{"id":14591,"date":"2021-08-13T10:00:23","date_gmt":"2021-08-13T08:00:23","guid":{"rendered":"https:\/\/www.tradecloud1.com\/?p=14591"},"modified":"2021-08-13T16:29:11","modified_gmt":"2021-08-13T14:29:11","slug":"ai-case-study-3-cost-saving-ai-in-manufacturing-logistics","status":"publish","type":"post","link":"https:\/\/tradecloud.hdnk.nl\/en\/ai-case-study-3-cost-saving-ai-in-manufacturing-logistics\/","title":{"rendered":"AI case study 3:  Cost-saving AI in Manufacturing Logistics"},"content":{"rendered":"<div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-1 fusion-flex-container nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-padding-right:0px;--awb-padding-right-small:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1216.8px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-0 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-title title fusion-title-1 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:#0073bd;--awb-margin-bottom:10px;--awb-margin-top-small:0px;--awb-margin-right-small:0px;--awb-margin-bottom-small:20px;--awb-margin-left-small:0px;--awb-font-size:24px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:24;line-height:2.08;\"><b><br \/>\nThe Business Problem<br \/>\n<\/b><\/h2><\/div><div class=\"fusion-text fusion-text-1\"><p>In the world of logistics, <strong><u>empty fleet management<\/u><\/strong> cannot be overlooked. For container shipping, the Boston Consulting Group estimates that up to 8% of a shipping line&#8217;s operating costs relate to the repositioning of empty containers &#8211; without the associated costs of empty container storage and maintenance (BCG, 2015). The situation is not very different for road transportation: improper empty fleet management can create surpluses in one area and shortages in another, leading to lost revenues and increased costs.<\/p>\n<p>Among logistics companies, two common factors stand out that further compound the issue of empty container management:<\/p>\n<ul>\n<li>Using Excel for planning, inefficient in part due to high amounts of manual input (Supply Chain Dive, 2018)<\/li>\n<li>Lacking visibility on costs, due to the lack of a company-wide cost overview system<\/li>\n<\/ul>\n<\/div><div class=\"fusion-title title fusion-title-2 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:#0073bd;--awb-margin-top:30px;--awb-margin-bottom:10px;--awb-margin-top-small:0px;--awb-margin-right-small:0px;--awb-margin-bottom-small:20px;--awb-margin-left-small:0px;--awb-font-size:24px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:24;line-height:2.08;\"><b>The Solution<\/b><\/h2><\/div><div class=\"fusion-text fusion-text-2\"><p><strong>NileDutch<\/strong> and <strong>TIP Trailer Services<\/strong> are two Dutch logistics players that turned to AI solutions to improve their empty fleet management. Though the first one operates on sea and the latter on land, the two companies share similarities both in overall fleet sizes and in the problems that unused assets can create for them. The key to reducing costs associated with unused assets also lies in the same place: improving the companies&#8217; forecasting abilities, while being able to more efficiently reposition their empty fleet. Using historical data &#8211; mostly proprietary &#8211; to feed into machine learning algorithms, the companies were able to develop tailor-made solutions to reduce costs associated with empty fleet management.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-3 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:#0073bd;--awb-margin-top:30px;--awb-margin-bottom:10px;--awb-margin-top-small:0px;--awb-margin-right-small:0px;--awb-margin-bottom-small:20px;--awb-margin-left-small:0px;--awb-font-size:24px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:24;line-height:2.08;\"><b>Benefits<\/b><\/h2><\/div><div class=\"fusion-text fusion-text-3\"><p>A tailor-made Artificial Intelligence system can help logistics companies plan better, leading to less congestions and more efficient use of their assets. This has led to:<\/p>\n<ul>\n<li><strong>More efficient planning: <\/strong>moving away from time-intensive manual planning using Excel, the companies are able to create automatic plans that are also more accurate due to the implementation of AI. This alleviates congestion both physically, in asset repositioning, but also organizationally, freeing up employee time.