Successful completion of the scenario: On average, operators using the ASM interface successfully dealt with the situation 96% of the time. Operators using the traditional screen scored 70% on average representing a 26% improvement for the ASM interface group.
Presenting the results in a graphical format shows even more dramatically the difference in the performance of the two groups. In Figure 3, a clustered box plot of the Total Completion Time results, not only is the difference in the mean significant but the variability of the performance of the operators using the ASM interface was substantially smaller than the variability of the operators using the traditional interface.
Figure 3 - ASM interface allows faster response.
Using these results in an analysis designed to determine the average from a set of distributions of influencing variables also called a Monte Carlo simulation the study team assessed the impact on the plants operation. Historical incident records, in conjunction with the costs of the incidents were the other inputs to the simulation. The results showed the plant could save on the order of $800,000 per year by helping operators identify and react to plant problems with the ASM-style interface.
Elements of the ASM interface
The ASM-style displays used in the study are extensions of an earlier ASM display prototype called Abnormal Event and Guidance Information System (AEGIS). AEGIS was designed for scenario-based task analysis and was intended to improve the console operators situational awareness to changing plant conditions. The displays implemented in the study took it even further by integrating trends and provided access to additional online information, among other enhancements.
ASM interfaces are designed for proactive monitoring, which requires a big-picture awareness of the plant. Key features include integrated trends of information, multiple levels of increasing plant detail, and easy display navigation that is integrated with the process alarm management. This allows operators to see a broad picture of the process, but also gives rapid access to detailed information when necessary, in the context of the entire process.
Some of the key ASM features include:
- multi-windowing with controlled window management to minimize display overlays;
- multi-level, simultaneous views of increasing plant detail;
- yoked navigation between display levels (i.e., automated display invocation through pre-configured display associations for assisted, task-relevant navigation);
- tabbed navigation within a display level;
- integrated trending of historical information;
- integrated alarm management into graphics and navigation tabs
- right-mouse click access to online documentation;
- human factors graphics design (e.g., principled limited, color-coding of critical, changing information; limited 3-D objects; simple, effective symbols); and
- access to online information (e.g., alarm rationalization documentation, operating procedures, shift logbook, etc.)
The ASM-style interface presents process data in a way that better matches human cognitive abilities, making the data more valuable. For example, trends are continuously displayed to show critical-variable status over time, something that people are not good at estimating from memory based on snapshots of digital readouts. Color is selectively used to highlight dynamic information such as alarms and conditions that require an operators attention. Also, different levels of detail or a display hierarchy are simultaneously shown, which better matches the way people think about information when they are troubleshooting.
Future ASM work on proactive monitoring
The ASM Consortium currently is working to improve span of control overview displays. These screens allow operators to use pattern recognition to spot potential problems or process changes, without having to perform mental calculations to determine if the various values are deviating. These displays will monitor critical variables in the context of their limits and display visual indications of the operating envelopes (e.g., point value indicators and trends in the equipment graphics) as well as composite indicators or process and equipment health.
Another example is the consortiums research on early event detection techniques. Operators can take corrective actions without losing plant production by using advanced statistical methods to detect subtle changes in plant operation, often minutes or even hours ahead of any operator using traditional methods.
Many institutions devote their time to studying how to improve technological performance in chemical processing plants. However, given the significant production costs lost because of abnormal situations, value lies in working to improve human performance. Though these situations may be minor deviations that may never be reported to catastrophic incidents, their avoidance can translate into very powerful economic benefits.
We would like to extend our sincerest thanks to NOVA Chemicals for supporting and participating in the case study.