simulation leads to unavoidable assumptions, simplifications in model development, and compromise with the desired outcome.
- Data quality: underlying risks from inconsistencies of data streams
- Interoperability: limited alternatives of technology providers.
- Education: Adoption of new working processes that challenge change management and ability building.
- IP protection: risks of product and customer data exposal that require more restrict data ownership, identity protection, data control, and access governance.
- Cyber Security: possible new points of entry for cybercriminals.
Confronting these obstacles requires lots of effort from the business. However, Mrs. Janina Kugel, board member and Chief HR Officer of Siemens, suggests that the change must be rooted in a leadership approach. Managers and leaders should be more open to learn, guide and empower their employees towards the new technology shift that was merely fictional 20 years ago. Each manager and leader needs to enhance their knowledge and their communication and other soft skills.
In a nutshell, Digital Twinning is a promising technology with multiple applications that could benefit warehouse management. It is predicted to be one of the change-makers in the sectors soon. Thus, it is wise to research and consider appropriate adoptions for your warehouse to keep pace with or even gain a competitive advantage in the Logistics industry.
Why choose GEM as your digital twin partner in Vietnam?
3. We have more than 7 years of experience. Our offices are based in Hanoi, Vietnam, and Tokyo, Japan.
4. We have successfully built more than 100 successful projects for our clients in the US, UK, Europe, Japan, Korea, Singapore, and many more.
5. If you are interested in a digital twin solution for your warehouse, drop us a message. We are always eager to discuss new opportunities.
This article was originally posted on May 19 2021 and updated on 13 October 2021 for more in-depth and relevance.
Trang is a graduate majoring in Economics & Finance. She became a tech writer as for her interest in Finance and Technology. She believes that these industries will be will be the changemakers of the future.