{"id":59502,"date":"2025-09-26T10:48:38","date_gmt":"2025-09-26T10:48:38","guid":{"rendered":"https:\/\/becolve.com\/blog\/how-and-where-to-use-machine-learning-for-production-optimization\/"},"modified":"2025-09-26T10:48:38","modified_gmt":"2025-09-26T10:48:38","slug":"how-and-where-to-use-machine-learning-for-production-optimization","status":"publish","type":"blog","link":"https:\/\/becolve.com\/en\/blog\/how-and-where-to-use-machine-learning-for-production-optimization\/","title":{"rendered":"How and where to Use Machine Learning for Production Optimization"},"content":{"rendered":"<h2><strong><span style=\"color: #00ff00;\">I<\/span> Machine Learning: Transforming Data into Knowledge<\/strong><\/h2>\n<p>Inefficiencies in processes impair production. Industrial data, an analytical and business mindset, and the application of <strong>Artificial Intelligence (Machine Learning)<\/strong> tools and techniques make it possible to understand why they occur, when they will happen, and how to avoid them. <\/p>\n<h3><strong>But, What is Machine Learning?<\/strong><\/h3>\n<p><strong>Machine Learning<\/strong> is the type of artificial intelligence that processes enormous data sets to detect patterns and trends, and then uses them to <strong>build models that predict<\/strong> what may happen in the future, becoming more intelligent over time in a continuous process.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-18498\" src=\"https:\/\/becolve.com\/wp-content\/uploads\/2023\/04\/grafico-machine-learning-min.png\" alt=\"graphic with 5 colored hexagons\" width=\"974\" height=\"447\"><\/p>\n<p>&nbsp;<\/p>\n<p>Machine Learning is not a system that can be connected to a production line and make the line work better than before. It is a continuous process that needs data inputs from one or more devices and that enables the data to be <strong>collected, prepared, trained, evaluated, and improved<\/strong> to develop knowledge about how the production line works. <\/p>\n<p>This knowledge can be used to determine how the production line can have a higher performance, operate at a lower cost, function more reliably, etc.<\/p>\n<p>In this way, machine learning <strong>transforms an industrial operation<\/strong> allowing companies to achieve:<\/p>\n<ul>\n<li>Find new efficiencies and reduce waste to save resources.<\/li>\n<li>Understand the trends and changes in your own market.<\/li>\n<li>Comply with industry regulations and standards, improve safety, and reduce your environmental impact.<\/li>\n<li>Increase the quality of products.<\/li>\n<li>Find and eliminate bottlenecks in the production process.<\/li>\n<li>Improve the visibility of the supply chain and distribution networks.<\/li>\n<li>Detect the first signs of failures or anomalies or reduce downtime and perform repairs more quickly.<\/li>\n<li>Carry out a root cause analysis to improve processes.<\/li>\n<li>Optimize the life cycle of assets.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-18499\" src=\"https:\/\/becolve.com\/wp-content\/uploads\/2023\/04\/machine-learning-min.png\" alt=\"Man using laptop\" width=\"974\" height=\"431\"><\/p>\n<p>&nbsp;<\/p>\n<h3><strong>In which Industrial Areas is Machine Learning Applied?<\/strong><\/h3>\n<p>Some of the current applications and <strong>transformations attributed to Machine Learning<\/strong> that allow predicting and improving inefficiencies in production processes are: <\/p>\n<h4>1.- Predictive Maintenance<\/h4>\n<ul>\n<li>Predict interruptions in a production line in advance to schedule downtime at the most advantageous time and eliminate unscheduled downtime.<\/li>\n<li>Identify anomalous behaviors by comparing current operation with the normal behavior of the machine to identify and address situations of risk to the integrity of the machines.<\/li>\n<li>Anticipate machine failures by identifying the complex behavior patterns that indicate the first signs of a problem, and take advantage of them to plan maintenance and avoid unexpected stops.<\/li>\n<li>Estimate the remaining useful life of the components by modeling the wear patterns of the components.<\/li>\n<\/ul>\n<h4>2.- Quality Control<\/h4>\n<ul>\n<li>Understand the variability by identifying the process inputs that most affect the quality metrics and the complex interactions between these and the quality of your product.<\/li>\n<li>Anticipate quality by continuously predicting the quality of the products based on the configuration of the process and its behavior.<\/li>\n<li>Simulate different configurations by modeling the quality based on the control levers and simulating the results of different configurations to search for the optimal one in each situation.<\/li>\n<li>Reduce laboratory analysis by identifying the batches with the highest risk of quality non-compliance to focus the tests on these, thus reducing costs and the lead time of the product.<\/li>\n<\/ul>\n<h4>3.- Resource Optimization<\/h4>\n<ul>\n<li>Increase the energy efficiency of the process by detecting anomalies and optimizing it from an energy cost point of view.<\/li>\n<li>Organize the tasks of the employees in an optimal way, so that these are adjusted to their workload, skills, experience, authorizations and, even, location.<\/li>\n<li>Discover the optimal behavior by modeling the normal operation of a process to identify anomalous behaviors and discover superior yields.<\/li>\n<\/ul>\n<h4>4.- Logistics<\/h4>\n<ul>\n<li>Demand forecasting with the identification of the most influential factors, as well as the most relevant KPIs to monitor.<\/li>\n<li>Planning of manufactures allowing the optimization of inventories of raw materials and finished products.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-18500\" src=\"https:\/\/becolve.com\/wp-content\/uploads\/2023\/04\/logistica-min.png\" alt=\"technological background\" width=\"902\" height=\"400\"><\/p>\n<p>&nbsp;<\/p>\n<h2><strong><span style=\"color: #00ff00;\">I<\/span> Conclusions<\/strong><\/h2>\n<p>Machine Learning is a <strong>truly revolutionary technology<\/strong> that uses industrial data to improve business and production practices and help companies make better decisions.<\/p>\n<p>Knowing all the how&#8217;s and why&#8217;s before something harmful happens can help streamline production, increase product quality, and improve customer satisfaction.<\/p>\n<p>The important thing is to <strong>identify the different points<\/strong> within the factory where Machine Learning can provide greater value. Applied correctly and meaningfully, it can bring great benefits that are reflected in the income statement. <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Machine Learning is a truly revolutionary technology that uses industrial data to improve business and production practices and help companies make better decisions.<\/p>\n","protected":false},"author":31,"featured_media":59506,"menu_order":0,"template":"","categories":[1378,1360],"tags":[1441,1440],"arquitectura":[1841],"area":[],"sector":[],"experto":[1392],"weborigen":[93],"productos-tax":[96],"soluciones-tax":[1407],"marcas-tax":[],"coauthors":[434],"class_list":["post-59502","blog","type-blog","status-publish","has-post-thumbnail","hentry","category-asset-maintenance","category-cloud","tag-aveva-predictive-analytics","tag-subscription","arquitectura-industrial-cloud","experto-industrial-digital-transformation","weborigen-wonderware-es","productos-tax-aveva-insight","soluciones-tax-cloud"],"acf":[],"yoast_head":"<!-- This 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