Obviously, data-centric manufacturing requires data. The availability of good quality, appropriate data can make or break a DCM project at various stages. The first step, given a well-defined project, is to define what data is required. The next step is to find out how to get that data (if it is indeed possible). There are 3 main categories of data availability and each one will require different amounts of effort, resource and cost to acquire and process so that it can be used as planned. These are:
Data is available and ready for use.
Data is available but requires processing before it can be used.
Data is not yet available.
In each case it is vital that there is a plan to properly:
Manage the data.
Secure the data.
Store the data.
A comprehensive data strategy should be drawn up before data is collected and regularly updated as the project progresses.
Keeping track of the data utilised throughout a project can be complex, but is essential for adhering to the FAIR principles. This Excel-based template provides a foundation to streamline this process for you.
Maximise the accessibility and reusability of your research with a visual representation of the data flow throughout your analysis.
Note: Different data may require different levels of acquisition and processing. Each should be documented as necessary