{"id":7202,"date":"2018-11-01T09:18:25","date_gmt":"2018-11-01T16:18:25","guid":{"rendered":"https:\/\/blog-prod.qad.com\/blog\/?p=7202"},"modified":"2023-09-28T11:17:37","modified_gmt":"2023-09-28T18:17:37","slug":"manufacturing-machine-learning-predictions-simplified","status":"publish","type":"post","link":"https:\/\/www.qad.com\/blog\/2018\/11\/manufacturing-machine-learning-predictions-simplified","title":{"rendered":"Manufacturing with Machine Learning \u2013 Predictions Simplified"},"content":{"rendered":"<p>[vc_row][vc_column][vc_single_image image=&#8221;7205&#8243; img_size=&#8221;full&#8221;][vc_column_text]<span style=\"font-weight: 400;\">Yes, machines can learn too! Put simply, machine learning is the ability for computerized machines to learn how to make predictions and\/or perform classifications without explicitly being taught or programmed. Just like humans have different learning styles and problem-solving techniques, so do machines, and there are numerous approaches to machine learning depending on the task at hand.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">At a Glance<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">By creating smart solutions using machine learning algorithms it is possible to increase productivity and improve efficiency and accuracy in manufacturing environments. Imagine any type of prediction scenario. You might be making predictions on some of the following aspects of manufacturing:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">when to schedule downtime for your factory machines and gadgets<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">how much scrap the production lines will produce at a given time<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">what your factory schedule will look like in order to meet seasonal demand during the holidays<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">which sales strategies to apply to your customers<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">whether or not your next promotional campaign will reach the right market and audience<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">The answers you seek almost always come from past experience and insights into current and future conditions. This past experience may have been gathered over a span of days, weeks or even years, and the current and future conditions may come from various market trends, your sensor data, your customer characteristics, etc. A variety of past, present and potential future data goes into making predictions. When humans make these predictions, there can be a level of uncertainty and bias to it. This same data can be fed into machine learning algorithms to create prediction models that not only predict outcomes with greater accuracy, but evolve and get more accurate over time as more factors and attributes are added to the knowledgebase for predictive outcomes. <\/span><\/p>\n<h2><span style=\"font-weight: 400;\">How does Machine Learning work?<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">When I think of <\/span><a href=\"https:\/\/www.qad.com\/blog\/2017\/10\/temperature-rising-machine-learning\/\"><span style=\"font-weight: 400;\">machine learning<\/span><\/a><span style=\"font-weight: 400;\">, I think about my experiences with Algebra in high school. Algebra math was tough to understand at first glance so I started by reading the chapter and going through many examples. I used a lot of trial and error, always checked my answer and practiced a lot of similar problems until I mastered them. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">With machine learning you need a lot of good training data or examples to work with. Through trial and error, you can try various algorithms, verify the results with test data and try it on various data sets as practice. Once you have the right model, it can then be used for a variety of similar data sets. One distinctive advantage that machine learning has over a human approach is an unlimited appetite for data and virtually infinite capacity to churn on that data. This allows machine learning to be applied at a scope and scale of problems that would simply be impossible for a person to solve alone.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Just like there are various techniques for humans to learn, there are numerous algorithms and methodologies available for machine learning. Classification and regression are the most common categories, and each provides a different outcome. Fundamentally, classification is about predicting a label while regression is about predicting a quantity. Various algorithms have their pros and cons and depending on the type of data and expected outcome, there are one or more to pick from. Most require feeding a lot of historical data as examples to the algorithms, which requires managing and cleansing countless data often found in a <\/span><a href=\"https:\/\/www.qad.com\/blog\/2018\/03\/data-warehouses-big-data-evolving-data-lakes\/\"><span style=\"font-weight: 400;\">data lake<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Looking Ahead<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning is allowing businesses to optimize and accelerate the repeatable processes that are often time-consuming and inaccurate by nature. It is also enabling computers to assimilate vast amounts of data accumulated from various <\/span><a href=\"https:\/\/www.qad.com\/blog\/2018\/09\/driving-smart-manufacturing-supply-chain-improvements-iiot\/\"><span style=\"font-weight: 400;\">IIoT enabled equipment<\/span><\/a><span style=\"font-weight: 400;\"> and make smart decisions and predictions, which would otherwise be too difficult or time consuming for humans.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">At QAD, we are exploring and experimenting with advanced technologies, like machine learning, to solve the problems of today and tomorrow. We are poised and ready for the industry disruptions that will create game-changing challenges for manufacturers and stand ready to assist in solving those that lie ahead with digitization, <\/span><a href=\"https:\/\/www.qad.com\/documents\/white-papers\/erp-journey-industry-40.pdf\"><span style=\"font-weight: 400;\">Industry 4.0<\/span><\/a><span style=\"font-weight: 400;\"> and beyond.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">We are always looking for additional lab partners! Whether the activity is centered on machine learning, IoT, Robotic Process Automation or other emerging technology, QAD is providing a platform and resources to jointly move our customers\u2019 capabilities along. If you have a need or an idea for experimentation around advancing technology, please let us know<\/span><span style=\"font-weight: 400;\">.<\/span>[\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][\/vc_column][\/vc_row]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>[vc_row][vc_column][vc_single_image image=&#8221;7205&#8243; img_size=&#8221;full&#8221;][vc_column_text]Yes, machines can learn too! Put simply, machine learning is the ability for computerized machines to learn how to make predictions and\/or perform classifications without explicitly being taught or programmed. Just like humans have different learning styles and problem-solving techniques, so do machines, and there are numerous approaches to machine learning depending on [&hellip;]<\/p>\n","protected":false},"author":67,"featured_media":7205,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[182,199],"tags":[491,424,601,107,380,26,602],"class_list":["post-7202","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-featured","category-manufacturing-trends","tag-advanced-technologies","tag-data-lake","tag-digitization","tag-iiot","tag-machine-learning","tag-manufacturing-erp","tag-predictions"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.7 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Manufacturing with Machine Learning \u2013 Predictions Simplified | QAD Blog<\/title>\n<meta name=\"description\" content=\"Yes, machines can learn too! 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