{"id":10530,"date":"2018-12-20T09:10:38","date_gmt":"2018-12-20T08:10:38","guid":{"rendered":"http:\/\/staging.blogs.yokogawa.de\/chemical-pharma\/uncategorized\/assistance-systems-3-the-signpost-the-predictor-2\/"},"modified":"2022-06-17T07:48:09","modified_gmt":"2022-06-17T05:48:09","slug":"assistance-systems-3-the-signpost-the-predictor-2","status":"publish","type":"post","link":"https:\/\/www.yokogawa.com\/eu\/blog\/chemical-pharma\/en\/assistance-systems-3-the-signpost-the-predictor-2\/","title":{"rendered":"Assistance systems 3 \u2013 The \u201csignpost\u201d &amp; the \u201cpredictor\u201d"},"content":{"rendered":"<p>In <a href=\"https:\/\/www.yokogawa.com\/eu\/blog\/chemical-pharma\/?p=7514\">Part 1<\/a> of our series we approached the subject of <strong>assistance systems in general<\/strong>, taking cars as an example. As we then showed in <a href=\"https:\/\/www.yokogawa.com\/eu\/blog\/chemical-pharma\/de\/assistenzsysteme-2-schleuderschutz\/\"><strong>Part 2 (\u201cElectronic stability control\u201d)<\/strong><\/a>, there are a number of common features and differences. However, no matter what kind of assistance system you use, it inevitably leads to an <strong>improvement<\/strong> in <strong>efficiency, safety and availability<\/strong>.<\/p>\n<p>Having talked about APC\u00a0\/\u00a0MPC in Part 2, we now want to take a look at the next assistance systems in this group:<\/p>\n<ul>\n<li><strong>APC\u00a0\/\u00a0MPC \u2013 Advanced Process Control\u00a0\/\u00a0Model (Multivariable) Predictive Control<\/strong><\/li>\n<li><strong>Digital Twin<\/strong><\/li>\n<li><strong>RTO \u2013 Real-Time Optimization<\/strong><\/li>\n<li><strong>MirrorPlant<\/strong><\/li>\n<\/ul>\n<p>In the final part of this series, we\u2019ll be turning our attention to Modular Procedural Automation and the solution it enables.<\/p>\n<h2>The dilemma<\/h2>\n<p>Plant managers and plant operators alike are regularly confronted with problems to which there is no obvious solution because they are too <strong>complex<\/strong> and \/ or too <strong>unpredictable<\/strong>. This has nothing whatsoever to do with their experience or their expertise but rather with the large number of <strong>variables<\/strong> and their possible <strong>combinations<\/strong>. One simple example would be when several simple curves are overlaid. How many of them does it take before you can\u2019t even begin to recognize the common <strong>minimum<\/strong>? Not very many at all! And it\u2019s much the same when it comes to predictability. You only need a very few variables before a reliable <strong>cause-effect assessment<\/strong> becomes extremely difficult, if not impossible.\u00a0There are two questions we need to address here:<\/p>\n<h3>How can I make it more efficient?<\/h3>\n<p><strong>Plant \/ production manager:<\/strong> My plant operators are experienced and I know we went to a lot of trouble to get our control and alarm strategy exactly right. Our functional safety, too, is bang up to date. We\u2019ve thought of absolutely everything. Nevertheless, there\u2019s something that\u2019s bugging me: although my plant operates stably and safely, I don\u2019t really have much idea how <strong>efficient<\/strong> it is.<\/p>\n<p><em>Is there an extra mile in there somewhere waiting to be squeezed out?<\/em><\/p>\n<p>Admittedly, there are an awful lot of <strong>variables<\/strong> that would need to be considered. Not just process variables but also <strong>regulatory<\/strong> and <strong>economic<\/strong> ones.\u00a0<em>Is that feasible?<\/em><\/p>\n<h3>What happens next?<\/h3>\n<p><strong>Plant operator:<\/strong>\u00a0I\u2019ve been operating this plant for years and I know it inside out. But from time to time it gets up to tricks and I can\u2019t figure out why. Even though I\u2019ve been careful not to exceed the allowable temperature step in the <strong>reactor<\/strong>, I feel like it\u2019s <strong>running away<\/strong>, or at least it\u2019s about to any minute.<\/p>\n<p><em>Some kind of \u201cearly warning system\u201d would definitely be useful in this situation.<\/em><\/p>\n<p>It would need to run parallel to the reactor <strong>in real time<\/strong> and give me an <strong>advance warning<\/strong> that something\u2019s likely to go wrong. Then I\u2019d still have <strong>plenty of time<\/strong> to react. A \u201ccrystal ball\u201d that tells the future of the process would be ideal.\u00a0<em>Does such a thing exist?<\/em><\/p>\n<h2>The solutions<\/h2>\n<h3>Digital twin<\/h3>\n<p>Let me start with a broad definition: a digital twin is basically the digital representation of \u201cobjects\u201d in the real world. It depicts them as a \u201cdigital\u201d model.