<\/li>\n<li><strong>Decrease in storage costs<\/strong>: the AI-powered planning tool is able to better predict when and where certain assets are required. Therefore, the companies&#8217; containers and trailers ended up spending less time in storage facilities.<\/li>\n<li><strong>Increased transparency across departments<\/strong>: since the companies are now working with consolidated information available to all offices across global supply chains, more informed decisions can be taken by all employees.<\/li>\n<\/ul>\n<\/div><div class=\"fusion-title title fusion-title-4 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:#0073bd;--awb-margin-top:30px;--awb-margin-bottom:10px;--awb-margin-top-small:0px;--awb-margin-right-small:0px;--awb-margin-bottom-small:20px;--awb-margin-left-small:0px;--awb-font-size:24px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:24;line-height:2.08;\"><b>Impact<\/b><\/h2><\/div><div class=\"fusion-text fusion-text-4\"><p>In the case of <strong>NileDutch<\/strong>, the AI solution is able to calculate an optimized empty container plan <strong>10 to 12 weeks in advance<\/strong>, being able to identify how to avoid container surplus and the most efficient routes to reposition its fleet. The company was also able to reduce its fleet size: the AI-powered planning allowed the company to satisfy the same demand with less assets.<\/p>\n<p>For <strong>TIP<\/strong>, a similar system is able to provide <strong>95% demand accuracy 6 weeks ahead of time<\/strong>. On a two-week basis, the accuracy is up to 98%. This has allowed the company to service one-way rentals to its clients, thanks to its optimized and flexible planning. With the implementation of the AI system, the company expects an <strong>11% increase in revenue<\/strong>.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-5 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:#0073bd;--awb-margin-top:30px;--awb-margin-bottom:10px;--awb-margin-top-small:0px;--awb-margin-right-small:0px;--awb-margin-bottom-small:20px;--awb-margin-left-small:0px;--awb-font-size:24px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:24;line-height:2.08;\"><b>Accessibility and Requirements<\/b><\/h2><\/div><div class=\"fusion-text fusion-text-5\"><p>In order to build and train the AI optimization system, companies first need to obtain the necessary data. While historical data was available, a multi-step approach was necessary in order to transform the data coming in from various EDIs into one, usable set.<\/p>\n<p>After cleaning the historical data, it was fed into machine learning algorithms in order to create a demand forecasting model, helping the companies identify how many assets would be required at a given time at a given place.<\/p>\n<p>Both example companies lacked the full data requirements to build this model, but this was not a problem: the model was further created with data from third-party global logistics actors, such as port authorities, storage partners, or freight exchange partners, in order to create the optimal routes to reposition and store their assets. NileDutch used a combination of internal and external data to feed into a ML algorithm:<\/p>\n<ul>\n<li>Storage costs<\/li>\n<li>Gate costs<\/li>\n<li>Repair costs<\/li>\n<li>Repositioning costs<\/li>\n<li>Suppliers<\/li>\n<li>Countries<\/li>\n<li>Ports<\/li>\n<li>Depots<\/li>\n<li>Safety stock<\/li>\n<li>And others: stevedoring costs, grading costs, outports, voyages, etc.<\/li>\n<\/ul>\n<p>Taking all of this information and creating a usable plan for a major shipping company would be an impossible task using manual inputs in Excel. For an AI system, it is simply a matter of feeding the data and using the outputs &#8211; not to mention the ever-learning and improving aspect of the system that comes with gathering more data as it&#8217;s being deployed and over the years.