Across our industry, you hear people talking about the digital transformation of manufacturing – what it looks like and how it’s happening in a variety of ways. Much effort is being spent to define the scope and vision behind individual initiatives, whether they’re labeled under the umbrella of the industrial internet of things (IIoT), Industrie 4.0, intelligent energy, or some other term, but the fundamental concept is the same: Technology is enabling new business models that promise to deliver significant value in the areas of operations performance and reliability while addressing long-standing and unresolved issues.
One such model – performance and reliability monitoring as a service – leverages streaming data and analytical models to detect problems that might otherwise go unseen. Rather than relying on infrequent route-based data collection, sensors and gateways can securely stream data to service providers. Wired and wireless gateways can be installed in dedicated monitoring networks that are isolated from other networks and require higher levels of security and performance. Data from these networks can be combined with process historian data for contextualization and more-advanced analytical models. Service providers can develop analytical models and offer deep expertise with a focus on specific equipment types and industry applications that can be deployed across an entire fleet of equipment across multiple sites.
Early detection of potential equipment failures or process upsets can result in better planning for maintenance, avoidance of unplanned downtime, increased process availability, and reduced maintenance costs. New technologies such as innovative sensing, wireless networks, inexpensive microprocessors, flexible messaging protocols, cloud computing, advanced analytics, and mobile tools provide opportunities to improve asset performance and reliability. These technologies enhance early fault detection and improve the capability to automate workflows to take corrective actions – a process that previously required complex manual work procedures and protocols that are challenging to scale and sustain.
Pervasive sensing: more measurement points, better monitoring
The most basic method for reliability monitoring is built on route-based data collection. This approach can deliver incremental value in focused areas, but it involves manual activities that are costly, subject to failure, and performed infrequently. Work processes in this kind of environment generally lead to on-site equipment inspection, which relies heavily on the technician or operator in the field.
Preventive, predictive, and corrective maintenance programs are increasingly dependent on instrumentation for online monitoring of critical process equipment. New sensing tools are making it possible to get increased visibility of assets or processes by providing more measurements at a lower installed cost. These measurements – for vibration or corrosion, for example – can help organizations detect a variety of undesirable conditions: leaks, overheating, equipment damage, and more. Connecting these sensors to networks that are independent of control and safety systems can mean faster deployment and reduced cybersecurity risk. In some cases, these monitoring networks operate completely separately from other networks.
On-site expertise is hard to come by
Many plants are looking to improve the performance and reliability of their operations, but they lack the scale to support the investment in technology and expertise that is required to be successful. For those facilities that have invested in instrumentation for data collection, hiring and retaining qualified experts can be difficult and costly. Most plants are attempting to accomplish more with fewer people. Even if a plant has trained engineers on site, the majority of their time is dedicated to urgently solving complex problems in the plant rather than studying data in an office. In either case, a lack of focused domain expertise can cause valuable data to go unused.
In many cases, having enough qualified engineers to staff every plant is an unrealistic proposition. In addition, experienced workers are retiring from the workforce at a staggering rate, making it difficult to find replacements. Whether the organization simply doesn’t have the resources or skilled engineers aren’t available, staying ahead of the curve in production means finding new ways to put data in the hands of experts.
For manufacturers with multiple production sites, the problem of thinly stretched resources can be remedied by centralizing reliability and performance monitoring experts in a center of excellence. This approach is becoming common in the oil and gas, power, and mining industries. Advances in wireless technology and video collaboration have made it possible for engineering experts employed by the company to be centralized in a physical location where they can monitor data across the enterprise, receiving information in real time. This allows all plant locations to have the benefit of expert analysts tracking data trends for predictive maintenance while still limiting the number of engineers the company needs to employ and keeping travel to a minimum.