{"id":494,"date":"2008-07-09T09:40:34","date_gmt":"2008-07-09T16:40:34","guid":{"rendered":"https:\/\/staging.opexlearning.com\/resources\/?p=494"},"modified":"2014-09-25T12:29:09","modified_gmt":"2014-09-25T17:29:09","slug":"fast-food-congestion","status":"publish","type":"post","link":"https:\/\/staging.opexlearning.com\/resources\/fast-food-congestion\/494\/","title":{"rendered":"Fast Food Congestion at a Burger Restaurant"},"content":{"rendered":"<div class=\"a296a24fa2fc69ef5487857f02f111e8\" data-index=\"9\" style=\"float: none; margin:10px 0 10px 0; text-align:center;\">\n<script async src=\"\/\/pagead2.googlesyndication.com\/pagead\/js\/adsbygoogle.js\"><\/script>\r\n<!-- Single Post readerboard -->\r\n<ins class=\"adsbygoogle\"\r\n     style=\"display:inline-block;width:728px;height:90px\"\r\n     data-ad-client=\"ca-pub-8207522353004717\"\r\n     data-ad-slot=\"1144967431\"><\/ins>\r\n<script>\r\n(adsbygoogle = window.adsbygoogle || []).push({});\r\n<\/script>\n<\/div>\n<p>Every <a title=\"how to identify a bottleneck\" href=\"https:\/\/staging.opexlearning.com\/resources\/recognizing-constraints-bottlenecks\/247\/\">system has constraints<\/a> &#8212; sometimes several &#8212; minor bottlenecks and major bottlenecks.\u00a0 What makes managing constraints even more challenging is that bottlenecks move: up-and-down the process paths.<\/p>\n<p>I saw this phenomenon recently during a visit to a fast food restaurant, which I discuss in this post &#8212; but, my application of the <a title=\"introduction to the theory of constraints\" href=\"https:\/\/staging.opexlearning.com\/resources\/the-theory-of-constraints-the-fundamentals\/2632\/\">Theory of Constraints<\/a>, Lean Manufacturing, and Six Sigma as applied to a Restaurant can be applied to <strong>any<\/strong> Dynamic System.<\/p>\n<p>One of the key lessons in The Theory of Constraints is that the constraint or the bottleneck determines the throughput for the entire system.\u00a0 This means, then, that if we optimize and improve a non-bottleneck, then those efforts have almost zero impact on the overall throughput of the system.\u00a0 It is only when we improve and optimize the contraint that we will see improvement in the throughput of the entire system.<\/p>\n<p>Every system has a constraint \u201d that is neither good nor bad \u201d but just a fact of dynamic systems.\u00a0 Once you&#8217;ve identified the constraints in your system, then the next step is to manage it.<\/p>\n<p>I was able to obtain some empirical volume data for a Burger King.\u00a0 The data below is taken from one Burger King restaurant.\u00a0 I imagine the numbers would be significantly different if we were to average the volume by geography, restaurant size, or by other factors.\u00a0 Now, consider the following process map for a typical Burger King:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter  wp-image-14956\" src=\"https:\/\/staging.opexlearning.com\/resources\/wp-content\/uploads\/2008\/07\/fast-food-congestion-and-queueing.jpg\" alt=\"fast food congestion map and where the bottlenecks are\" width=\"956\" height=\"528\" srcset=\"https:\/\/staging.opexlearning.com\/resources\/wp-content\/uploads\/2008\/07\/fast-food-congestion-and-queueing.jpg 1248w, https:\/\/staging.opexlearning.com\/resources\/wp-content\/uploads\/2008\/07\/fast-food-congestion-and-queueing-600x331.jpg 600w, https:\/\/staging.opexlearning.com\/resources\/wp-content\/uploads\/2008\/07\/fast-food-congestion-and-queueing-300x165.jpg 300w, https:\/\/staging.opexlearning.com\/resources\/wp-content\/uploads\/2008\/07\/fast-food-congestion-and-queueing-1024x565.jpg 1024w\" sizes=\"(max-width: 956px) 100vw, 956px\" \/><\/p>\n<p align=\"center\">\n<p style=\"text-align: center; font-size: 10px;\">Click on the image for a larger view.<\/p>\n<p>For this restaurant, over the course of an average month, Burger King produces 34227 sandwiches.\u00a0 This means, then, that for an average hour, Burger King produces 198 sandwiches per hour during normal hours.<\/p>\n<p>But, on Friday and at 12:00PM, Burger King experiences higher-than-normal volume and so we add a &#8220;Peak Multiplier&#8221; of 18% and 17.9% to arrive at 256 sandwiches during Peak Hours.\u00a0\u00a0 The &#8220;Peak Multiplier&#8221; is not completely arbitrary, but a quasi-educated guess at the volume increase during those hours.\u00a0 In both cases of Fridays and Lunch Hours, we add a ~20% multiplier.<\/p>\n<p>Now, let&#8217;s take a look at the process map above.