<\/p>\n<\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-2 fusion-flex-container nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-margin-top:40px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1216.8px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-1 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-padding-top:31px;--awb-padding-left:76px;--awb-bg-color:#f7f7f7;--awb-bg-color-hover:#f7f7f7;--awb-bg-size:cover;--awb-border-color:#0071bd;--awb-border-top:0;--awb-border-right:0;--awb-border-bottom:0;--awb-border-left:5px;--awb-border-style:solid;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-title title fusion-title-6 fusion-sep-none fusion-title-text fusion-title-size-three\" style=\"--awb-margin-top-small:0px;--awb-margin-right-small:0px;--awb-margin-bottom-small:20px;--awb-margin-left-small:0px;--awb-font-size:22px;\"><h3 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:22;--minFontSize:22;line-height:2.5;\">Want to know more what AI can do for your supply chain?<br \/>\n<a href=\"https:\/\/tradecloud.hdnk.nl\/en\/contact\/\"><span style=\"color: #0073bd;\"><b>Contact us.<\/b><\/span><\/a><\/h3><\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-3 fusion-flex-container nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1216.8px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-2 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-title title fusion-title-7 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:#0073bd;--awb-margin-top:30px;--awb-margin-top-small:0px;--awb-margin-right-small:0px;--awb-margin-bottom-small:20px;--awb-margin-left-small:0px;--awb-font-size:24px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:24;line-height:2.08;\"><b>More AI Case Studies:<\/b><\/h2><\/div><div class=\"fusion-recent-posts fusion-recent-posts-1 avada-container layout-default layout-columns-2\"><section class=\"fusion-columns columns fusion-columns-2 columns-2\"><article class=\"post fusion-column column col col-lg-6 col-md-6 col-sm-6\"><div class=\"fusion-flexslider fusion-flexslider-loading flexslider flexslider-hover-type-zoomin\"><ul class=\"slides\"><li><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/ai-case-study-5-workflow-automation-with-tradecloud-one\/\" aria-label=\"AI case study 5: Workflow automation with TradeCloud One\" class=\"hover-type-zoomin\"><img fetchpriority=\"high\" decoding=\"async\" width=\"700\" height=\"441\" src=\"https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-700x441.png\" class=\"attachment-recent-posts size-recent-posts\" alt=\"\" srcset=\"https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-320x202.png 320w, https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-700x441.png 700w\" sizes=\"(max-width: 700px) 100vw, 700px\" \/><\/a><\/li><\/ul><\/div><div class=\"recent-posts-content\"><span class=\"vcard\" style=\"display: none;\"><span class=\"fn\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/author\/olyyaa-shulgagmail-com\/\" title=\"Posts by Tradecloud Marketing Team\" rel=\"author\">Tradecloud Marketing Team<\/a><\/span><\/span><span class=\"updated\" style=\"display:none;\">2023-07-14T14:49:28+02:00<\/span><h4 class=\"entry-title\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/ai-case-study-5-workflow-automation-with-tradecloud-one\/\">AI case study 5: Workflow automation with TradeCloud One<\/a><\/h4><p class=\"meta\"><span class=\"vcard\" style=\"display: none;\"><span class=\"fn\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/author\/olyyaa-shulgagmail-com\/\" title=\"Posts by Tradecloud Marketing Team\" rel=\"author\">Tradecloud Marketing Team<\/a><\/span><\/span><span class=\"updated\" style=\"display:none;\">2023-07-14T14:49:28+02:00<\/span><\/p><p> The Business Problem  In this business case, AI workflow automation will be exemplified using the example of a TradeCloud client. The client is a manufacturer of machines for the sorting of eggs and [...]