If you’re reading this, you’ve probably heard that the digital twin can enable your manufacturing facility:
- Optimize its operations and production cycles to go to market faster
- leverage data-driven analysis to make better decisions that increase revenue
- Monitor operations in real-time to reduce errors and increase throughput
All you have heard is accurate but the digital twin can help you accomplish much more. The digital twin is a high-performing virtual model of your facilities that facilitates the transfer of data to-and-from the physical factory. The cyber-physical system a digital twin creates captures unstructured data from the shop floor and attaches it to specific processes. Thus, it supports every data-producing operation including predictive maintenance, resource management, capacity planning etc.
The digital twin provides you with the insight to understand the present and accurately predict the future.
Leveraging the power the digital twin confers on manufacturing processes starts with choosing the right digital twin software. This comprehensive guide will help you apply an informed approach to choosing the right digital twin software to optimize your manufacturing processes.
Choosing the Right Digital Twin Software in 5 Steps
In manufacturing facilities where complex variables and processes must be executed to achieve a successful production cycle, complex production scenarios become difficult to track. The digital twin helps you capture the fast-moving scenarios and the data they produce within the context of a manufacturing facility. You can get started with choosing the right solution by:
1. Integrate C-level Decision Makers in the Selection Process
Purchasing, configuring, and creating digital representations of the factory floor and its processes requires capital. Although the returns are substantial, the startup costs could be off-putting to decision-makers.
The right digital twin software may not necessarily be the cheapest option or the most expensive, but you must be prepared to convince stakeholders about the importance of utilizing a digital twin. If an IT department or a trusted technical individual work within the enterprise, seeking assistance from the technical individual to convince decision–makers is recommended. Kick start the convincing process by speaking to decision-makers to educate them on the benefits of the digital twin. With the stakeholders by your side, your selection process will not be limited to choosing the most affordable digital twin software on the market but selecting a solution with cutting-edge features.
2. Define Your Use Case for the Digital Twin Solution
A digital twin is a tool with the capacity to solve complex design and operational problems within a facility. Its far-reaching abilities do not mean your first application of a digital twin should be targeted at solving every problem within the shop floor.
Defining why your facility needs a digital twin and which problem or problems it intends to solve is an important step to choosing the right solution. In a scenario where predictive maintenance is the use case, a digital twin that can capture machine and related IoT data to gain context into the equipment’s behavioral pattern will be the better solution to choose.
A rule of thumb for determining which use cases you intend to apply your digital twin to solve, involves listing the top three problems you would like to gain insight into. The list will help you decide which of the following types of digital twin solution meets your requirements:
- Parts Twining – This process involves the use of a digital twin to create virtual representations of parts or components of an item. Discrete digital twin software applications are the tools used for parts twining.
- Product Twining – The process of creating virtual representations of a product for evaluation and innovative reasons is called product twining. Discrete digital twin software is used for product twining.
- System and Process Twining – This process involves the creation of virtual representations of processes and systems within a facility. A digital twin of organizations or a simulation digital twin is the software used to develop a system or process twins.
Your use case should determine the category of digital twin software to consider when making a choice.
3. Define the Requirements and Features of the Digital Twin
Once you have decided on the use cases you intend to apply the digital twin to solve, the next step is compiling the features a digital twin must have to be able to evaluate these use cases.
For example, if you would like to apply your digital twin as a risk-based evaluation tool capable of evaluating risks and provide real-time solutions to mitigate them, then the digital twin must possess a risk-based evaluation feature.
Examples of features to consider include:
- A digital twin capable of running thousands of simulation scenarios to enable you evaluates multiple what-if scenarios during complex operations.
- A digital twin that provides scalability to account for increased manufacturing assets and process on the shop floor.
4. Support for Implemented Digital Transformation Initiatives
A digital twin thrives on data and in an ideal environment, data capturing digital transformation technologies should be in place before implementing a digital twin. The more data that can be captured from your shop floor the more accurate its digital twin will be.
Considerations for choosing a digital twin must include compatibility. The digital twin software must be capable of integrating the data within your enterprise resource planning software, IoT platforms etc. to create accurate representations. A bonus criterion to consider is the after-sales support digital twin software provider offers. After-sales support helps with easing the implementation process and utilizing the digital twin.
5. Consider the ROI of purchasing a Digital Twin
From whom or what much capital is invested, many returns are expected. The stakeholders you convinced to back the application of the digital twin to solve complex operational problems require results. Although forecasting the ROI of an investment in digital twin solutions can be difficult, it is not an impossible task.
You can forecast ROI by estimating what a digital twin solution brings to the table. The estimation process should be done through demo requests where the service provider utilizes your facilities historical data to create digital twins capable of solving problems. A digital twin solution capable of supporting the implementation of lean manufacturing procedures, reducing the time spent building models, and running simulations, as well as, integrates AI is capable of delivering revenue growth.
What Digital Twin Does Your Facility Needs?
The process of choosing a digital twin solution should not be rushed. You are encouraged to conduct extensive research and request demos from shortlisted vendors before making a choice. Making the right choice will lead to optimized manufacturing processes and gaining data-driven insight that leads to making data-driven plant optimization decisions.