The following webinars may be viewed online. Each lasts about an hour. They are taken from our monthly live offerings. To view them in your browser, click 'Read more...' on the right of the page.  

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The cost of downtime and degraded production from abnormal events is a major cost in the process industry. Giving your operators additional warning of situations such as column flooding, valve failure or equipment fouling can dramatically reduce production losses. Traditional condition monitoring and fault detection models are time consuming and expensive to create and maintain. Here we present a simple, low-cost method based on process history which can be implemented by a trained engineer in a matter of hours.

C Process Modeller, PPCL’s real-time process monitoring software, provides faster, earlier detection of faults against a standard benchmark. This webinar introduces our unique and innovative Geometric Process Control (GPC) technology and demonstrates its application to a standard process benchmark for fault-detection techniques, the Tennessee Eastman process, looking at case studies from real process plants.

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Most process plants today operate with excess energy. This not only increases operating costs but affects the maintenance costs and lifetimes of fired heaters. It also requires excessive cooling capacity to remove the excess energy later in the process. Why is it done? Well, it is usually ‘easier’ for operations to operate with excess energy and after a while that level of energy becomes the norm and the organisation stops pressing for improvement.

But it needn’t be like this!

C Visual Explorer (CVE) is our innovative interrogative visualisation software. It has allowed engineers around the world to investigate the historic operation of their plant and identify their best energy usage, giving them the key parameters, targets and MPC constraints to better replicate past best operation into the future. Results reported by some of our users include increased paraxylene production without increasing energy input; tracking non-stationary energy minimums in an LNG refrigeration system with a look-up table of constraints to guide MPC controls to the current minimum; and avoiding historic energy blackspots in a hydrocracker through being able to see non-linearities. All of these delivered substantially reduced energy usage and operating costs as a direct result of the insights provided by CVE.

It is surprisingly easy to achieve results such as these with CVE compared to other analytical methods as CVE usage is entirely visual and designed by experienced process and control engineers for use by experienced process and control engineers. Watch this webinar to find out how it is done.

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Process plants generate continuous time-series data for thousands of variables. This data has enormous potential, untapped today because of the limitations of process engineers’ conventional analysis tools. Fashionable “Big Data” approaches are challenged by process plant data and have limited applications for busy process and control engineers. Predictive Analytics, a time-consuming method which requires a data scientist to interpret the results, provides generalized answers through simplifications which can destroy much of the richness of the data. Geometric Process Control (GPC) – a technology developed here at Process Plant Computing Ltd – avoids these pitfalls and provides engineers with graphical tools to work with datasets spanning their entire plant which create low-cost predictive models without equations to develop new process understanding quickly and easily.

This webinar from October 2018 starts with analysis of a process with 750 variables over a year at 10-minute intervals. We discuss how to approach big datasets and explore them visually, using operating envelopes and finding interactions between variables. Covering the entire process including incoming analyses through processing conditions to final quality variables, KPIs and performance variables, GPC enables engineers to fully explore their data and make discoveries that they can’t now. We also demonstrate real-time online GPC models that provide ongoing enforcement of your discoveries for achieving quality targets and operational excellence long after you have moved on to your next project.

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The alarm system is a key tool for operators to maintain the efficient operation of the process plant. Why are there so many issues? Nuisance alarms and alarms that have been stale for far too long cost us production, as well as potentially contributing to process incidents. How can we make the alarms, and the alarm process, better? Geometric Process Control is the answer, demonstrating the relationship between operator alarms and process behaviour and leading to a revolution in alarm management.

This webinar will demonstrate the fundamental understanding relating operator alarm limits to process behavior, enabling the creation and management of an entire set of alarm limits. This differentiates Modern Alarm Rationalization from the isolated alarm methods currently used across the industry. With this technique, alarm limits and their performance can be evaluated before putting them in place, forcing underlying process issues to be recognized and addressed. This is dramatically different from today’s try-it-and-see approach to “bad actors” and allows a rational process for setting alarm limits that have never activated. The result is much better alarm limits taking up less process engineering time, thereby reducing the number, duration and staff levels of review meetings.

