AI to reduce production chain costs: 7 significant advantages
In the last year, with the democratization of generative artificial intelligence (AI) algorithms like ChatGPT, AI has stepped up a gear. Generative AI tools are used by several professions, and numerous studies have shown that its use can lead to an increase in productivity and work quality. According to a recent study by the Boston Consulting Group (BCG), most manufacturing sector leaders are optimistic about AI, and nearly 90% plan to integrate it into their processes.
For the manufacturing sector, AI is a driving force capable of transforming the manufacturing industry in multiple ways. When used properly, AI can improve production efficiency and product quality, customize production, improve workplace safety, and assist in data-based decision making. Companies, now more than ever, need to modernize and increase their productivity in the face of an increasingly competitive market, must absolutely take advantage of the benefits of AI.
Concretely, how can AI help manufacturing companies improve their efficiency and reduce their production costs? Here are some examples of what AI can accomplish:
1. Predictive maintenance:
One of the main ways AI reduces production costs is through predictive maintenance. AI systems can analyze large amounts of data from machine sensors to predict potential equipment failures before they occur. This allows for timely maintenance, preventing costly shutdowns and extending the equipment's lifespan.
2. Quality Control:
Another significant impact of AI is in quality control. AI-powered visual inspection systems can identify defects and inconsistencies in products faster and more accurately than human inspectors. This not only reduces waste but also ensures that only high-quality products reach the market, improving the company's reputation and reducing potential costs associated with returns and repairs.
3. Inventory management:
AI can also optimize supply chain management by predicting demand trends, optimizing stock levels, and streamlining logistics. This reduces storage and transportation costs, mitigates the risk of overproduction, and ensures a steady flow of goods from the production chain to customers.
4. Smart manufacturing:
AI enables automated smart manufacturing where machines can communicate and make decisions without human intervention. This leads to a more efficient production process as it reduces the time needed to react to changes in the production chain, such as a sudden increase in product demand or a supply shortage.
5. Workplace safety:
Safety is a priority in any work environment, and the manufacturing industry is no exception. AI can monitor working conditions and alert workers and managers in the event of potentially dangerous situations, thus helping to maintain a safe working environment.
6. Data-based decision making:
AI can help business leaders make more informed decisions. By providing real-time analyses and accurate forecasts based on a multitude of data, AI can help guide business strategy and optimize performance.
7. Automation of repetitive tasks:
AI can support the automation of repetitive tasks. For example, AI models can manage document management (sorting, analyzing, and organizing a large number of documents) and automate writing and communication processes. The use of AI frees up employees for higher value-added activities, thereby improving the overall productivity of the company.
How to get started with AI?
To successfully make the transition to AI, the first step is to identify the most urgent needs and key processes for your company where AI could have a quick and significant impact. Once the needs and goals are clarified, setting up a dedicated team or collaborating with trusted partners allows for the establishment of a winning AI integration strategy.
The strategy must consider technical components, including the development and integration of innovations, but also human components, including the adoption of solutions and change management. All of this should enable the company to quickly, and sustainably benefit from the advantages of this technology.
What matters most is to establish a clear strategy, adapted to the technical and human context and aligned with the commercial and growth objectives of each company.
The integration of AI into production chains represents a major evolution for manufacturing companies. With its capabilities to increase efficiency, reduce costs, and improve decision-making, AI is thus asserting itself as an essential tool in the modern industrial landscape. By adopting a thoughtful strategy, which includes identifying the company's specific objectives, appropriate staff training, and collaboration with trusted partners, manufacturing companies can thrive in a market increasingly dominated by technological innovations.