Plant operations insights

• Operational risk is prominent on any plant floor and must be addressed to make the plant as safe as possible for the operators.
• Operation failures have gone up over the years, with many plants using a manual system to record shift handover information.
• Utilizing an ERP and data historians will help mitigate plant operations and operational risk to build a more productive, efficient and safe work environment.

Operational risk, particularly in chemical processing plants, is not a new phenomenon. However, the level of risk has increased as advancements in technology and machines have made plant operations more complex. Paper logs, spreadsheets, and emails are no longer reliable systems to ensure safety and operational best practices.  As mechanical technology has become more sophisticated, what can a chemical plant do to mitigate potential problems?  Just how risky has it become for plants?

Operational risk is an everyday concern and can run the gamut from minor anomalies to potential production interruptions or even hazardous events. Responsibilities for safety best practices reside with workers throughout the organization – from plant and production managers to chemical engineers, maintenance personnel, shift supervisors, and plant floor workers.  It’s a team effort where individuals must coalesce around a shared focus of information sharing, particularly in the area of shift-to-shift communication.

Research conducted by the 451 Group asked 300 senior executives representing the chemical, pharma, and petrochemical derivatives process industries, what percentage of safety incidents had occurred during their tenure were a direct or indirect result of communication breakdowns between shift teams and senior staff. More than 60% of respondents said up to 25% of incidents fell into that category, and another 20% said up to half of the reported incidents were due to these communication failures.

What can trigger a failure

There has been much reported on catastrophic incidents over the years, including one of the most devasting at the Bhopal plant in India in 1984 which resulted in 2,000 casualties, and the more recent DuPont chemical plant accident in 2014, which also resulted in fatalities. These disasters each were attributed to, among other issues, a lack of information-sharing. In the case of DuPont, the U.S. Chemical Safety Board investigation uncovered flawed safety planning and procedures when workers did not communicate information about a blocked valve in one area of the plant. When workers in a different area opened valves in response to what they thought was a routine pressure problem, toxic vapors escaped which resulted in the fatalities and thus highlighted significant safety and procedure problems in the plant.

It’s common during plant operations to have the shifts monitor the constant stream of raw materials through the continuous process encompassing filtration, mixing, temperature, and pressure changes to create a flow of final product.  Most of these plants utilize an ad hoc, manual system of recording shift handover information, and the operation teams meet to discuss issues and status as part of the regular shift handover process.

A day in the life

In the day of the life of one engineer, David, who started his 12-hour shift with a safety meeting and then proceeded with some routine process checks, noticed a slight fluctuation in pressure in one part of the process but found it still well within tolerance levels. At the shift handover, he decides that the fluctuation isn’t noteworthy enough to jot down on the whiteboard, but during a casual conversation on the way out of the handover meeting, David simply mentions it to his peer Pat, who is about to start the night shift. Pat agrees to keep an eye on the pressure level.

During Pat’s 12-hour night shift, no noticeable fluctuation occurs as far as he can determine. As the following day shift begins work, Pat makes no mention of the original fluctuation at the handover meeting, in part because David, who originally noted the concern, is not working today. Now, none of the engineers on this day shift have any evidence or gut feeling that anything might be operating incorrectly. However, as the day shift begins, several systems start to exhibit fluctuations. The root causes are not yet known, and as things worsen, production is halted while lengthy investigations begin.

Had an enterprise platform for plant process management been in place, the first shift engineer, David, would have been able to make a digital note of the pressure concerns giving Pat’s night shift full transparency on that issue, as well as any additional concerns from other engineers. This would have given the night shift a heads-up on the problem before it worsened. But, even if that early resolution did not happen, the following day shift would have an information trail leading to the potential root cause of the problem much sooner, possibly averting a full shutdown and loss of production time. Despite the absence of the engineer David, the day shift would still have the information they needed.

Taken to the next level, consider that the same plant has been upgraded with a fleet of connected industrial IoT sensors feeding into a predictive maintenance system such as SAP. The initial slight fluctuation in pressure would be identified by the system but being within tolerance, it would not prompt any action. Going into the 12-hour night shift, nothing is yet triggering the process management algorithm. By the second-day shift, however, the system would start to register the growing combined impact of multiple and varying data points. It would deliver an alert, giving production teams an early diagnosis and the ability to seamlessly send this information to the maintenance system for further diagnosis and subsequent action.

With a plant operations and process management system set up, David’s initial concern during the first 12-hour day shift would act as an input to the predictive maintenance algorithm. A digitally recorded fluctuation combined with a human engineer’s concern significantly heightens the validity of the data. This then provides early warning remedial actions for the night shift, as opposed to waiting until the degradation worsens the following day. In addition, due to it being a machine-learning approach, at any time in the future when a similar incident occurs, if an engineer notices a problem mid-shift and digitally records it during an inspection round, warnings and work orders can be issued even earlier for preventative maintenance activity. With this digital recording, machines and humans are now working in harmony, while augmenting and increasing each other’s overall intelligence. Workers’ experiences and observations of any industrial process or system, and their communication with one another, are worthy data points that are on par with, or possibly even more significant than data simply generated by equipment instrumentation. It clearly demonstrates the importance of maintaining a timely and transparent communications stream.

Elevating the information flow

Plant operations and safety will always remain a critical issue in manufacturing plant operations and a shift-to-shift communication platform integrated with ERP, historians, and maintenance systems is foundational to delivering proactive solutions to plant floor issues. An enterprise-wide solution to support shift communication can also deliver wider access to communications gaps. This alleviates information silos that inhibit safety and plant reliability by contextualizing data and providing visual dashboards easily accessible to all plant hierarchies to ensure plant integrity, quality, safety, and audit trails for regulatory performance. And, in this era of worker transitions, this communications platform captures the valuable knowledge of long-term employees to address new workforce demographics.

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