- Subscribe Today
- All Topics
- Training & Events
- Buyer's Guide
The demand for increased maintenance optimization will never dwindle. As plants continue to expand to meet the ever-increasing needs of consumers, they must identify new opportunities to advance facility practices.
Progressive technologies present new and unique solutions to a host of obstacles and offer a glimpse into what the future of maintenance looks like. From the C-Suite to the boots on the ground, these innovations offer measurable results that have a direct impact on job performance and facility productivity.
By using technology to strategically position themselves for increased efficiency and future growth, facilities can minimize the effects of the widening skills gap currently plaguing the industry. While new solutions regularly hit the market, technologies here to stay include the Industrial Internet of Things (IIoT), big data, the cloud, artificial intelligence (AI) and virtual reality (VR).
The Industrial Internet of Things (IIoT) is an interconnected network of devices and machines that collects data and communicates it directly to the maintenance team in real time. This technology focuses on machine automation and helps staff and managers minimize machine downtime by giving valuable assets a voice. This technology helps facility activities such as:
By connecting the maintenance team to the machines through IIoT, technicians can more accurately predict when an asset is expected to fail. This data allows them to plan and schedule maintenance at the optimal time, reducing unplanned outages and productivity losses.
The industry has seen these benefits, and as a result, the number of IIoT connections will increase from the current 17.7 billion to nearly 36.8 billion by 2025, representing a 107% growth rate.
For IIoT to be effective, it needs two things: sensors on the equipment and a software system to process and translate the data. While it does require an upfront expense, with sensors accounting for nearly 50% of the total cost, this investment is regained through an increase in production efficiency, a reduction in machine failures and a decrease in mismanaged inventory.
Other benefits of adopting IIoT include:
Because sensors constantly monitor equipment conditions, rather than performing calendar-based preventative maintenance, real-time data notifies the team when work is required. At its core, predictive maintenance is all about increasing maintenance effectiveness by performing maintenance only when it’s required.
While IIoT sensors allow teams to predict impending failures, they can also identify failure patterns and recurring issues. Not only can the team design a maintenance solution around this data, but Original Equipment Manufacturers (OEMs) can also use it to improve the quality and design of their machines.
If a machine does fail, the IIoT system has collected various source data, and the software can analyze it. Based on the results, the system can present the data and make appropriate recommendations about the best solution. With this, technicians have all the relevant information and can confirm the best path forward.
IIoT-connected machines can receive software updates as needed to enhance performance or fix technical issues. These updates are often completed remotely by the software company or OEM. This ensures that the machines are constantly evolving into more productive assets.
An IIoT system can also aid in inventory management. By having a connected stockroom, facilities can monitor what supplies are used to help make purchasing decisions. These decisions can lead to more accurate inventory stocking decisions and reduced spending. OEMs can also utilize this information to make more accurate spare part recommendations.
IIoT can also be used on remote equipment, eliminating the need to use precious maintenance time to get to the asset and perform the necessary checks. This reduces the overall time it takes to monitor a piece of equipment and lowers the costs associated with labor-intensive manual inspections.
Big data refers to a set of equipment data so large and comprehensive it’s extremely difficult for a technician or typical software system to effectively analyze. When combined with the challenge of processing multiple assets simultaneously, the job of deciphering this unstructured data becomes nearly impossible. One study found that 95% of businesses cite the need to manage unstructured data as one of the largest problems for their company.
Historically, this data has not been analyzed or utilized properly because it couldn’t be. But the introduction of elevated software systems such as IIoT platforms makes processing this data mine possible, revealing valuable information about the health and performance of critical assets.
Big data provides a holistic overview of a plant’s assets, revealing which machines are healthy, which need more attention and even how the assets interact and affect each other. Teams can take this information and apply it to their daily maintenance routines to improve asset performance, streamline maintenance processes and customize asset settings.
For example, big data is being used to accurately define an asset’s PF (Potential to Fail) interval, which describes the point where an asset fails to perform a required function. By more accurately defining the PF interval, maintenance teams can schedule maintenance based on the needs of the machine, not on feeling or failure.
While it has always been considered important, with no effective way to process the information, big data was often left out of the decision-making process. Now that technology has caught up with plant needs and can handle the information, this data can be harvested and utilized to make extraordinary leaps in plant optimization and maintenance. So many businesses have begun utilizing big data that the market is expected to be valued at $655 billion by 2029.