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In this webinar from July 2018, Dr Alan Mahoney, PPCL's Operations and Technical Director, shares our insights and methods for higher quality batch processes.

He demonstrates improving the yield of a multi-phase, multi-stage batch process. Dramatic reduction of quality variability and improvement of cycle times for batch processes, product/grade transitions and plant start-ups can be achieved by finding the best historic operating envelope, identifying the processing stages and targeting the key variables that drive process differences. Dr Mahoney shows you how to find these envelopes and identify the key variables which drive achievement of quality goals. We also investigate real-time monitoring of multi-dimensional operating envelope models which goes far beyond following single-variable trajectories and instead considers the ideal relationship between variables at each point in the batch.

The data required to drive these improvements is already available in your plant historian. PPCL’s C Visual Explorer is the vital tool to unlock that information, putting it on an interactive graph so that engineering and operations can investigate it for process discovery, test hypotheses and evaluate the effect of targeted operations. This visual method requires no higher mathematics training, only process knowledge to ask and answer the questions whose answers will drive better and better production.

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Process plants rarely operate consistently at their minimum energy input. A number of factors contribute to this, including lack of knowledge of the best conditions and also the ease of operation with excess energy. There is an inevitable drift back to higher energy operation without ongoing monitoring and feedback as part of energy minimisation.

Process engineers worldwide using C Visual Explorer (CVE) – innovative software developed here at PPCL - to investigate historic data from PI, PHD, IP21 and similar have produced some remarkable process improvements in remarkably little time. Results include increasing the product output of a paraxylene plant already at maximum energy input; identifying and steering an LNG refrigeration process to the best of several non-stationary local efficiency optima by adjusting the constraints of existing MPC controls; and providing a hydrocracker operator with a map to avoid several high energy sink-holes that were not previously known, reducing energy usage by 40%.

In this webinar, first delivered by our Technical and Operations Director Dr Alan Mahoney in May 2018, we demonstrate our simple no-maths visual method which requires only the knowledge of the process and its operating objectives and practices which senior process engineers already possess. It uses data already in your plant historian and can identify operational changes to a lower energy operating window. We also discuss maintaining improved operation into the future and real time guidance for the operator and/or existing process control systems.

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Do your Key Performance Indicators drive Operational Excellence? Or does Operations pay lip-service to some targets that they consider unrealistic?

ARE they unrealistic?
How and why do unrealistic targets get created?
Is an impending abnormal event, such as pump failure, about to sabotage your pursuit of Operational Excellence?

In a modern process plant using traditional methods, identifying and evaluating KPI targets is somewhere between difficult and impossible. However, it becomes much easier when leading KPIs are positioned on an operating envelope defined by lagging KPIs.

Geometric Process Control, PPCL's innovative new technology, provides the way to quickly and easily see such an operating envelope across many hundreds of variables. This makes it immediately obvious to everyone which targets are inconsistent or unrealistic. Performance monitoring and reporting become clear and consistent for everyone involved, allowing process refinement and increasing understanding of how KPIs interact. The approach is radically different but, as with all really good inventions, much simpler than what it replaces.

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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. In this one hour webinar, presented in September 2017, Dr Alan Mahoney, PPCL's Technical Director, shows 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 demonstrates 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.

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Here at PPCL we have spent 25 years developing GPC (Geometric Process Control), an innovative new method of viewing process operations. Our work with gas production includes production fields, gas treatment and processing, LNG production, landing and re-vaporization. We have worked with LNG producers worldwide helping them to understand their process better by analyzing their data in far more detail than was previously possible. This work has contributed to achieving better operation through better alarms, process optimization and product compliance – improvements directly impacting the bottom line. 

This webinar from May 2017 takes an in-depth look at gas production. We demonstrate our technology using graphical tools to optimize product split in an LNG production train, monitor performance week-on-week and identify targets for process improvement. By connecting historical data completely across the process with quality variables, GPC enables value-finding in your process through data exploration and discovery which are simply not possible with today’s techniques.

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