\u00a0 These <strong>\u201cobjects\u201d<\/strong> could be <strong>apparatus<\/strong>, <strong>plant components<\/strong>, etc. or alternatively <strong>workflows<\/strong>, <strong>IT systems<\/strong> and so on.\u00a0Theoretically, <strong>more than a model<\/strong> could be stored in the digital twin of one and the same \u201cobject\u201d \u2013 depending on its purpose and function. It\u2019s irrelevant whether the counterpart already exists in the real world or whether it will only exist at some point in the future. The digital twin enables <strong>data and information<\/strong> to be <strong>exchanged<\/strong> between different systems or people in ways I\u2019d be reluctant to allow in the real world even if I could. Yet a digital twin is far more than just a classification yard for data. It opens up a whole series of options for us, which I\u2019d now like to outline below.<\/p>\n<p>RTO and MirrorPlant can be regarded as standalone systems.\u00a0However, if we postulate that digital twins are a kind of superset of applications, then RTO and MirrorPlant are its subsets. So if someone asks whether RTO is actually a digital twin, you can answer \u201cYes, it can be part or a function of one\u201d.<\/p>\n<h3>RTO \u2013 the \u201csignpost\u201d<\/h3>\n<p>It\u2019s time to give our <strong>plant or production manager<\/strong> a helping hand. The production planners have specified the <strong>requirements<\/strong>. The monetary values for energy, starting materials and products are on the table. All of this information is automatically transmitted to the RTO. The <strong>objective<\/strong> today is to fulfill the production plan on schedule with a minimum of costs (other objectives are likewise possible). Of course, no regulatory requirements must be violated and the <strong>condition<\/strong> of the plant must be taken into account along with the <strong>features<\/strong> of the apparatus. The RTO then starts to \u201cdo its sums\u201d and after a while (plants vary in size and complexity) comes up with a set of <strong>setpoints<\/strong>. These setpoints are automatically transferred to the PCS or entered by the plant operator, depending on whether the RTO is used in a closed loop or an open loop.\u00a0This <strong>optimization process<\/strong> can be automated (triggered) or initiated manually at intervals.<\/p>\n<p>The plant or production manager has not only succeeded in <strong>squeezing out<\/strong> that <em>\u201cextra mile<\/em>; he now also operates his plant as <strong>efficiently<\/strong> as possible.<\/p>\n<h3>How does RTO work?<\/h3>\n<p>RTO stands for <strong>real-time optimization<\/strong>; it describes a software solution that tells me how I must operate my plant (setpoints) in order to achieve a particular objective as efficiently as possible. In that respect, it\u2019s similar to the GPS device in a car. An RTO is based on a rigorous* model of my plant (or of one of its components) in process simulation software.<\/p>\n<p>The RTO uses a separate program to execute the following steps:<\/p>\n<ol>\n<li><strong>Aims and objectives<\/strong>, e.g. as defined by the production planners, are (automatically) transferred.<br \/>\n2.\u00a0<strong>Boundary conditions<\/strong> are derived from the process model, e.g. the maximum output of a pump, or stored in this model as regulatory measures, e.g. emission limits.<br \/>\n3. Rules may exist to determine which of the model\u2019s parameters are available as <strong>degrees of freedom<\/strong>.<\/li>\n<\/ol>\n<p>When the RTO is triggered, either manually or automatically, it extracts a current set of data from the real plant. It checks this data for <strong>consistency<\/strong> as well as <strong>stationarity<\/strong>. If no anomalies are found, it starts an <strong>optimization run.<\/strong>\u00a0Otherwise, the step is repeated. An optimization run may take several hours, depending on the size and complexity of the process. It is therefore advisable to conduct feasibility and benefit studies before opting for an RTO. And if you decide to install an RTO, you also have a prediction far more precise than anything an LP model could provide regarding the modus operandi for this process. As an added advantage, you can also use the results of the RTO to optimize the LP model.<\/p>\n<p>RTOs are traditionally used in two different ways: online or offline. Let\u2019s start with <strong>offline<\/strong>. The RTO model is the method of choice here for case studies, in other words I enter values and take a look at the if-then case. By varying these values, I can act out different scenarios and select one of them, which I then transfer to my plant manually. This procedure is reminiscent of the LP models that are utilized for planning. However, <strong>online<\/strong> use of RTOs \u2013 either <strong>open<\/strong> or <strong>closed loop<\/strong> \u2013 is much more common.