With the need for data to be available anywhere at any time in an easy-to-use manner, more facilities are turning to cloud-based data solutions instead of traditional onsite data storage. With cloud storage, data is saved on a secure, outside server hosted by a vendor that can be accessed remotely by an authorized user with an internet connection.
By making information easier to access for approved employees, production times, maintenance schedules and operational costs are all positively affected.
While these are often the highlights of a cloud-based system, other benefits include:
Because cloud-based storage is so accessible, the system can be outfitted for a facility's exact demands. By optimizing the experience to the relevant needs of the team, a company can customize its cloud experience to utilize the data in a way that positively impacts work performance and information searches.
Not only can the cloud store a vast amount of data, greater than that typically seen in onsite data systems, it can also be scaled up without having to add new equipment or processes. This ensures the system can handle all historical and future data.
Because the cloud doesn’t require onsite data silos, the implementation time is relatively low compared to traditional data storage systems. A facility can set up and begin using the new system quickly, allowing technicians to discover new information and maintenance opportunities that were buried in the traditional system.
The cloud is rapidly gaining industry approval, and it’s estimated that by 2025, the total worth of the cloud market will reach nearly $850 billion. Despite this vote of confidence, many still question the security of cloud systems. While some seek to exploit the system and gain access to valuable data, it was reported that 88% of all cloud data breaches were the result of human error, not a cloud provider security failure. With the safety, ease and multiple uses of cloud data systems, they are quickly becoming a viable option for many facilities.
Artificial Intelligence (AI) is a learning technology deployed in facilities to sort and transcribe big data into easy-to-understand reports. The reports are generated using a mix of current condition data, historical data and performance records to determine when a machine needs servicing. With this information, the maintenance team can make quick and informed decisions about the health of their machines.
By performing root cause analysis functions, AI can also help prevent asset failures and significantly decrease unplanned downtime. Because of these benefits, the AI revenue worldwide for 2022 reached a record $342 billion, showing that the world is ready to adopt and fully incorporate this technology into its everyday processes.
AI systems require the use of IIoT sensors that monitor machine activity and report the findings to the AI’s analytics program, where the complex data is synthesized and transcribed. Because AI is not a fixed technology, like onsite physical hardware, the system can also learn over time, allowing it to evolve to meet the demands of its facility.
To ensure the system evolves appropriately, it’s critical to work with the facility’s most experienced maintenance technicians during AI implementation to determine what machines and data need monitoring, what historical data could be added to improve performance and how often the data should be collected and transcribed.
Other benefits of AI technology include:
Virtual Reality (VR) is an incredibly advanced simulation tool that realistically recreates different scenarios that can be interacted with and learned from. The size and sophistication of this equipment vary depending on the type of VR experience needed. For instance, VR technology can be accessed on a single device or computer, or it can fill an entire room, allowing operators a deeper level of interaction with the digitally rendered environment.
Like its counterpart, Augmented Reality (AR) also allows for advanced computer-generated simulations, but instead of completely recreating a virtual scenario, it seeks to enhance the real world. For example, when purchasing an office chair, an employee could use their phone’s camera and an AR program to digitally insert what the chair would look like in the space before the product is ever purchased.
For example, if a technician is performing a maintenance task, instead of the AR system simply giving step-by-step instructions, the program can digitally render the steps onto the actual work surface to better guide the technician through the process. In this way, technicians are connected to advanced renderings and data without having to immerse themselves in a computer simulation.
VR is increasing in popularity, especially in industries where training presents challenges due to trainee inexperience and the cost of procuring physical training materials. VR gives members a safe space to explore the ins and outs of their job without their mistakes having an impact on actual plant assets or other employees.
VR technology is also deployed to help team members work through complex problems. If maintenance technicians encounter a unique anomaly, they can practice the necessary techniques in VR and learn from their mistakes before ever attempting it on the physical equipment.
Because of this, there has been a rapid growth in the demand for VR. In 2018, the estimated market value of VR for use in maintenance practices was $400 million. This number is now predicted to reach $3.3 billion by 2024.
Industries with a growing demand for VR and AR technology include:
By understanding how to solve a problem before ever stepping on the facility floor, team members can build confidence in their abilities and operate at a higher caliber. For the entire facility, this means more highly trained staff members, less downtime and a significant reduction in the mishandling of facility assets.
The future of the industry is here, and while the tools may look more like science fiction, the results are anything but. By leveraging these technologies, facilities can create an environment dedicated to the progression and enhancement of all assets and employees.