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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Downtime and degraded production from process disturbances are major costs to the process industry. How can we understand these events and implement the changes needed to reduce their impact? Can we provide operators with early warning of developing abnormal process conditions giving them the precious time needed to understand and respond to disturbances before they grow to threaten shutdown or lost production?

In this webinar from March 2020, we present simple visual methods for analyzing large historical datasets and producing real-time event prediction and fault detection models based on process history which can be implemented by the engineer without the need for advanced mathematics. Building models is fast and easy compared with traditional condition monitoring and fault detection frameworks.

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Operator alarms are the key to improving value from your plant by increasing uptime and reducing operational variability. Better alarms drive the operator’s capability to keep the plant on-line and producing saleable material. Poor alarm systems distract the operator, cause overload in responses or, at worst, don’t prompt at all for necessary actions.

The single biggest factor in improving 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 useless because there hasn’t been a way to locate this 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 delivered in February 2020, you will discover a simple visual method for 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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Operational Excellence depends on feedback of lagging KPI (Key Performance Indicator) achievement to ensure business performance meets required financial, environmental and efficiency requirements. Feedback on achieved KPI values against the KPI targets is via infrequent performance reports and ‘dashboards’. These may indicate the existence of a problem but rarely indicate the cause - and no guidance is available to the process operator as to how to address the lagging KPIs and manage the interactions between them.

The solution for effective Operational Excellence is to use an Operating Envelope model which includes variable interaction effects. 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.

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The key to repeating best operation is understanding your process behavior. This is necessary to achieve higher throughput, lower costs, least waste and minimum downtime. While some of this is known in the process design, much of what is taken as true about your process is likely wrong or contradictory. The resolution to these conflicts and a true process picture are already present implicitly in your plant historian, built from years of experience. This webinar, given by Dr Alan Mahoney in December 2019, will demonstrate PPCL's unique visual tools which engineers can use to extract and exploit the wealth of information available.

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Geometric Process Control (GPC) is a technology developed here at PPCL. It lets you see hundreds of process variables and tens of thousands of observations from process and other plant data in a single parallel coordinates graph with supplemental time-trends, distribution plots, and Pareto plots with every individual point traceable through all the views. It comes with an extremely powerful graphical Boolean query capability that lets you extract feed-to-product operating windows and operating envelopes to help you explain why yesterday was such a great day for your KPIs and what went wrong last week when the fractionator column flooded five times.

Why is this important? Well, it lets you benefit from a few hundred thousand years of evolution and use your amazing human powers of pattern recognition and interpretation to determine cause-and-effect relationships – as well as correlations - in multi-variable problems where previously you had fewer than 10 variables to work with. You also would have needed some heavy-duty mathematics, which requires first an expensive statistician and then a hypothesis to test and which tends to introduce new complications when trying to explain your results to others.

Having determined your best operating envelope from process history, GPC creates a real-time model complete with graphical operator interface for process operator guidance and an OPC Client to link to your DCS or historian to keep your process operating in the best operating envelope you have chosen far into the future.

Watch this webinar from September 2019 to discover how GPC unifies process control, quality control, KPI achievement, operating limits and operator alarms into one readily understandable framework. A huge step forward for chemical engineering and you won’t need more than basic maths!

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Wouldn’t you rather have a process that is easier to operate and needs less attention and intervention? Just turn up the temperature, increase recycle or reflux and allow grinding to continue for longer and your wish will be granted - but at the cost of expensive additional fuel. Fuel is the directly visible cost of excess energy, but it’s not the whole cost. Additional cooling is needed to remove the excess energy, throughput is reduced due to higher recycle and reflux, and extra downstream processing is needed. What’s more, carbon credits or environmental permits may also be needed.

In this webinar from August 2019 we show you how to make your process easier to operate without increasing your energy usage. Once you know how the plant should be operated it is easy to compare that with how it is being operated now and calculate the cost difference. For most companies the difference lies somewhere between “large” and “very large”.

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Process plant control systems capture measurements of thousands of variables as often as every few seconds. These add to a continuously lengthening time-series for each measurement which began when the plant was first started. This data has enormous potential, which is largely untapped by the conventional analysis tools available to most process and control engineers. Fashionable “Big Data” approaches are challenged by process plant data and have limited application for busy engineers since many of the assumptions and simplifications destroy the richness of process data. Geometric Process Control (GPC) – a technology unique to us here at PPCL – avoids these pitfalls and provides engineers with graphical tools to work with datasets spanning their entire plant and create low-cost, equation-free predictive models to develop new process understanding quickly and easily.

This webinar, presented by Dr Alan Mahoney in May 2019, demonstrates our unique approach to analysis on a process with a medium size dataset spanning the process from feed to product, 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 explore their data fully and make discoveries that they couldn’t before. We also cover process stewardship, using your discoveries to achieve quality targets and operational excellence long into the future.

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All processes are multi-step, but many where the producing step is much longer than the start-up and shut-down steps have long been characterized as ‘continuous’, leaving all others to be put into categories such as ‘batch’, ‘cyclic’, ‘fed-batch’ and ‘transition’. In reality, all processes are multi-step, which means there are almost always different operating envelopes for each step. The envelopes for successive steps wholly or partially overlap with each other in high-dimensionality space and can now be examined and modelled to achieve both single and multi-step performance monitoring, optimization, operator alarm-setting and process improvement using the same no-maths Geometric Process Control tools which we demonstrated in last month’s webinar on continuous process optimization.

In this webinar you will see modelling of operating envelopes for a multi-step, multi-variable environment (a stirred-tank reactor with distillation and thus several very different operating phases) and for an oil well drilling example. There is a discussion-led review of other frequently-encountered applications, such as grade transition in polymer manufacturing.

The webinar is delivered by our CEO Dr Robin Brooks and, while of primary interest to process and control engineers, is fully within the comprehension of managers and other staff remote from real-time process operations who may have the task of creating business cases justifying future investment.

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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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