<\/p><\/div><\/article><article class=\"post fusion-column column col col-lg-6 col-md-6 col-sm-6\"><div class=\"fusion-flexslider fusion-flexslider-loading flexslider flexslider-hover-type-zoomin\"><ul class=\"slides\"><li><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/ai-case-study-4-machine-learning-in-the-manufacturing-process\/\" aria-label=\"AI case study 4: Machine Learning in the Manufacturing Process\" class=\"hover-type-zoomin\"><img fetchpriority=\"high\" decoding=\"async\" width=\"700\" height=\"441\" src=\"https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-700x441.png\" class=\"attachment-recent-posts size-recent-posts\" alt=\"\" srcset=\"https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-320x202.png 320w, https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-700x441.png 700w\" sizes=\"(max-width: 700px) 100vw, 700px\" \/><\/a><\/li><\/ul><\/div><div class=\"recent-posts-content\"><span class=\"vcard\" style=\"display: none;\"><span class=\"fn\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/author\/olyyaa-shulgagmail-com\/\" title=\"Posts by Tradecloud Marketing Team\" rel=\"author\">Tradecloud Marketing Team<\/a><\/span><\/span><span class=\"updated\" style=\"display:none;\">2021-09-06T00:16:16+02:00<\/span><h4 class=\"entry-title\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/ai-case-study-4-machine-learning-in-the-manufacturing-process\/\">AI case study 4: Machine Learning in the Manufacturing Process<\/a><\/h4><p class=\"meta\"><span class=\"vcard\" style=\"display: none;\"><span class=\"fn\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/author\/olyyaa-shulgagmail-com\/\" title=\"Posts by Tradecloud Marketing Team\" rel=\"author\">Tradecloud Marketing Team<\/a><\/span><\/span><span class=\"updated\" style=\"display:none;\">2021-09-06T00:16:16+02:00<\/span><\/p><p> The Business Problem  The manufacturing process of memory chips involves around 1,500 steps that need to be performed in sterile conditions to avoid specks of dust from damaging the wafers. However, damages occur [...]<\/p><\/div><\/article><article class=\"post fusion-column column col col-lg-6 col-md-6 col-sm-6\"><div class=\"fusion-flexslider fusion-flexslider-loading flexslider flexslider-hover-type-zoomin\"><ul class=\"slides\"><li><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/ai-case-study-3-cost-saving-ai-in-manufacturing-logistics\/\" aria-label=\"AI case study 3: Cost-saving AI in Manufacturing Logistics\" class=\"hover-type-zoomin\"><img fetchpriority=\"high\" decoding=\"async\" width=\"700\" height=\"441\" src=\"https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-700x441.png\" class=\"attachment-recent-posts size-recent-posts\" alt=\"\" srcset=\"https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-320x202.png 320w, https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-700x441.png 700w\" sizes=\"(max-width: 700px) 100vw, 700px\" \/><\/a><\/li><\/ul><\/div><div class=\"recent-posts-content\"><span class=\"vcard\" style=\"display: none;\"><span class=\"fn\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/author\/olyyaa-shulgagmail-com\/\" title=\"Posts by Tradecloud Marketing Team\" rel=\"author\">Tradecloud Marketing Team<\/a><\/span><\/span><span class=\"updated\" style=\"display:none;\">2021-08-13T16:29:11+02:00<\/span><h4 class=\"entry-title\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/ai-case-study-3-cost-saving-ai-in-manufacturing-logistics\/\">AI case study 3:  Cost-saving AI in Manufacturing Logistics<\/a><\/h4><p class=\"meta\"><span class=\"vcard\" style=\"display: none;\"><span class=\"fn\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/author\/olyyaa-shulgagmail-com\/\" title=\"Posts by Tradecloud Marketing Team\" rel=\"author\">Tradecloud Marketing Team<\/a><\/span><\/span><span class=\"updated\" style=\"display:none;\">2021-08-13T16:29:11+02:00<\/span><\/p><p> The Business Problem  In the world of logistics, empty fleet management cannot be overlooked. For container shipping, the Boston Consulting Group estimates that up to 8% of a shipping line's operating costs relate [...]