Sustain Digital Transformation Momentum
EP Editorial Staff | July 20, 2022
The connectivity solutions put in place during the pandemic are a strong foundation for improved plant reliability and sustainability well into the future.
By Erik Lindhjem, Emerson
Businesses needed to adapt more in the past few years than in the decades preceding. The global pandemic rocked the foundation upon which those businesses were built, and process manufacturers were no exception. Almost overnight, organizations had to find ways to continue to operate—in many cases 24×7—with fewer people in the plant and less predictability in daily schedules. The result was an increased and immediate need for automated solutions to help monitor and maintain plant equipment and operations.
Today, as the effects of the pandemic recede, the most successful process manufacturers are not slowing their adaptation. On the contrary, they are taking advantage of the new investments they made prior to and during the pandemic to stay in step with two intertwined trends currently shaping the global marketplace: a need for a more connected digital workforce and a drive for increased sustainability. The organizations that win the future of manufacturing will be those who leverage technology to boost their capabilities in these areas to better meet the needs of their personnel, customers, and bottom line.
Connectivity unlocks possibility
Well before the global pandemic, many reliability teams were digitally transforming day-to-day plant management. With a rapid decrease in the cost of and an increase in the quality of wireless sensing devices, teams could instantly gain visibility of any asset, whether it was in the plant or at a site remote from the control room. Most organizations had at least begun online-monitoring pilot projects. When pandemic-related lockdowns occurred, plants found themselves at varying levels of readiness to facilitate offsite operations.
Nearly overnight, process manufacturers around the globe began to scale up their online-monitoring pilot projects. Many implemented edge-analytics devices and predictive-intelligence software solutions to deliver critical data to key personnel who could no longer sit in the control room. Teams also installed more sensors and connected them to cloud-enabled asset-management software. Cloud capability enabled offsite personnel to continuously monitor asset health and receive intuitive alerts when asset performance deteriorated.
Armed with predictive intelligence well before failure, these, now remote, personnel could work closely with onsite team members to intervene before small problems led to expensive failures that would have been complicated to fix with short-staffed maintenance crews.
A key partnership
Expanding remote connectivity did not happen in a vacuum. It required strong collaboration between reliability teams and their information technology (IT) partners—a relationship that is also key to the strategies driving a more successful manufacturing future. Working closely together, reliability and IT teams used their knowledge to build the secure technology solutions offsite workers needed to enable continuous reliable production.
Many forward-thinking organizations were already using industrial solutions, such as condition-monitoring platforms built with remote connectivity in mind. These systems offered web-based interfaces for fast and easy connectivity and could be easily integrated with cloud-based asset-management platforms.
Other teams—typically those with a smaller condition-monitoring footprint already in place—relied more heavily on existing consumer-grade IT solutions for connectivity. These solutions could be customized to create temporary gateways for remote monitoring.
Regardless of the solutions the reliability and IT team partnerships chose, as business slowly returns to normal, those teams are finding the need for remote connectivity is not going away. As a result, the relationship between the two teams must continue to grow.
Plants using fit-for-purpose industrial condition-monitoring solutions discovered that the very tools that enabled remote monitoring of equipment also provided a pathway to a more mobile, digital workforce. These continuous condition-monitoring tools untethered personnel from manual inspection rounds by providing on-demand delivery of asset health data.
Today, these newly empowered digital workers receive instant, intuitive, actionable asset health data anywhere and at any time. This allows them to respond faster and more effectively to problems, while also freeing them to work on higher-value tasks, such as increasing performance.
Fully unlocking these capabilities, and ensuring they work efficiently and reliably across the plant equipment lifecycle, requires further collaboration with IT to use technology to not only remotely connect to data, but also to organize and contextualize it to continuously improve insights into the health and reliability of plant operations.
A system of systems
With access to more plant data than ever before, reliability teams have begun working with their IT partners to look beyond the health of individual assets and focus on the holistic health of the plant. Using multivariate data, these teams track, trend, and analyze information from sensors around the plant to identify big-picture problems.
Intuitive plant-health software collects and contextualizes data from disparate systems and combines them with analytics to track and trend the health of entire systems. Using data from sensors, maintenance records, inspection notes, computerized maintenance-management systems, and calibration data, reliability teams can better understand what is happening, empowering them to identify, isolate, and solve the plant’s biggest problems.
Consider a compressor that shows symptoms of a rub condition. Not long ago, a technician would have identified the problem during manual rounds, poured over the data provided by a portable analyzer, and likely studied the problem for weeks, or possibly replaced the bearing. If the same problem happened again in six months, the pattern might go unnoticed, and the process would start again, especially if the compressor was maintained by a different person each time.
In the same scenario—approached by today’s digitally connected workforce—access to multivariate data helps technicians immediately see how the system, rather than a component, might be failing. Continuous data collected from a wide variety of sensors and presented on a dashboard might instead show that the rub condition occurs simultaneously with a report from a digital valve positioner showing the valve is in the open position. What, at first, appeared to be wear and tear instead proves to be an operations issue, one that is easily and quickly corrected.
In tandem with the shift to more connected and distributed work, many process manufacturers are seeing a rapid shift in corporate mindset—driven by calls from investors and the public—toward more sustainable operations. Much like reliability, sustainability is enhanced by moving past the traditional method of focusing on individual assets to a more holistic focus on plant systems.
Moving toward more sustainable operations need not start with massive, groundbreaking projects. Sustainability and reliability are intertwined and making small strides in reliability often results in increased sustainability operation. Those reliability strides are often unlocked by moves the plant is already making toward a connected, digital workforce.
For example, as process manufacturers begin to use their connected systems to build strong predictive-maintenance programs, they quickly stop allowing machines to run to failure. Historically, this change in approach was driven by the significant cost savings of repair over replacement. Today, the ability to demonstrate reduced waste is proving nearly as important.
If, instead of replacing an entire failed motor, the reliability team can instead predict wear on a bearing and replace it before the motor seizes, the amount of waste going to a landfill is dramatically reduced. Repair, rather than replacement, eliminates significant part and packaging waste to incrementally help process manufacturers meet corporate sustainability goals.
Moreover, each asset that operates at designed performance levels contributes to a more reliable, and thus sustainable, plant. When reliability teams have the predictive-maintenance tools to identify problems and intervene before asset performance degradation, they can keep equipment running at peak efficiency—meaning reduced emissions and less energy use. It can even result in fewer expedited parts orders, reducing the environmental impact of extraneous transportation.
The newest, most advanced reliability technologies—such as high-fidelity simulation software—can help drive even more efficiency, while promoting sustainable operations. Digital-twin simulations create highly accurate, interactive replicas of plant processes, which can be used to test new methods to improve plant performance.
Though the transition to digital operations generated some growing pains at the beginning of the global pandemic, the ripple effect those digital-transformation decisions are having today has created an unprecedented era of maintenance and reliability improvement. These connectivity upgrades can be a perfect springboard for adding other technologies to increase the effectiveness of reliability actions. Leveraging comprehensive software tools, such as predictive-maintenance, analytics, and simulation platforms—in tandem with the sensors you already have in place—will help unlock fast return on investment and demonstrable gains in performance, efficiency, and sustainability across the enterprise. EP
Erik Lindhjem is Vice President and General Manager of Emerson’s Reliability Solutions, St. Louis (emerson.com) business. He is focused on driving digital transformation that enables clients to reach top-quartile performance. Lindhjem holds a bachelor’s degree in mechanical engineering from the Univ. of Virginia, Charlottesville, and a master’s degree in business administration from the Wake Forest Univ., Winston-Salem, NC.