Introduction
Industrial enterprises are increasingly under pressure to adopt and use asset maintenance solutions to elevate operational efficiency, ensure compliance, and optimise overall maintenance practices. These pressures have been heightened as a result of workforce shortages, budget constraints, and product optimisation needs.
Computerised Maintenance Management System (CMMS) software, such as PEMAC ASSETS is the starting point for digitalising asset maintenance strategies by providing a centralised platform for tracking maintenance activities, managing work orders, and keeping detailed records of asset performance.
Transforming Asset Management
In the 2023 Verdantix global survey, 65% of the 304 executives in operations, maintenance, engineering and process safety roles mentioned plans to increase investment in CMMS software to support asset maintenance planning, scheduling and work order management over the next 12 months.
While traditional CMMS tools primarily focus on managing work for reactive maintenance, there is a growing interest in deploying predictive maintenance to prevent costly downtime and extend the lifespan of assets. Sixty percent of respondents in the Verdantix global survey started plans to increase spending on initiatives to improve asset uptime or availability, reliability and integrity.
The CMMS market has responded to these needs through Industrial Internet of Things (IIoT) driven integrations and Artificial Intelligence (AI) based analytics. By connecting IIoT sensors to critical assets, asset managers can receive near real time asset condition and performance data, while AI algorithms provide anomaly detection to optimise maintenance strategies. Key benefits include:
- Enhanced asset performance: By enhancing CMMS capabilities with IIoT and AI, maintenance leaders can implement proactive strategies to continuously monitor asset conditions, analyse historical data patterns and future proof maintenance decisions to minimise unplanned downtime, optimise maintenance schedules, extend asset life, reduce maintenance costs, and achieve higher levels of asset reliability.
- Streamlined maintenance workflows: Data from IIoT sensors enables maintenance leaders to use CMMS to automatically optimise and trigger work orders based on real-time asset conditions, thereby reducing administrative burdens and enhancing productivity.
- Optimised inventory and spare parts management: IIoT sensors and automated storage systems, when integrated with CMMS, optimize inventory and spare parts management by providing real-time data, automating retrieval, reducing downtime, preventing stock outs, and improving overall efficiency in manufacturing operations..
- Remote troubleshooting and technician empowerment: IIoT sensors provide real-time data on asset condition and health for remote diagnostics, allowing technicians to make informed decisions and troubleshoot effectively. AI solutions further enhance this by operationalising and visualising maintenance expertise and asset data, placing these advanced resources directly in the hands of frontline workers. With CMMS tools largely supported by mobile applications, technicians can receive real-time alerts, access critical data, and execute AI-driven recommendations while in the field, minimizing the time spent on physical inspections, improving response times, and saving both time and resources.
Driving Digital Transformation
With 95% of industrial executives in the 2023 Verdantix global survey identifying the growing maturity and availability of technologies such as AI analytics and IIoT devices as key drivers of digital transformation in plant operations, the need for seamless integration with CMMS tools has never been more critical. By seamlessly connecting with IoT devices, ERP systems, and other enterprise software, CMMS solutions can streamline asset maintenance workflows, ensure consistency and accuracy across all systems, and automate critical processes like triggering work orders. For example, IIoT sensors continuously monitor critical equipment such as refrigeration units, mixers, and packaging lines in real-time, in food and beverage manufacturing facilities. AI algorithms analyse this data to predict potential failures, such as temperature fluctuations or mechanical wear, and recommend maintenance actions. This data is then sent to CMMS, which automatically generates work orders, ensuring timely interventions that prevent production delays, maintain product safety standards, extend equipment life, and optimize maintenance resources.
PEMAC, for example, has developed capabilities to integrate our CMMS software with 3rd party tools such as Programmable Logic Controllers (PLCs) through the PEMAC IIoT interface. This integration allows users to collect and analyse real-time data from production sensors, enabling the system to automatically generate work orders based on predefined rules whenever an anomaly is detected. This helps firms achieve more holistic asset management, eliminate manual interventions, improve operational efficiency, and ensure that maintenance practices remain closely aligned with broader business objectives. A recent Verdantix Asset Maintenance Report observed an approximate 50% reduction in time spent on work management related tasks, unplanned work and reactive maintenance through the implementation of automated and digitized maintenance workflows.
However, firms seeking to integrate IIoT and AI into their CMMS workflows must consider challenges associated with data security, the need for skilled personnel to manage and interpret complex data sets, training requirements and capital investment needs.
Conclusion
As asset maintenance activities increasingly focus on reducing downtime, extending asset life and optimising resources, industry experts such asVerdantix anticipate CMMS solutions to play a key role in supporting predictive maintenance planning and preventing compliance issues. Organisations that embrace the change will be better equipped to optimise their asset performance management practices.
