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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Better operator alarms make money for YOUR plant by reducing operational variability, which contributes to a reduction in operating costs and, in cases where throughput is increased, to a reduction in the unit costs of production. The single biggest cause of poor operator alarm performance is the values at which the alarm limits are set. But search for advice on how to find correct alarm limits and the answer will be “put the limits at the boundary of where you normally operate”. For the practising engineer this advice is next to useless because he or she doesn’t have a way to locate that boundary across many hundreds of variables.

The key is an Operating Envelope or Operating Window spanning the many hundreds or even thousands of variables, some with alarms defined and some without.

In this webinar, first presented in February 2019, you will discover a simple visual method of locating the Operating Window and Envelope of any chosen set of objectives and of setting alarm limits around its boundary. You will see the usefulness of being able to see and compare Windows and Envelopes for different operating objectives and the benefits of predicting Alarm Performance with immediate feedback.

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Does achieving operational Key Performance Indicators (KPIs) support your business goals? Or are they considered contradictory, unrealistic or even impossible?

Are they unrealistic? How and why do unrealistic targets get created?

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, an innovative new technology developed here at PPCL, provides the way to quickly and easily see such operating envelopes across hundreds of variables. Potential KPIs and targets can immediately be evaluated and compared, and contradictions or difficulties are immediately visible. Performance monitoring and reporting become clear and consistent for everyone involved, allowing process refinement and increasing understanding of how KPIs interact.

Watch the webinar now and discover more about our fast, practical, no-math approach to extracting the information and insight buried in your process history data.

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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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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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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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This webinar was presented by Michael Bell, Principal Applications Engineer at NOVA Chemicals of Canada in September 2016. The feed preparation section at NOVA’s Ethylene 1 plant receives and combines feed from a multiple of sources while reducing the feed pressure to prepare for thermal cracking in an ethylene furnace. What is unique in modelling this process is that it has multiple modes of operation. This multi-mode problem fits well with CPM and CVE, which allow for the automatic turning off and on of variables to minimize the number of alerts sent to the panel operator by the setting of the “Phase” variable.

Geometric models are a new class of mathematical model and well-suited to plant applications because of their very low cost due to the speed with which the wholly visual nature of Geometric Process Control (GPC) allows them to be created, implemented and maintained. They have been applied to continuous and batch processes in process industry segments ranging from pharmaceuticals through chemicals to oil refining and upstream oil and gas production. 

PPCL’s mission is to reduce variability in plant operations. This starts with the gaining of better process and operations understanding using our offline product, C Visual Explorer (CVE), to view years of process operation for hundreds of variables in a single interrogable graph. This much wider view than was ever previously available considerably simplifies and accelerates traditional process applications such as process analysis, de-bottlenecking, optimisation, alarm rationalization and KPI target setting and monitoring. Operating Windows found by CVE and expressed as independent Operating Limits on process variables are immediately usable by plant operations as a guide to greater achievement of the business objective.

Operating Envelopes are modelled by our online real-time product, C Process Modeller (CPM), updating on a frequency between seconds and minutes and providing alerts to supplement alarms, guiding operations to stay inside the Operating Envelope and providing early warning of impending events, alerting the process operator to take mitigating action.

Michael offers an invaluable account of NOVA's experience with PPCL tools. The webinar includes a Q&A session with process industry professionals addressing some of the issues which commonly arise when considering and implementing the software.

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