The last 18 months has seen huge challenges and changes for asset managers. From the disruption of COVID to increasing regulations, the industry needs new and more efficient ways to manage assets. Many organisations are turning to technology, deploying sophisticated solutions that use asset data to generate insights and enable compliance with new standards. This technology presents a wealth of new concepts and terms to understand, from AI and ML to ERP, AMS and BIM. Some customers may be confused about what all the different aspects are and how everything integrates together. So, for anyone struggling with acronym overload, here’s our quick guide to the main terms and abbreviations:
1. CMMS (Computerised Maintenance Management System)
CMMS is software that centralises maintenance information and makes it easier for managers to streamline maintenance operations. It’s used by a variety of industries where physical infrastructure is critical, such as manufacturing, mining, transportation and building/facilities management.
2. Digital Twin
A Digital Twin is a digital model of a real-life object, process or system. For Asset Management, this could be a building or facility. It can be fed data to simulate how a real-life asset will perform. So, for example, you could test how a cooling system would cope with more people in the building.
3. EAM (Enterprise Asset Management)
Enterprise asset management (EAM) is about managing assets throughout their lifecycle, from installation to planning maintenance and eventual replacement. Assets may be fixed, such as buildings or machinery, or moving such as vehicles.
4. AMS (Asset Management System)
An asset management system is a set of processes and interactions to plan and control how you manage your assets.
5. ERP (Enterprise Resource Planning)
An ERP system is used to manage a business’s main processes. It’s typically a suite of applications that ranges from HR and finance to tracking stock and orders. ERP helps information flow throughout the business as well as connect with other parties.
6. IoT (Internet of Things)
IoT refers to machines and devices being connected to one another over the internet, using sensors to collect and exchange data. It includes everything from "smart" home appliances and building environmental control systems to self-driving cars and industrial machinery.
7. ML (Machine Learning)
Machine Learning involves machines learning how to do things without being programmed to do, and getting “smarter” and more accurate. For example, by analysing temperature and weather data against patterns of failure in a machine or system, a machine eventually gets better at predicting when future failures may occur.
8. BIM (Building Information Modelling)
BIM is about creating digital representations of physical buildings and using them to plan everything from design and construction to ongoing maintenance. The aim is to enable businesses, governments and other stakeholders to share data and contribute to the same model.
9. Data Visualisation
With data visualisation, information is converted into a visual display, such as a graph or chart, rather than a table of values. For asset management, it could be used to show a heat map of facility usage or display the location of malfunctioning equipment in a building, making it quicker and easier to plan maintenance routes.
10. SaaS (Software-as-a-Service)
SaaS is effectively about renting software on a continual basis rather than buying it in one go. SaaS solutions are typically cloud-based, making deployment instant, and allowing users to be added or removed as required. This also means that updates and new features are handled "behind the scenes", so users don’t have to install anything.
At AssetFuture, our solutions involve a lot of different technologies and concepts. It can be easy to forget that not everyone understands all the jargon, so we hope this will be a helpful guide.
You can also learn more about the core concepts on the Asset Management Council (AMC) website.