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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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Managing alarm systems and settings are vital for the operation of every process and often a major load on operation and engineering resource. Operator alarms direct the operator to take action to react to an abnormal situation to maintain efficient production, but commonly 50% or more of these are false or unnecessary requests, dramatically increasing the load on operators and leading to distrust of all alarms. The problem arises because alarm limits are not truly independent of each other, so that it is incorrect to set them one-at-a-time in isolation as has been typically done in formal alarm rationalization.

This webinar from January 2018 demonstrates a new understanding of how alarm limits are related to process behaviour, leading to the new ability to create and manage an entire set of alarm limits together. This innovative method differentiates Modern Alarm Rationalization from the isolated alarm methods most people in the industry are still using. It generates much better alarm limits while taking less process engineering time, thereby reducing the number, duration and staffing levels of review meetings.

Plants rarely operate consistently at their minimum energy input. This is partly because the minimum is not usually known and also because it is ‘easier’ to operate with excess energy. There is an inevitable drift back to higher energy operation without ongoing monitoring and feedback as part of energy minimisation. Where should you start?

The minimum energy required is not constant. It varies with ambient conditions; operational loads on the plant; changing disturbances such as catalyst activity, furnace efficiency and equipment fouling; and unintentional local optima and sink-holes that are difficult to identify or avoid.

In this webinar we demonstrate our simple, no-maths visual method for bringing the many operational factors together which requires only the knowledge of the process and its operating practices and objectives – knowledge your senior process engineers already possess. It uses data that you already have in your plant historian and can identify operational changes to a low-energy operating window. We also discuss how to maintain low-energy operation into the future by monitoring operation against the low-energy operating window, or progressing to real-time use of an operating envelope for minute-to-minute guidance to the operator and/or existing process control systems.

Providing process operators with even a few minutes warning of approaching abnormal events such as column flooding, pump/motor failure, transformer failure, compressor surge or equipment fouling can dramatically reduce production losses. Models of normal operation are necessary. In the past these models were time consuming to create and maintain, but now there is a simple, low-cost method based on process history and understanding that can be implemented by a trained user in a matter of hours. While this method is simple, it’s far from simplistic. It can integrate more than 100 process variables over thousands of time points, achieving very high detection sensitivity.

In this webinar we demonstrate exactly how our method works and answer your questions. We look at a powerful data visualisation tool - C Visual Explorer (CVE) - and how it can be used to investigate events using historical data from the plant historian. Starting with individual occurrences and then expanding the method to multiple similar events, we demonstrate how to pinpoint common causes of faults and spot potential precursor signatures. We show how to use our online process monitoring tool - C Process Modeller (CPM) - to model fault-free operation, providing dynamic real-time warning of developing events and bringing attention to the key deviating variables.

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.

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.

This one hour webinar, first delivered by founder and CEO of PPCL Dr Robin Brooks in August 2017, explores how PPCL's innovative software products, CVE and CPM, could help YOUR process plant achieve operational excellence.

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.

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 this webinar, delivered on 17th and 18th May 2017, Alan Mahoney, PPCL's Technical Director, demonstrates GPC using graphical tools to screen for key variables and eliminate the effects of uncontrolled variables.  He shows 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.

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.

Phillips 66 talk about their experiences using CVE for Alarm Rationalization in their Bayway, NJ refinery and field questions from users and non-users of CVE. If you are new to using CVE for Alarm Rationalisation you will probably want to start with one of our own Alarm Webinars, but this one is not to be missed. 


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PPCL Webinar: Achieving Operational Excellence
28th Feb and 1st March

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