<\/p><\/div><\/article><article class=\"post fusion-column column col col-lg-6 col-md-6 col-sm-6\"><div class=\"fusion-flexslider fusion-flexslider-loading flexslider flexslider-hover-type-zoomin\"><ul class=\"slides\"><li><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/ai-case-study-2-efficient-inventory-management-using-artificial-intelligence\/\" aria-label=\"AI case study 2: Efficient inventory management using Artificial Intelligence\" class=\"hover-type-zoomin\"><img fetchpriority=\"high\" decoding=\"async\" width=\"700\" height=\"441\" src=\"https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-700x441.png\" class=\"attachment-recent-posts size-recent-posts\" alt=\"\" srcset=\"https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-320x202.png 320w, https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-700x441.png 700w\" sizes=\"(max-width: 700px) 100vw, 700px\" \/><\/a><\/li><\/ul><\/div><div class=\"recent-posts-content\"><span class=\"vcard\" style=\"display: none;\"><span class=\"fn\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/author\/olyyaa-shulgagmail-com\/\" title=\"Posts by Tradecloud Marketing Team\" rel=\"author\">Tradecloud Marketing Team<\/a><\/span><\/span><span class=\"updated\" style=\"display:none;\">2021-07-15T19:16:23+02:00<\/span><h4 class=\"entry-title\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/ai-case-study-2-efficient-inventory-management-using-artificial-intelligence\/\">AI case study 2:  Efficient inventory management using Artificial Intelligence<\/a><\/h4><p class=\"meta\"><span class=\"vcard\" style=\"display: none;\"><span class=\"fn\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/author\/olyyaa-shulgagmail-com\/\" title=\"Posts by Tradecloud Marketing Team\" rel=\"author\">Tradecloud Marketing Team<\/a><\/span><\/span><span class=\"updated\" style=\"display:none;\">2021-07-15T19:16:23+02:00<\/span><\/p><p> The Business Problem  A major challenge for manufacturing companies is to know what, when, where and how much stock should be ordered and kept. SME\u2019s traditionally calculate this manually using Excel, Google Sheets [...]<\/p><\/div><\/article><article class=\"post fusion-column column col col-lg-6 col-md-6 col-sm-6\"><div class=\"fusion-flexslider fusion-flexslider-loading flexslider flexslider-hover-type-zoomin\"><ul class=\"slides\"><li><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/ai-case-study-1-demand-forecasting-using-artificial-intelligence\/\" aria-label=\"AI case study 1: Demand Forecasting using Artificial Intelligence\" class=\"hover-type-zoomin\"><img fetchpriority=\"high\" decoding=\"async\" width=\"700\" height=\"441\" src=\"https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-700x441.png\" class=\"attachment-recent-posts size-recent-posts\" alt=\"\" srcset=\"https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-320x202.png 320w, https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1-700x441.png 700w\" sizes=\"(max-width: 700px) 100vw, 700px\" \/><\/a><\/li><\/ul><\/div><div class=\"recent-posts-content\"><span class=\"vcard\" style=\"display: none;\"><span class=\"fn\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/author\/olyyaa-shulgagmail-com\/\" title=\"Posts by Tradecloud Marketing Team\" rel=\"author\">Tradecloud Marketing Team<\/a><\/span><\/span><span class=\"updated\" style=\"display:none;\">2021-07-15T19:39:28+02:00<\/span><h4 class=\"entry-title\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/ai-case-study-1-demand-forecasting-using-artificial-intelligence\/\">AI case study 1:  Demand Forecasting using Artificial Intelligence<\/a><\/h4><p class=\"meta\"><span class=\"vcard\" style=\"display: none;\"><span class=\"fn\"><a href=\"https:\/\/tradecloud.hdnk.nl\/en\/author\/olyyaa-shulgagmail-com\/\" title=\"Posts by Tradecloud Marketing Team\" rel=\"author\">Tradecloud Marketing Team<\/a><\/span><\/span><span class=\"updated\" style=\"display:none;\">2021-07-15T19:39:28+02:00<\/span><\/p><p> The Business Problem One of the biggest challenges for business executives today is demand volatility in relation to demand forecasting. Whereas data availability continues to increase, customer purchase patterns are becoming increasingly complex, and [...]