ARMour® - A Bureau Veritas Predictive Maintenance System
Enterprise Wide Predictive Maintenance Data Management System
As predictive maintenance programs increase in size, so too does the volume of information that needs to be reviewed, processed, filed and acted on. Often this is an ad-hoc process and the responsibility of dealing with this data is shared by many people across the organisation. This can make it difficult to quickly understand the current hot spots in your plant and it can be difficult to quickly retrieve the full predictive maintenance history for a particular asset.
What is ARMour®? ARMour is a state-of-the-art web based system for holistic management of the predictive maintenance data for your enterprise.
Why Choose Bureau Veritas
Recognition - Founded in 1828, Bureau Veritas is a worldwide leader specialised in QHSE and social responsibility services. Certified to ISO 9001 for all of its activities throughout the world, the company actively participates within professional authorities for the development of international standards and regulations.
Knowledge and Expertise - Technical knowledge and availability of our qualified local teams, able to provide packaged and targeted information, are strengths appreciated by our clients.
Network With a global network of over 900 locations in more than 140 countries, Bureau Veritas provides tailored solutions to clients throughout the world across a diverse range of industries.
FAQ - Frequently Asked Questions
Who owns the data?
You do. Bureau Veritas simply provides the systems and processes to manage that data.
How many users can access my data?
You can specify as many users as you like. They can have access to all of the data or only the areas that you authorise.
Can ARMour be integrated with my CMMS system?
Yes, we recommend that ARMour is integrated with your CMMS to allow the seamless creation of work orders or notifications.
Can ARMour be integrated with other CM providers’ systems?
Yes. ARMour can be integrated with any other sources of predictive maintenance data.