The streamlining of manufacturing processes has been one of the major focuses for companies in recent years, and the integration of new technologies has been a key element in achieving these goals. AI and machine learning are two fields that have been seeing increasing progress, and now manufacturers are starting to learn how best to incorporate them into their efficiency-boosting plans.
Most will start by attaching sensors to their machines and equipment. These sensors, which are usually simple and cheap, are important for gathering important streams of data. This data can then be used to begin machine learning processes. Being able to identify patterns and trends in the data will make it much easier to start the optimization process.
Specialists can also help with this process. As companies like to use a “develop, test, explore” system when developing their optimization plans, using experts in AI and machine learning can help get better results faster. The utilization of software experts is also helpful for ensuring there are no issues with data collection, giving companies accurate results to build their plans around.
One question in particular which has stood out with the rise of AI, machine learning, and other new technologies is how will small- and medium-sized manufacturers fit into the picture. While beginning the process may not be too costly, constant testing and implementation, along with upkeep, can add up fast. Specialist support can also command a premium, with many working for larger companies already. While not impossible to do on a tighter budget, some experts in the AI field do agree that it can be tougher for smaller competitors.
As a result of these challenges, some smaller manufacturers have begun to explore the use of open-source projects. There is a plethora of information, code, and explanations directly available online, which can provide a more cost-effective solution. However, while this may help to save on costs, it instead can take up more time.