<\/p><\/div><\/article><\/section><\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-4 fusion-flex-container nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-padding-top:40px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1216.8px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-3 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-padding-top:42px;--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-title title fusion-title-8 fusion-sep-none fusion-title-text fusion-title-size-three\" style=\"--awb-text-color:#191919;--awb-margin-top:30px;--awb-margin-bottom:10px;--awb-margin-top-small:0px;--awb-margin-right-small:0px;--awb-margin-bottom-small:20px;--awb-margin-left-small:0px;--awb-font-size:16px;\"><h3 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:16;--minFontSize:16;line-height:2.5;\">Bibliography<\/h3><\/div><div class=\"fusion-text fusion-text-6\"><p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/www.altexsoft.com\/blog\/demand-forecasting-methods-using-machine-learning\/\">Alexsoft. (2019, November 11). Demand Forecasting Methods: Using Machine Learning and Predictive Analytics to See the Future of Sales. Retrieved April 6, 2021, from Alexsoft<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/www.ibm.com\/blogs\/internet-of-things\/iot-cheat-sheet-digital-twin\/\">Armstrong, M. M. (2020, December 4). Cheat sheet: What is Digital Twin? Retrieved April 21, 2021, from ibm.com<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/www.bcg.com\/publications\/2015\/transportation-travel-logistics-think-outside-your-boxes-solving-global-container-repositioning-puzzle\">BCG. (2015, November 17). Think Outside Your Boxes: Solving the Global Container-Repositioning Puzzle . Retrieved from Boston Consulting Group<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/www.bestpractice.ai\/studies\/danone_reduces_forecast_error_and_lost_sales_by_20_and_30_percent_respectively_and_achieves_a_10_point_roi_improvement_in_promotions_with_machine_learning#\">Best Practice AI. (n.d.). Danone reduces forecast error and lost sales by 20 and 30 percent respectively and achieve a 10 point ROI improvement in promotions with machine learning. Retrieved April 6, 2021, from Bestpractice<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/www.capgemini.com\/research\/scaling-ai-in-manufacturing-operations\/\">Brosset, P., Patsko, S., Khadikar, A., Thieullent, A., Buvat, J., Khemka, Y., &amp; Jain, A. (n.d.). Scaling AI in Manufacturing Operations. Retrieved April 06, 2021, from Capgemini<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/blogs.nvidia.com\/blog\/2009\/12\/16\/whats-the-difference-between-a-cpu-and-a-gpu\/\">Caulfield, B. (2019, December 16). What\u2019s the Difference Between a CPU and a GPU? Retrieved April 22, 2021, from nvidia.com<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/research.aimultiple.com\/demand-forecasting\/#:~:text=unexpected%20demand%20fluctuations.-,AI%20in%20Demand%20Forecasting,decrease%20around%2010%20to%2040%25\">Dilmegani, C. (2021, January 7). Demand forecasting in the age of AI &amp; machine learning [2021]. Retrieved April 6, 2021, from AImultiple<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/news.europawire.eu\/shipment-planning-and-inventory-management-improved-with-ai-and-big-data-on-kuehne-nagels-new-version-of-seaexplorer\/eu-press-release\/2020\/04\/15\/10\/09\/18\/79328\/\">Europawire. (2020, April 15). Shipment planning and inventory management improved with AI and big data on Kuehne + Nagel\u2019s new version of SeaExplorer. Retrieved from Europawire<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/towardsdatascience.com\/detecting-sounds-with-deep-learning-ed9a41909da0\">Hyeongchan, K. (2020, December 16). Detecting Sounds with Deep Learning. Retrieved April 21, 2021, from towardsdatascience.com<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/inoxoft.com\/how-to-improve-inventory-management-using-ai\/\">Kvartalnyi, N. (2021, May 11). 