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Register below for one of our live webinars that share new approaches to process improvement & optimisation. 

Or watch one of our Pre-Recorded Webinars here...

Finding, Understanding and Repeating Best Operation with Operating Windows


Setting KPI targets and reporting is necessary, but for use in the control room these targets need to be translated into operating windows. It is easy to get this wrong and difficult to realize when the window becomes outdated. This one hour webinar demonstrates a better way to address these problems. There can be a new understanding of the relationship between KPI targets, operating targets and process objectives. The webinar shows how to use that understanding to find the best operating window to achieve KPI targets and other operating objectives. Providing the best operating window to operators is the essential first step toward repeating and improving best process operations.

Achieving Operational Excellence

Process plants have numerous “Key Performance Indicators” intended to guide everyone from process operators to senior management towards operational excellence. But do they?

KPI targets are set individually and it is not easy to confirm whether leading KPI’s really do contribute effectively to achievement of lagging KPI’s. It isn’t unheard-of for one KPI to conflict with another and different managers may disregard some KPI’s in favour of others. Operational excellence would suggest that all KPI’s, both leading and lagging, should be achieved.

It is easy to say that all KPI target values should be set to be consistent with each other, but there used not to be a way to achieve that, or even to test whether they were. But it is very easy to do when the leading KPI’s are positioned using an operating envelope that you can actually see defined by the lagging KPI’s and containing possibly hundreds of variables. The picture makes performance monitoring much easier for everyone, as is performance reporting. This, amongst other things, is the feedback to KPI target setting for further refinement and understanding of how KPI’s interact with each other.

The approach is radically different but, as with all really good inventions, much simpler than what it replaces.

In this webinar, Dr Robin Brooks, Founder and CEO of PPCL, explores how PPCL's innovative software products, CVE and CPM, could help YOUR process plant achieve operational excellence.

The webinar is suitable for anyone who has ever had an involvement in plant operations in any process industry or energy industry segment, or who has wondered if there was a fast, practical, no-maths method to extract the information and greater understanding that they always knew was buried in their process history data. Well, there is now!

PPCL is working across the world to improve business efficiency in process plants. Why not see what we could do with you?  

Avoiding Downtime through Event Forensics and Prediction


Value lost to downtime and degraded product quality during abnormal events and designed overcapacity to compensate are among the largest avoidable costs in any process plant. Process events come in the form of disturbances, faults, trips and excursions that cause downtime and lost production. Operational excellence requires reducing the frequency and impact of these events.

This webinar explores PPCL’s novel Geometric Process Control (GPC) technology for understanding the course and causes of these events and generating real-time operator alerts for early warning of developing future events.

The start is investigating events using historical data from the plant historian through C Visual Explorer (CVE). Building from individual events to discovering similarities between events, CVE allows investigating significantly larger datasets than most engineering applications, hundreds of variables across thousands of time points. This power lets us quickly see and explore data far beyond what we’d typically use.

PPCL’s online process monitoring tool, C Process Modeller (CPM), goes beyond traditional alerts by implicitly including the relationship between process variables and providing a sensitive detector for changes. By excluding events and event precursors from our model of normal operation, CPM provides a powerful low-cost method of building event prediction models that have been shown to provide hours or days of advance warning of process changes, giving plant personnel more time to react and mitigate the effects of disturbances and faults. We’ll look at examples including a gas turbine-driven generator and surge in a large propylene refrigeration compressor. CPM models can be created in just a few hours, bringing the benefits of condition monitoring to applications where it isn't currently economical. Process availability and efficiency will improve and facilitate the move toward predictive maintenance and operational excellence.

Reducing Operator Workload with Better Alarms


The role of operator alarms is to alert the operator of abnormal process operation as early as possible, giving the most time to react, address the developing issue and keep producing product while the plant is in a degraded state, or at worst shut the unit down in the most sympathetic way. Good alarms produce the economic benefits of higher plant availability and more saleable product, while reducing operator load, giving operators the ability to react to abnormal situations.

Achieving these benefits requires well-designed and properly positioned alarms as well as a healthy process. Many organizations have reviewed these alarm limits repeatedly through rationalization exercises, never getting the real benefits they know are possible.

C Visual Explorer (CVE), PPCL's flagship software product, provides a graphical framework for bringing the entire process history into the context of alarm rationalization. CVE lets engineers, operators and all involved see directly the full richness of operation and the process envelope, relating this immediately to current and potential alarm limits. The range of conditions a process experiences, including variations in feed, ambient temperature, changing demand, different goals and normal operation variability are included, linking operations through from incoming material to product quality and economic KPIs. It has never been easier to explore years of process history for thousands of variables for rationalization and other applications.

