6 benefits of machine learning in manufacturing
A recent study by McKinsey tells that 50% of companies that will implement AI in the next five to seven years will double their cash flow. And this statistic applies primarily to the booming manufacturing sector due to its growing reliance on data.
Manufacturing ERP software clubbed with Artificial intelligence and Machine Learning can significantly benefit manufacturing companies by boosting their efficiency and opening the doors of new business opportunities. But manufacturers often ask how machine learning can help solve crucial challenges like tracing manufacturing defects and reducing waste by defective components in the early stages.
So, here are the six critical benefits of machine learning in manufacturing:
1. Quality control
Maintaining top-notch product quality is essential for manufacturing companies. Fortunately, machine learning models play a pivotal role in product inspection and quality control stages. For example, ML-based computer vision algorithms can pull data from the manufacturing ERP software and learn to differentiate between superior quality products from the faulty ones. Another benefit is that they automate the supervision and inspection process, thereby freeing up time for the quality control team to focus on mission-critical tasks.
2. Predictive maintenance
Machine learning detects equipment failure in the early stages, which helps schedule timely maintenance, eliminate downtime, and provide customer assistance even before equipment breakdown occurs. If done manually, manufacturers might spend too much time fixing breakdowns, and the chances of human-induced errors also increase exponentially.
Recent studies report that machine learning algorithms show a mind-boggling 92% accuracy in predicting equipment failure. Another study by Forrester reveals that 76% of manufacturers consider improved operational efficiency an essential benefit of taking machine learning initiatives. Therefore, businesses can improve asset reliability, plan maintenance schedules, and boost product quality significantly using ML models.
3. Product development
Product development involves designing new products or improving existing products, requiring extensive data collection and analysis. Machine learning algorithms provide an upper hand to manufacturing companies by collecting and analyzing vast quantities of data that helps:
- Uncover hidden product development flaws
- Identify unseen business opportunities
- Comprehend changing market trends and customer preferences
ML-enabled Manufacturing ERP software enables companies to generate new revenue streams, decrease product development risks, and provide real-time data and valuable insights that help make informed decisions.
4. Supply chain management
A well-monitored warehouse and a highly-efficient logistic infrastructure help manufacturing companies run the production process better.
Machine-learning-based solutions are a worthy add-on to Manufacturing ERP software as they suggest better transport routes, reduce transportation costs, improve packaging, and boost inventory control.
A recent study shows that businesses in the US lose a whopping USD 171,340 each year because they manually perform time-consuming tasks, such as production-related paperwork and organizing products within the warehouse. Instead, they can automate routine tasks by implementing machine learning algorithms that significantly shorten the process completion time.
Another benefit of ML is resource management. For example, Google reduced its data center cooling expenses by 40% using DeepMind AI.
5. Robotics
Manufacturing companies globally rely too much on the human workforce, resulting in loss of time and productivity. But robots are ready to bring a significant transformation in the manufacturing sector. With massive developments in machine learning and AI algorithms, robots can perform most manufacturing operations at lightning-fast speed. Except for a few processes that require very high precision, robots have replaced humans and are doing a fantastic job. The best part is that robots show tremendous flexibility in working together with humans and perform repetitive tasks quickly and efficiently.
Thanks to ML and AI, robots can access critical business data from the manufacturing ERP software and perform most manufacturing tasks independently. Moreover, they can work in dynamic environments and hazardous situations with minimal human supervision.
6. Cybersecurity
ML-enabled manufacturing ERP software, both On-premise and On-cloud, depends extensively on data, network, and technology platforms. Therefore, providing adequate security to these systems is essential. Machine learning authenticates the identity of users and only allows verified stakeholders to access the company’s central database. Moreover, it can also control how individual users might access and share sensitive data & applications. The most significant benefit is that companies can quickly detect anomalies and take corrective actions.
Conclusion
Manufacturing ERP software provides several benefits, including accurate inventory management, 360-degree data visibility, standardized working processes, innovative scheduling capabilities, and continuous improvement of existing methods. But machine learning algorithms transform the ERP system into an intelligent solution that collects real-time data and generates easy-to-understand visual reports enabling senior management to brainstorm effective strategies. ML and AI are transforming the manufacturing sector boosting quality control, implementing predictive maintenance systems, detecting product flaws, and managing resources effectively.
Author:
Nishant Joshi likes to read and write on technologies that form the bedrock of modern-day and age like ERP, CRM, Web Apps, machine learning, data science, AI, and robotics. His expertise in content marketing has helped grow countless business opportunities. Nishant works for Sage Software Solutions Pvt. Ltd., a leading provider of business management software to small and mid-sized businesses in India.
You can learn more about him on Linkedin
