Building factories of the future with Machine Learning in manufacturing
As emerging technologies seep through business models of companies across industries, more prominent ones like Artificial Intelligence and Machine Learning are penetrating deeper than ever before. In today’s day and age, a company’s digital capabilities are shaping their core competencies. As the need for adaptable and flexible businesses grow, so does the requirement for predictive and prescriptive technologies that help leaders identify gaps and make better business decisions. By combining the powers of machine learning and ERP, leaders can now have mobile access to insights that can help them meet rapidly evolving business demands. From streamlining operations to enabling data-driven decisions, it has become clear that Machine Learning in manufacturing has the potential to truly revolutionize how the everyday world works.
A BCG analysis found that AI implementation can reduce producer’s conversion costs up to 20% and up to 70% reduction of cost reduction resulting in higher workforce productivity. Manufacturing companies especially can optimize technologies like machine learning by combining it with their ERP system. Here’s how-
Machine Learning In Manufacturing
Supply Chain– Demand forecasting is one of the key issues where Machine Learning can help revolutionize manufacturing. By better anticipating changes in demand, companies can alter their production program and reduce wastage. By learning from data related to products, purchasing behaviors, machine learning in manufacturing firms supports forecasting of customer demand. Consolidation of data from warehouses and your ERP system, machine learning algorithms can predict demand patterns and give out customer insights.
Production – Coping with production complexities and increasing liabilities of manufacturing processes is one of the key functions facilitated by machine learning. It enables machines in the factory to become self-optimized systems that keep readjusting their parameters based on data and analyzing algorithms.
According to BCG, which recently conducted a study to understand the impact of AI and ML on companies. Some steel producers are using AI to enable furnaces to autonomously optimize their settings. For many of them Artificial Intelligence can analyze iron intake composition and provide lowest temperature recommendations for stable process conditions, thereby reducing overall energy consumption.
Quality and maintenance – Machine Learning in manufacturing can drastically help reduce equipment breakdown and increase asset utilization with the help of predictive analytics offered by ML. As machines analyze and learn from data, business leaders can avoid breakdowns and replace worn machinery on the basis of prescriptive analytics.
Process based industries especially can optimize this to the fullest. Implementing machine-learning models that estimate the remaining time before equipment failures. The models consider more than 1,000 variables related to process parameters, material input and output and weather conditions.
Logistics- Machine Learning manufacturing factories will enable efficient supply of material and autonomous movement within the factory.
Machine learning algorithms can use logistical data like turn rates of parts, inventory levels, outflow and inflow of material —enabling warehouses to self-optimize their operations. For instance, an algorithm could recommend moving low-demand parts to more remote locations and moving high-demand parts to nearby areas for faster access.
Over the years Bista has been helping businesses reshape their digital processes. One of the key practices that we take pride in is our Machine Learning developers. They can seamlessly integrate your ERP system with intelligent technologies like Artificial Intelligence and Machine Learning in your manufacturing. Get your free machine learning POC done today! Contact us for more details.