In this webinar, we demonstrate how to take full advantage of this display and data, leveraging the parallel plot to give easy access to historic data in the context of desired plant operation, alarm and process limits for hundreds of variables. Bringing historical operation into the alarm process allows the immediate evaluation of alarm limits, taking less time and enabling continuous alarm review, and giving better limits that have been pre-tested as well as vital process understanding. We give examples on real systems and discuss some of the successes our users have had.

GPC Technology for Big Data and Predictive Analytics in Process Plants

The Problem: Process plants generate continuous data for thousands of variables at sub-minute frequencies. This is far beyond what process engineers can analyse with their conventional analysis tools. This data has enormous value, containing the records of plant operation and implicitly the relationships between process variables and quality variables. But only a tiny fraction of this data is used today. Many may consider the “Big Data” methods that are the current buzz, but these approaches are challenged by process plant data.

Big Data techniques focus on pulling subtle correlations from largely uncorrelated data, but chemical processes have extensive relationships due to balances and governing physical laws. Predictive Analytics provides generalized answers through simplifications; choosing a small subset of variables, processing or averaging data, and ignoring the fundamental complexities such as nonlinearity of the process. This can destroy much of the richness of the data and reinforce preconceptions. It can also be time-consuming and require a statistician to interpret the results.

The Solution: Geometric Process Control (GPC) is a visual technology: quick and easy to understand and implement by anyone familiar with the process. Hundreds of variables can be seen simultaneously on one graph to gain an overall understanding of your operation, target investigation, test hypotheses and quickly identify improvements.

PPCL presents a Geometric Process Control alternative to reach the goals sought from Big Data and Predictive Analytics that shows how to operate the process so that objectives are met, keeping their values at the desired targets.

In the webinar, delivered in May 2017, Dr Alan Mahoney, PPCL's Technical Director, demonstrated GPC using graphical tools to screen for key variables and eliminate the effects of uncontrolled variables.  He showed how to approach big datasets and explore them visually using the parallel plot, a unique graphical technique that puts axes parallel to each other rather than perpendicular, allowing the exploration of interactions between variables with orders of magnitude fewer graphs. By connecting historical data completely across the process from incoming conditions and initial processing conditions to final quality variables, KPIs and performance with the richness of years of data in a technique that can examine hundreds of variables, the parallel plot enables discoveries and exploration that are not possible with today’s techniques. He also demonstrated online GPC models for achieving quality targets and operational excellence.

In Pursuit of Operational Excellence

Perhaps once or twice in a person’s career something comes along that is not just an improvement on what was there before. Starting from different principles, it makes possible what was previously unachievable or even unimaginable and, in time, establishes new levels of operational excellence. Many engineers in the 1960s could not imagine that computers would ever be of use in operating their plants, while younger engineers today have difficulty understanding how a plant could be run without them. Fax machines and photocopiers in the 1980s replaced the telex, typewriters, carbon-paper and internal-mail carts of the 1970s and in turn were replaced by word processing and email in the 1990s. The telephones of the 1980s and face-to-face trade-shows and meetings of the 1990s are even now are being replaced by video conferencing and instant messaging.

All these massive changes came about without great drama through individual engineers recognising easier and better ways to do things and creating pressure on their organisations to provide the necessary facilities. And the process of change continues.

PPCL has developed Geometric Process Control (GPC) with its 1,000-variable graph and the first-ever general method of modelling the operating envelope of a process as a multi-dimensional geometric object. The graph brings remarkable analytical, optimisation and monitoring power to the engineer without requiring more than high-school mathematics, and leads to the reduction of operational variability which is at the heart of operational excellence.

Operating envelope models are used for fault detection and prediction, predictive alarming, operator guidance, compliance with KPI’s, target-setting, SPC replacement or “just” for helping the process operator to stay inside many sets of operating limits and KPI limits simultaneously. The appeal of these models for plant use is that they are equation-less, requiring no maths but only process knowledge from the user. This makes them very cheap in man-hours to develop and maintain.

Before being exposed to Geometric Process Control, many have struggled to understand how a mathematical model could possibly be “equation-less” or why a 1,000 variable graph has such a big advantage over the traditional methods of Predictive Analytics. Seeing is understanding with GPC, and many have had a Eureka moment in our demonstrations and webinars as the accuracy of our descriptions and the potential of GPC strike home. PPCL is working in industries across the world to improve the business efficiency of process plants. Why not see what we could do for you?


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