One thing that has become abundantly clear to me over the last several years is the incredible synergy that occurs when digital transformation meets asset operations management (AOM). The convergence of these two symbiotic forces is reshaping plants and optimizing operational efficiency. Asset-intensive organizations have much to gain by adopting new approaches to data, collaboration, and communication — all supported by modern, consumer-grade technology experiences.
Here are some of the key ways that can happen:
Unleashing the Power of Data
We’ve all heard the term “garbage in, garbage out” when it comes to collecting data. Identifying the right data is the key to getting an accurate measure of your plant’s performance. For years, the most common way to collect data was through a computerized maintenance management system (CMMS) or through enterprise asset management (EAM) software. These tend to focus on the creation and completion of work orders and gathering related information.
Ideally, this data helps plant management track every stage of an asset's life cycle, allowing them to pay special attention to things like equipment downtime and asset depreciation. The data can even be connected to a facility’s financial software to inform purchasing decisions based on an asset's reliability.
Today, digital transformation takes that one step further with condition monitoring sensors that can collect different types of data such as vibration and infrared readings to diagnose issues with individual assets. An abnormality in the data signals a problem and prompts an inspection work order. The synergy between digital transformation and AOM eliminates the lag in data interpretation, allowing for agile responses to evolving situations. Real-time monitoring is pivotal in preventing costly downtime. Organizations can now detect anomalies, inefficiencies, or potential failures as they occur, empowering them to take immediate corrective action. This data can then help track the functionality of individual assets, informing future work orders, reliability analysis and maintenance planning.
By integrating digital transformation with AOM, plants gain unparalleled insights into their operational landscape. This transformation is not just about collecting data; it's about extracting actionable intelligence that enhances decision-making processes.
Machine Learning and Real-Time Monitoring
Machine learning is where artificial intelligence meets maintenance, giving plant managers the power to monitor critical assets around the clock. The moment something seems out of the ordinary, monitoring equipment can automatically communicate with a centralized computer system allowing technicians to take action before or immediately after failures occur.
This allows a plant to move toward more predictive maintenance, which leads to better performance and lower costs. For example, advanced level machine learning can sift through thousands of data points to calculate the likelihood that errors will result in a full malfunction.
The digital transformation that occurs with machine learning positively impacts AOM through:
- Lowering costs of monitoring
- Accelerating repairs
- Allocating resources efficiently
- Improving plant safety
- Reducing downtime
- Optimizing maintenance budgets
- Facilitating scaling and growth
Predictive maintenance is therefore a direct outcome of the collaboration between digital transformation and AOM. As a result, maintenance becomes a proactive and strategic activity, aligning with broader business objectives and ensuring that investments in asset performance yield maximum returns.
Enhanced Asset Reliability
The marriage of digital transformation and AOM enables organizations to move beyond traditional approaches to maintenance and reliability. Assets are no longer treated as standalone entities; instead, they become interconnected components within a larger ecosystem of data-driven insights.
For some plants, digital transformation may allow for the creation of a comprehensive digital twin or a virtual representation of physical assets. This digital twin evolves in real-time based on data collected from the actual asset. AOM strategies can leverage this digital representation to simulate various scenarios, predict potential failures, and optimize performance. This synergy results in enhanced asset reliability, as plants gain a deeper understanding of how each asset functions within the broader operational context. By embracing this holistic approach to asset management, businesses can achieve higher levels of reliability, ensuring that critical assets consistently operate at peak efficiency.
For others, focusing on the importance of maintenance work can enhance asset reliability and increase uptime. Plants that successfully reduce the amount of time that equipment spends offline through digital transformation find that reduced downtime equals more production, which equals more products and increased profit. In addition, benchmarking key performance indicators and metrics that track things like uptime asset availability or the number of breakdowns over a specific time period can help plants measure themselves against world-class standards when it comes to asset reliability.
Empowering Workforce with Smart Technologies
It’s clear that as an industry, manufacturing is struggling with a significant skills gap. The level of skill needed to work in this field is immense as plant technicians often work on multi-million dollar assets in highly complex and sometimes inherently dangerous environments. In addition, the rate that experienced workers in manufacturing are retiring is far outpacing new talent entering the field. These issues, coupled with digital transformation and advanced technologies that require a whole new skill set, threaten to stunt future progress and growth in the industry.
The integration of digital transformation and AOM extends beyond the fact that machines can empower the workforce with smart technologies. As assets become more interconnected and data-driven, plants can invest in technologies that enhance the capabilities of their workforce that are being asked to do more with less. Augmented reality, artificial intelligence, and other smart tools become integral components of the employee toolkit, fostering a culture of continuous improvement and innovation.
For example, through AR applications, technicians can access relevant information overlaid onto their physical environment, facilitating faster and more accurate decision-making. AI algorithms analyze vast datasets to offer recommendations for optimizing asset performance. The workforce becomes an active participant in the digital transformation journey, adapting to new technologies that enhance productivity, reduce human error, and contribute to the overall efficiency of operations.
This empowerment goes beyond the technical aspects, influencing organizational culture. As technicians embrace smart technologies, they become catalysts for change, driving a mindset of continuous learning and adaptation. Ideally, this not only transforms the way assets are managed but also shapes a workforce that is agile, tech-savvy, and ready to embrace the challenges of the digital age.
