The first two decades of the 21st century have seen artificial intelligence (AI) go from a favored trope of science fiction writers to a part of daily life. Increasingly sophisticated and variable algorithms can adapt to changing conditions while performing deep dives into accumulated data analysis. They prove their value in just about every segment of the economy, including manufacturing.
Depending on your employment field, it may or may not surprise you to learn that 90 percent of the data generated since the dawn of human history was created in the last two years. It also may not surprise you to learn that one of the primary beneficiaries of that outpouring of data has been the manufacturing industry. Challenges such as shorter product life cycles and decreased times to market are putting new pressures on manufacturers, and while AI and its associated technologies can potentially give manufacturers the capabilities and flexibility they need, the systems that incorporate it will need to be user-friendly and practical so that management and employees can get the most out of them.
Of all the subsets of AI, the one with the most potential to be a real game-changer for manufacturers is machine learning. At its most basic, machine learning is the study of computer algorithms that improve automatically through experience by building mathematical models based on sample data to make predictions or decisions – without being explicitly programmed to do so. For example, machine learning enables predictive monitoring, where algorithms forecast equipment breakdowns before they occur and schedule preventative maintenance.
Machine Learning also goes hand in hand, enriching vehicles leveraging the Autonomous Driving. With its innovative driving support system, Tesla is continually improving Autopilot through software updates, aiming to achieve a complete self-driving system Things that once seemed achievable only in an unforeseeable future are almost being introduced to everyday life tomorrow, mainly due to machine learning achievements.
As technology continues to prove its value, applications like Manufacturo will become “must-haves” for manufacturers all over the world. Manufacturo streamlines maintenance tasks and lets operators solve production line challenges without calling on more experienced colleagues. Using sophisticated AI, it can gather knowledge from documentation and historical issues to assist in maintenance actions that would minimize downtimes.
Human error has always been a loss leader for manufacturers, but specific problem areas in the business environment of 2020 involve rapidly-changing conditions that may not be manually predicted or detected in time for action. Existing IT systems provide reliable support for specific tasks that they have been designed or developed for, but even minor customization often triggers problems. In contrast, flexibility and adaptability are the AI’s most significant advantages. Supplementing traditional systems and products with AI has been proven to significantly improve quality, lower costs, and boost productivity.
Recent developments are opening the doors to further improvements in memory, connectivity, and communication, with a great example being the way that Manufacturo has incorporated chatbot technology and natural language processing (NLP) algorithms into its interface. A user can take advantage of a conversation instead of manually typing questions, making the whole experience akin to a discussion with an experienced maintenance engineer.
One of AI’s most prominent potential benefits is its ability to simplify knowledge management. Turnover in the manufacturing industry is notoriously high. The knowledge, expertise, and experience of departing employees need to be maintained if a company wishes to maintain a fixed production performance level. Currently, HR departments across the industry are scrambling to minimize the massive costs of training new employees by searching for better ways of documenting a company’s knowledge and processes. However, there are some things that won’t fit in a filing cabinet or on a hard disk – intangible expertise and experience have proven almost impossible to replace. Process implementation on a global scale has also been a challenge.
The answer to this puzzle is a solution that accumulates knowledge, gives it structure, and allows easy access to it on a global scale. It’s another area where Manufacturo could well prove to be the answer to many a manufacturer’s prayer. Its “mentoring” approach to troubleshooting supplements an on-site maintenance team’s knowledge and experience with machine learning capabilities. Information provided by the system is constantly evaluated, and this feedback is used for further learning. The more the application is used, the more knowledge gets collected, resulting in an improved user experience and a faster, more precise response to future issues.
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