The manufacturing industry is evolving rapidly, with technology playing a critical role in improving operational efficiency and quality. Two technologies that have gained considerable attention in recent years are Lean Management and Artificial Intelligence (AI). Lean Management aims to streamline processes and eliminate waste, while AI offers the ability to process vast amounts of data and make predictions based on that data. In this blog post, we explore the benefits of combining these two technologies in manufacturing and real-world applications.
Benefits of Lean in Manufacturing
Lean Management is a set of principles that aims to streamline operations, improve quality, and reduce waste. By eliminating waste and focusing on value-adding activities, manufacturers can improve efficiency, reduce costs, and increase profitability. A report by Deloitte found that the transformation from lean to digital lean is expected to generate improvement in earnings before interest, taxes, depreciation, and amortization of US$20 million annually, reduce costs by 15% per line per year, and improve overall equipment effectiveness (OEE) by 11% annually.
The seven kinds of waste
Source: Deloitte analysis.
Benefits of Artificial Intelligence in Manufacturing
Artificial Intelligence offers the ability to process vast amounts of data and make predictions based on that data. In manufacturing, AI can help identify patterns and anomalies in data, predict machine failure, optimize supply chain management, and improve product quality.
Manufacturing companies are increasingly turning to AI to address their capability challenges and talent shortages. The most significant advantage of using AI in manufacturing is that it allows businesses to automate monotonous, repetitive tasks, freeing up the workforce to focus on other more value-adding activities. According to a survey by OECD, in manufacturing AI technology is most commonly used in production processes (60%) and maintenance tasks (40%).
Combining Lean Management and Artificial Intelligence
By combining Lean Management and Artificial Intelligence, manufacturers can optimize processes, improve product quality, and reduce costs. Lean Management provides a framework for eliminating waste and improving efficiency, while AI offers the ability to process vast amounts of data and make predictions based on that data. Together, they can help manufacturers identify areas of improvement, optimize supply chain management, and improve product quality.
Real-world Applications of AI and Lean Manufacturing
The automotive industry is increasingly adopting AI technology to modernize their operations, with specialized applications that can revolutionize a modern production company. The integration of AI algorithms in procurement, industrial sourcing, cost control, and more is already underway across various industries. This technology is powered by data collected from instruments or sensors installed in manufacturing machinery, enabling customers to enhance their product requirement projections and streamline their workflow.
With advancements in sensor technology and the development of deep learning algorithms, a new generation of powerful computing resources is emerging. AI enables machines to collect and analyze data, recognize patterns, and learn and adapt through machine learning and natural language processing. It can also enhance communication between employees and managers, making it easier for them to understand complex concepts.
The digitalization of Lean Manufacturing processes in today's production lines is made possible through AI-based digital tools.
Artificial Intelligence (AI) goes beyond relying solely on machine-generated data to enhance efficiency. It also enables the effective collection of data from manual operations through the utilization of AI-based video analytics. The insights derived from this process are instrumental in identifying the underlying causes of waste while leveraging digital tools for analysis and implementing improvements.
Imagine a production line with intensive manual operations. Measuring the cycle times for each station would take much time and limited data would be created as a base for further calculations. Through recorded videos of manual operations, AI-based video analytics enable engineers to automatically measure cycle time data, and apply time study. The results obtained can be utilized for root cause analysis, value-added analysis, MTM, and line balancing improvements.
These tools enable engineers to measure and analyze more quickly, allowing them to focus their time on value-added decision-making processes.
By leveraging AI, manufacturing companies can significantly lead to substantial advancements in the industry. To optimize the manufacturing process, integrated manufacturing plants that are well-structured in the product line and quality management are required.
Conclusion
In conclusion, the manufacturing industry is evolving rapidly, with technology playing a critical role in improving operational efficiency and quality. Lean Management and Artificial Intelligence are two technologies that can help manufacturers streamline processes, improve product quality, and reduce costs. By combining these two technologies, manufacturers can optimize processes, improve product quality, and reduce costs. Real-world examples have shown that the combination of AI and Lean Manufacturing can lead to significant improvements in efficiency, cost savings, and product quality. As the manufacturing industry continues to evolve, the combination of AI and Lean Manufacturing will become increasingly important for manufacturers looking to stay competitive.
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