6 TIPS OF HOW TO IMPROVE INVENTORY MANAGEMENT USING ARTIFICIAL INTELLIGENCE. Retrieved from Inoxoft<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/synlabs.io\/704-2\/\">Majumdar, D. (n.d.). Case Study-How SynergyLabs AI solutions Brought Efficiency in warehouse Inventory management. Retrieved April 19, 2021, from Synlabs<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/sg.micron.com\/insight\/micron-uses-data-and-artificial-intelligence-to-see-hear-and-feel\">Micron Technology. (2021). Case Study: Micron Uses Data and Artificial Intelligence to See, Hear and Feel. Retrieved April 21, 2021, from sg.micron.com<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/towardsdatascience.com\/what-is-deep-learning-and-how-does-it-work-2ce44bb692ac\">Opperman, A. (2019, November 19). What is Deep Learning and How does it work? Retrieved April 21, 2021, from towardsdatascience.com<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/www.n-ix.com\/automation-warehouse-inventory-management\/\">Serheichuk, N. (2020, December 15). Inventory management automation: How you can benefit from it. Retrieved from N-ix<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/blogs.gartner.com\/jitendra-subramanyam\/prediction-models-traditional-versus-machine-learning\/#:~:text=In%20traditional%20approaches%2C%20the%20parameter,for%20transforming%20inputs%20into%20outputs\">Subramanyam, J. (2019, July 8). Prediction Models: Traditional versus Machine Learning. Retrieved May 20, 2021, from Gartner.com<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/www.supplychain247.com\/article\/coca_cola_leverages_ai_for_inventory_management\">Supply Chain 247. (2017, March 28). Coca-Cola Leverages AI for Inventory Management. Retrieved from SupplyChain247<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/www.supplychaindive.com\/news\/supply-chain-innovation-survey-BluJay-AdelanteSCM\/530263\/\">Supply Chain Dive. (2018, August 17). Two-thirds of companies consider Excel a supply chain system. Retrieved from Supply Chain Dive<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/www.symphonyretailai.com\/supply-chain\/demand-forecasting-ai\/\">Symphony Retail. (n.d.). demand forecasting ai. Retrieved April 06, 2021, from symphonyretail<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/www.tradegecko.com\/inventory-management\">TradeGecko. (2019, December 4). What is inventory management? Retrieved from tradegecko<\/a><\/p>\n<p style=\"font-size: 12px; line-height: 22px;\" data-fusion-font=\"true\"><a href=\"https:\/\/www.intel.com\/content\/dam\/www\/public\/us\/en\/documents\/best-practices\/faster-more-accurate-defect-classification-using-machine-vision-paper.pdf\" target=\"_blank\" rel=\"noopener noreferrer\">Tuv, E., Murat, G., Enis, P., &amp; Lee, D. H. (2018, November). Faster, More Accurate Defect Classification Using Machine Vision. Retrieved April 21, 2021, from Intel.com<\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":10,"featured_media":14407,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8696],"tags":[8707,2752],"class_list":["post-14591","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","tag-ai-case-study","tag-artificial-intelligence"],"jetpack_featured_media_url":"https:\/\/tradecloud.hdnk.nl\/wp-content\/uploads\/2021\/06\/tradecloud-ai-forecast-1.png","_links":{"self":[{"href":"https:\/\/tradecloud.hdnk.nl\/en\/wp-json\/wp\/v2\/posts\/14591","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/tradecloud.hdnk.nl\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/tradecloud.hdnk.nl\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/tradecloud.hdnk.nl\/en\/wp-json\/wp\/v2\/users\/10"}],"replies":[{"embeddable":true,"href":"https:\/\/tradecloud.hdnk.nl\/en\/wp-json\/wp\/v2\/comments?post=14591"}],"version-history":[{"count":7,"href":"https:\/\/tradecloud.hdnk.nl\/en\/wp-json\/wp\/v2\/posts\/14591\/revisions"}],"predecessor-version":[{"id":14904,"href":"https:\/\/tradecloud.hdnk.nl\/en\/wp-json\/wp\/v2\/posts\/14591\/revisions\/14904"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/tradecloud.hdnk.nl\/en\/wp-json\/wp\/v2\/media\/14407"}],"wp:attachment":[{"href":"https:\/\/tradecloud.hdnk.nl\/en\/wp-json\/wp\/v2\/media?parent=14591"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/tradecloud.hdnk.nl\/en\/wp-json\/wp\/v2\/categories?post=14591"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/tradecloud.hdnk.nl\/en\/wp-json\/wp\/v2\/tags?post=14591"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}