<\/p>\n<h3><img decoding=\"async\" class=\" wp-image-7608 alignleft\" src=\"https:\/\/www.yokogawa.com\/eu\/blog\/app\/uploads\/sites\/8\/2022\/06\/Blog-RTOAPC-300x207.png\" alt=\"\" width=\"536\" height=\"370\" \/>How RTO interacts with APC\u00a0\/\u00a0MPC<\/h3>\n<p>By the way, I mentioned in my previous post that the various solutions are often used together. <strong>RTO interacting<\/strong> with <strong>APC\u00a0\/\u00a0MPC<\/strong> is a classic, for instance. On the one hand, the new setpoints supplied by the RTO can be achieved <strong>efficiently<\/strong> with the APC\u00a0\/\u00a0MPC. On the other hand, since the plant is stabilized by the APC\u00a0\/\u00a0MPC, the RTO can set setpoints closer to the <strong>plant limits<\/strong>. This results in <strong>more efficient production<\/strong> without compromising safety or availability.<\/p>\n<h3><a href=\"https:\/\/www.yokogawa.com\/solutions\/solutions\/industrial-iot\/iiot-efficiency\/iiot-mirror-plant\/\">MirrorPlant<\/a> \u2013 the \u201cpredictor\u201d<\/h3>\n<p>Remember that <strong>plant operator<\/strong> we spoke about earlier? A typical <strong>scenario with MirrorPlant<\/strong> could look like this: the operator executes the allowable temperature step, e.g. +40\u00b0C. MirrorPlant detects this <strong>change<\/strong> and then runs its model faster than real time with the new setpoint. Thirty minutes later, everything still looks fine to the plant operator but MirrorPlant has already run two hours into the <strong>future<\/strong>. The picture is not quite as good any more: the reactor is about to \u201crun away\u201d. This insight is communicated to the plant operator, who has <strong>plenty of time<\/strong> to react, for instance by reducing the temperature step and executing it in two smaller steps instead.<\/p>\n<p>The plant operator has finally got the <em>\u201cearly warning system\u201d<\/em> he was longing for and is <strong>better equipped<\/strong> for the <strong>future<\/strong>.\u00a0<img decoding=\"async\" class=\" wp-image-7613 alignright\" src=\"https:\/\/www.yokogawa.com\/eu\/blog\/app\/uploads\/sites\/8\/2022\/06\/Blog-Mirrorplant-300x191.png\" alt=\"\" width=\"451\" height=\"287\" \/><\/p>\n<h3>How does MirrorPlant work?<\/h3>\n<p>MirrorPlant is based on a rigorous*, dynamic** <strong>process model<\/strong>, which runs in <strong>real time parallel<\/strong> to the <strong>plant<\/strong>. Actual data is continuously extracted from the PCS or the PIMS, and the process model aligns itself with the plant\u2019s condition. The process model then runs <strong>faster<\/strong> than real time.\u00a0This can be visualized and the plant operator receives an advance warning. Incidentally, fouling on the heat exchanger, for example, or a reduction in catalyst performance can also be tracked by MirrorPlant in its process model, creating an accurate map of reality. MirrorPlant is currently used in <strong>online open loop<\/strong> mode. There are no plans for MirrorPlant itself to intervene actively in the control system. MirrorPlant\u2019s \u201cresults\u201d can naturally be used (in a digital twin) to trigger further actions. In the simplest case, this might be a \u201cfuture alarm\u201d.<\/p>\n<p>By the way, a <strong>process data analysis<\/strong> can provide additional support for the plant operator. This is especially helpful if it is too complicated, or not feasible, to develop a process model. The solution which is adopted is based on an <strong>evaluation<\/strong> of the <strong>values measured<\/strong> in the plant in real time.\u00a0Human beings are often unable to detect critical changes in these values, or at least not until it\u2019s too late. By contrast, PDA generally has this capability and can warn the plant operator upfront by means of a suitable alert or using a visualization system like MirrorPlant. But that\u2019s another story&#8230;<\/p>\n<h2>Benefits<\/h2>\n<p>Regardless of whether you choose RTO, MirrorPlant or any other <strong>assistance system<\/strong>, the aim is always to <strong>improve efficiency, safety and availability<\/strong>. After all, there has to be some good to come of it! And experience has shown that these systems seldom disappoint. As <strong>digitalization<\/strong> and <strong>Industry 4.0<\/strong> continue to advance, their <strong>value<\/strong> is expected to <strong>increase<\/strong> steadily. Apart from the features described here, they also offer other useful capabilities such as <strong>soft sensors<\/strong>.