\u00a0 We see the Assembly Step producing 200 sandwiches an hour.\u00a0\u00a0 We consider the Assembly to be the constraint in the system.\u00a0 The upstream processes produces more than 200, but when we arrive at the Assembly, the capacity of that step is lower than its upstream processes.\u00a0 So, the maximum throughput of the entire system above is 200 sandwiches per hour.<\/p>\n<p>Under normal hours, the constraint functions reasonably well.\u00a0 Since normal hour demand is 198 sandwiches per normal hour, the Assembly Step can produce at least at that amount \u201d but, it&#8217;s cutting it close.\u00a0 Under peak volume, the constraint is not able to fulfill demand.<\/p>\n<h2>How To Manage a Constraint<\/h2>\n<p>Under normal hours, it appears that the Assembly Step can produce at expected demand.\u00a0 But, there are several things that could put burden on the constraint and cause it to producing less than capacity.\u00a0 Here are some of those items:<\/p>\n<ul>\n<li><strong>Rework<\/strong>: Having to Re-Assemble sandwiches adds undue burden on the system and exaggerates the effects of the constraint, leading to a potentially higher-than normal work-in-process, or build-up.<\/li>\n<li><strong>Set-up &amp; Changeover<\/strong>: If all the parts aren&#8217;t immediately available in the Assembly step, then it could lead the operator to slow down which could lead to build-up and higher-than-normal work-in-process.<\/li>\n<\/ul>\n<p>It&#8217;s easy enough to see that the Assembly Step needs some help.\u00a0\u00a0 Here are several things Burger King \u201d or any system with constraints \u201d can do to better manage the natural constraints that are in every system:<\/p>\n<ul>\n<li><strong>Eliminate Defects at the Constraint<\/strong>: This means that all <a href=\"https:\/\/staging.opexlearning.com\/resources\/process-cycle-efficiency-pce\/330\/\">waste is eliminated<\/a> or reduced at the constraint.<\/li>\n<li><strong>Have the Quality Steps in Front of Constraint<\/strong>: In support of the first bullet, make sure that the parts entering the Assembly step are free of defects.<\/li>\n<li><strong>Support the Constraint<\/strong>: Add labor to the constraint or more lines, if that is prudent.<\/li>\n<li><strong>Appropriately use Buffers<\/strong>: Systems with Constraints exhibit a feast\/famine phenomena.\u00a0 To avoid having too much coming into the constraint or too little coming into the constraint, have a buffer of parts large enough that the constraint stays appropriately busy.\u00a0 Put another way, reduce the <a href=\"https:\/\/staging.opexlearning.com\/resources\/variation-for-dummies\/289\/\">variation in front of the constraint<\/a> as much as is possible.\u00a0 A <a href=\"https:\/\/staging.opexlearning.com\/resources\/shmula-goes-camping-drum-buffer-rope\/138\/\">Drum-Buffer-Rope<\/a> system might be appropriate for some systems.<\/li>\n<li><strong>Evaluate the overall system<\/strong>: How much of the steps in the system are really value-add to the customer?\u00a0 What is the <a href=\"https:\/\/staging.opexlearning.com\/resources\/process-cycle-efficiency-pce\/330\/\">process-cycle effeciency<\/a> of the process?<\/li>\n<\/ul>\n<h2>Conclusion<\/h2>\n<p>All systems have constraints.\u00a0 Identify what they are, quantify the effects, then manage it.\u00a0 The above Burger King example shows how this can &#8212; with some effort &#8212; be done.\u00a0 What are the constraints in your systems?\u00a0 What can you do to better manage those constraints?<\/p>\n<!--CusAds0-->\n<div style=\"font-size: 0px; height: 0px; line-height: 0px; margin: 0; padding: 0; clear: both;\"><\/div>","protected":false},"excerpt":{"rendered":"<p>Every system has constraints &#8212; sometimes several &#8212; minor bottlenecks and major bottlenecks.\u00a0 What makes managing constraints even more challenging is that bottlenecks move: up-and-down the process paths. I saw this phenomenon recently during a visit to a fast food restaurant, which I discuss in this post &#8212; but, my application of the Theory of [&hellip;]<\/p>\n","protected":false},"author":12327,"featured_media":9820,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","footnotes":""},"categories":[9],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.0 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Fast Food Congestion<\/title>\n<meta name=\"description\" content=\"Fast Food Congestion is common in dynamic systems. 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