What is engineering data management? Key perception and advantages

Engineering data management (EDM) is important in modern engineering projects and industries, as it ensures the usability of data. Taking a strategic and systematic approach to the acquisition, organisation and analysis of engineering data, EDM maintains its quality throughout the lifecycle.

Being proficient in EDM means fully understanding the strategies, processes and tools involved to make sure engineering data is not just usable but also accessible and secure. When handled correctly, EDM facilitates informed decision-making, improves efficiency and leads to an environment where innovation can thrive.

The significance of engineering data management

Organised data management in industries like manufacturing, construction and software development is crucial for engineering teams, businesses and project success. Following EDM best practices enables engineers, designers and other stakeholders to work seamlessly together.

The key benefits of data management in engineering are:

• Ensuring data integrity and consistency, while reducing errors and the need to replicate work.
• Promoting collaboration between departments and removing silos through the sharing and reusing of critical data.
• Improving security and compliance of data with the relevant bodies and authorities.
• Protecting sensitive information and intellectual property from unauthorised access.
• Gaining valuable insights from in-depth data analysis.
• Optimising processes based on evidence provided by the data.
• Meeting quality control expectations and implementing engineering data solutions for continuous improvement.

Common challenges in EDM

Pain points found within the EDM discipline include data overload, versioning issues, collaboration barriers and security risks. Due to the complexity of having data spread across multiple systems, these challenges can make it difficult to retrieve data quickly and efficiently. By addressing these issues, the engineering data workflow can be restored.

Here are some strategies to counteract common EDM challenges:

Data overload

Data from various sources comes in multiple formats, which all need to be brought in line with each other before further processing can occur. Once the collected data has been standardised into a regular structure, it can be analysed and put to use.

Collaboration barriers

The lack of a unified data storage and sharing platform to enable consistent access to up-to-date project files can be a barrier to collaboration. Managing permissions for multiple stakeholders and facilitating clear communication around projects can help overcome these silos.

Security risks

All data is at risk of security breaches and the large volumes handled in engineering data systems is no exception. Access controls and encryption measures help to ensure the data management process is secure and only those who legitimately need access are granted it.

Versioning issues

Using older versions of data can easily happen when newer ones are constantly being created. This makes version control in engineering crucial, but can be managed with the right processes and modelling software.

The step-by-step process for successful engineering data management

There are seven key components of engineering data management that facilitate the building of a systematic framework to deal with vast quantities of data. Carrying out data processing in this way is crucial for engineering-intensive industries to move a product through its lifecycle.

Map the processes

Map each step the product will go through on its journey from idea and data acquisition to reality. Include all of the stages from conception of the initial idea to reaching the factory floor.

Assign responsibility for each step

Create a point of contact to take responsibility for capturing the data in their area at each stage in the product’s lifecycle. It doesn’t matter if they’re a team leader or a department head, but transparency in this will smooth the process.

Capture data

Capture as much of the data generated as possible, including documents, drawings, brand names and part numbers, as well as metadata like who created it and when it was most recently modified. It’s not always clear what data will be relevant in the future, so collect all of it.

Data categorisation

Choose a standard way to categorise data and label files so they’re all completed in the same format. These will prevent confusion and lead to more streamlined processes that are easier for everyone to follow.

Data storage

Data management systems can help to create a centralised storage space for data, which is not only accessible to those that need it, but also secure from those who don’t. Data security in engineering is crucial to remain compliant.

Ensuring compliance

Part of ​​data governance for engineering is to ensure it’s secure, private and accurate, as well as compliant with all the right regulatory bodies. Put frameworks, policies and standards in place to govern all data management activities.

Regular audits

Regular data backups and audits are required to mitigate the risks of data loss or systems breach. These measures will allow you to detect vulnerabilities and fix them as soon as possible to ensure business continuity.

Functional applications of engineering data management

The manufacturing, construction, aerospace and automotive industries rely heavily on EDM to carry out successful engineering projects. Being able to analyse and maintain engineering data throughout its lifecycle informs decisions, drives innovation and allows engineers, designers, and other stakeholders to collaborate effortlessly.

As a dynamic field, EDM is set to see many advances in the coming years, with artificial intelligence and machine learning set to aid in the automation of engineering data management. Augmented reality and virtual reality will transform the ways in which engineers visualise data, while the Internet of Things will increase the volume of engineering data being generated exponentially.

Career growth opportunities in engineering data management

Demand for EDM specialists is only set to grow in the future, with all areas of engineering increasingly relying on data. Areas that are set to be particularly in need of EDM skills are printed circuit board design and electrical design, creating interesting job opportunities for candidates in the industry.

Job roles to search for include:

• EDM specialist
• Data analyst
• IT consultant
• Field service engineer
• EDM machinist

Skills needed for a career in engineering data management

Landing a job in EDM means having the right skills and experience, which can be gained through training and certification programmes. Before signing up to obtain these qualifications, make sure they cover all the EDM skills you’re going to need. These include:

• Proficiency in data analysis
• Knowledge of EDM software
• Understanding of engineering workflows
• Ability to visualise data findings
• Capacity to build scalable and optimised databases and data warehouses