<\/p>\n<p><em>PDA<\/em>\u00a0Process Data Analysis<br \/>\n<em>PIMS<\/em>\u00a0Plant Information Management System<br \/>\n<em>PCS<\/em>\u00a0Process Control System<\/p>\n<p>*Rigorous means that the process model is based on physical, chemical, mechanical, etc. principles<br \/>\n**Dynamic means that, unlike stationary models, the process model also maps the time response<\/p>\n<hr \/>\n<blockquote class=\"wp-embedded-content\" data-secret=\"ESwlrCnpfG\"><p><a href=\"https:\/\/www.yokogawa.com\/eu\/blog\/chemical-pharma\/en\/automation-en\/assistance-systems-2-electronic-stability-control\/\">Assistance systems \u2013 2. Electronic stability control<\/a><\/p><\/blockquote>\n<p><iframe class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; clip: rect(1px, 1px, 1px, 1px);\" title=\"&#8220;Assistance systems \u2013 2. Electronic stability control&#8221; &#8212; Chemical Pharma Blog\" src=\"https:\/\/www.yokogawa.com\/eu\/blog\/chemical-pharma\/en\/automation-en\/assistance-systems-2-electronic-stability-control\/embed\/#?secret=vk3p6m3MqP#?secret=ESwlrCnpfG\" data-secret=\"ESwlrCnpfG\" width=\"500\" height=\"282\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe><\/p>\n<blockquote class=\"wp-embedded-content\" data-secret=\"zGGwJlTBa4\"><p><a href=\"https:\/\/www.yokogawa.com\/eu\/blog\/chemical-pharma\/en\/automation-en\/assistance-systems-1-our-little-daily-helpers\/\">Assistance systems \u2013 1. Our little daily helpers<\/a><\/p><\/blockquote>\n<p><iframe class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; clip: rect(1px, 1px, 1px, 1px);\" title=\"&#8220;Assistance systems \u2013 1. Our little daily helpers&#8221; &#8212; Chemical Pharma Blog\" src=\"https:\/\/www.yokogawa.com\/eu\/blog\/chemical-pharma\/en\/automation-en\/assistance-systems-1-our-little-daily-helpers\/embed\/#?secret=vubQTE8eoF#?secret=zGGwJlTBa4\" data-secret=\"zGGwJlTBa4\" width=\"500\" height=\"282\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe><\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Can you do that? Is there? Surely both production managers and plant operators have already asked themselves these questions. To become more concrete: You, as a production manager, have experienced plant operators and you know that you have taken good&hellip; <\/p>\n<p class=\"read-more\"> <a class=\"\" href=\"https:\/\/www.yokogawa.com\/eu\/blog\/chemical-pharma\/en\/assistance-systems-3-the-signpost-the-predictor-2\/\"> <span class=\"screen-reader-text\">Assistance systems 3 \u2013 The \u201csignpost\u201d &amp; the \u201cpredictor\u201d<\/span> Read More &raquo;<\/a><\/p>\n","protected":false},"author":125,"featured_media":2409,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"","footnotes":""},"categories":[53,56,58],"tags":[162,430,431,82,410,121,224,432,139,165,433,434,406,68,435,73,215,167,78,133],"coauthors":[],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.13 (Yoast SEO v20.13) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Assistance systems 3 \u2013 The \u201csignpost\u201d &amp; the \u201cpredictor\u201d - Chemical Pharma Blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.yokogawa.com\/eu\/blog\/chemical-pharma\/en\/assistance-systems-3-the-signpost-the-predictor-2\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Assistance systems 3 \u2013 The \u201csignpost\u201d &amp; the \u201cpredictor\u201d\" \/>\n<meta property=\"og:description\" content=\"Can you do that? 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To become more concrete: You, as a production manager, have experienced plant operators and you know that you have taken good&hellip;  Assistance systems 3 \u2013 The \u201csignpost\u201d &amp; the \u201cpredictor\u201d Read More &raquo;\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.yokogawa.com\/eu\/blog\/chemical-pharma\/en\/assistance-systems-3-the-signpost-the-predictor-2\/\" \/>\n<meta property=\"og:site_name\" content=\"Chemical Pharma Blog\" \/>\n<meta property=\"article:published_time\" content=\"2018-12-20T08:10:38+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2022-06-17T05:48:09+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.yokogawa.com\/eu\/blog\/app\/uploads\/sites\/8\/2022\/06\/Fotolia_175771326_S.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"823\" \/>\n\t<meta property=\"og:image:height\" content=\"583\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Peter Both\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.yokogawa.com\/eu\/blog\/chemical-pharma\/en\/assistance-systems-3-the-signpost-the-predictor-2\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.yokogawa.com\/eu\/blog\/chemical-pharma\/en\/assistance-systems-3-the-signpost-the-predictor-2\/\"},\"author\":{\"name\":\"Peter Both\",\"@id\":\"https:\/\/www.yokogawa.com\/eu\/blog\/chemical-pharma\/en\/#\/schema\/person\/13a6f75e9dcc8baef54e6ec281a5f04e\"},\"headline\":\"Assistance systems 3 \u2013 The \u201csignpost\u201d &amp; 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