Experts reveal the benefits of using AI for predictive maintenance in facilities management
In the facilities management space, the convergence of Artificial Intelligence (AI) and predictive maintenance is urgent and innovative. By melding AI’s analytical prowess with real-time data, this transformative approach averts operational disruptions, slashes costs, and elevates facilities’ performance.
Explaining this much better is Javeria Aijaz, Managing Director of HITEK. She says: “Since the inception of AI, it has found widespread application and endorsement across all sectors. Over time, it has become a subject of extensive discussion and implementation efforts within facilities management. This transition aims to move away from traditional modes of reactive, corrective, and planned maintenance towards the realm of predictive maintenance. AI brings forth a multitude of significant benefits, including cost savings, prolonged equipment lifespan, heightened reliability, streamlined maintenance scheduling, data-driven insights, minimised downtime, safety enhancements, condition-based monitoring, efficient resource allocation, and a competitive edge.”
HITEK, a UAE-based provider of smart facilities management (FM) solutions, is part of Farnek group of companies.
Aijaz adds that in contrast to conventional maintenance methodologies that rely on fixed schedules or respond to failures, AI-driven predictive maintenance operates proactively and is tailored to the specific attributes of each piece of equipment. As a result, it not only delivers cost savings but also enhances resource scheduling and utilisation, thereby amplifying overall facility efficiency. Traditional maintenance approaches can sometimes result in inadequate or excessive equipment upkeep, leading to increased operational expenses and heightened downtime due to unforeseen breakdowns.
“While AI offers a plethora of advantages, its integration must be executed judiciously into existing maintenance strategies. This involves considering pivotal factors such as data quality, model precision, and the expertise of maintenance personnel. It is through this strategic fusion of AI capabilities with the existing framework that its true potential can be harnessed to drive efficiency, effectiveness, and lasting operational gains within facilities management,” says Aijaz.
In response to the growing demand for AI, an application called CAFMTEK was developed by HITEK. This smart, secure, and sustainable maintenance management tool incorporates AI throughout its processes, starting from the assets level. By harnessing predictive maintenance approaches, this tool assists organisations in transitioning their processes from traditional to predictive maintenance.
Challenges
“To address the challenges, organisations can adopt a holistic approach that encompasses technical, organisational, and cultural considerations. Forming multidisciplinary teams, executing pilot projects, selecting experienced vendors, and providing continuous training, monitoring, and optimisation of AI models are measures that contribute to the successful adoption and long-term benefits in facilities management.
“Several challenges and barriers must be addressed before embarking on any AI implementation. As an organisation, we have integrated AI into our overall strategy to maximise efficiency and reap its benefits. We have established working groups comprising FM professionals, system designers, and AI developers. Their collaboration has resulted in the creation of standardised operating procedures for training and operating AI models, as well as end-user training.”
HITEK has successfully implemented AI-driven predictive maintenance within CMMS solutions, providing FM teams with the tools to make data-driven and informed decisions. This empowers teams to optimise energy usage, lower operational costs, and elevate facilities’ overall efficiency. Notably, other prominent players in the market have also embraced AI-driven predictive maintenance. Examples include Royal Dutch Shell, Siemens Gas Turbines, and Honeywell Building Management System. All these entities share a common goal: to achieve enhanced efficiency, cost reduction in maintenance, and increased energy output.
Aijaz adds: “These instances underscore how AI-driven predictive maintenance has the potential to revolutionise efficiency, minimise downtime, and elevate operational performance across diverse industries and sectors within facilities management. By harnessing insights derived from data, organisations can confidently make informed choices, efficiently allocate resources, and ensure the seamless operation of critical equipment and systems.”
Aijaz says: “AI-driven predictive maintenance relies on data-hungry models that necessitate a continuous flow of precise, consistent data for making accurate predictions. This practice helps avert potential issues or challenges. Achieving this data feeding process is feasible through various methods, with manual data entry and the utilisation of available sensor technologies being the most vital approaches.”
As an organisation, HITEK also employs sensor technologies to gather data from assets, yielding positive outcomes. Among the key IoT sensors widely utilised by HITEK are those for current, temperature, voltage, vibration, and the Building Management System (BMS). Leveraging this data, the CAFMTEK platform generates and assigns work orders for assets requiring maintenance. Emphasising both intelligence and security, HITEK places significant importance on data security and employs industry-standard encryption technologies. This ensures that all assets are meticulously monitored and maintained to operate at their utmost efficiency.
Aijaz concludes: “As we all know that AI is the future as its is advancement is increasing day by day, so in order to adapt the continuously changing and enhancing technologies, organisations must have a strategy in place to create multidisciplinary teams that are working and collaborating together to bring the AI to existing organisational set up so that it can be utilised to drive efficiency and cost optimisation.”
In an era where efficiency and uptime are paramount, the marriage of AI and predictive maintenance in FM offers not just a glimpse, but a tangible path to a smarter, more resilient future. By harnessing the potential of AI, organisations can navigate maintenance challenges with foresight, ensuring facilities operate at their best while embracing a new standard of operational excellence.