The 3 fundamental challenges of AI for Industry 4.0

Artificial intelligence is becoming an ally of choice that contributes not only to the development and growth of the company but also to the redefinition of the organization of work. Coupled with augmented reality, it is also very useful for simulating and identifying risky situations when designing new equipment or new infrastructures. Welcome to a new era of an industry that dusts off conventional wisdom.

Cost and productivity

Improving competitiveness is the first added value that artificial intelligence can bring to industry. By controlling the data and therefore the flows, the company can organize its production chain, integrate new processes, gain flexibility, efficiency, productivity, to respond more quickly to demand while optimizing its costs and thus increasing its competitiveness. Thanks to machine learning, the analysis of the parameters that influence the performance of a production line and the comparison of quantitative and structured data collected on site with a pool of reference data, make it possible to make proposals for optimizing production processes. production. For example by influencing speed, material consumption or energy…

Beyond the optimization of production processes, AI applied to industry can provide a concrete response to the prevention and management of breakdowns. Thanks to connected sensors, it is now possible to detect an operating anomaly or premature wear in real time. Maintenance is carried out in advance, even before the failure occurs and this as close as possible to the real need: this is the predictive maintenance of equipment. Breaks in the production chain are thus avoided, with all the resulting economic consequences. The prediction of technical failures then replaces scheduled and repetitive maintenance, synonymous with additional costs. Predictive maintenance can notably rely on deep learning. This method works on the principle of the neural network of the brain and makes it possible to produce prediction models based on complex data such as images or sounds.

Working conditions and safety

In Industry 4.0, the human and the machine form an interactive couple, actors in the evolution of the company. By decompartmentalizing the professions, artificial intelligence allows employees to focus on activities with higher added value. Technology improves working conditions, making it more ergonomic and attractive. The digitization of certain activities relieves and frees employees from repetitive and time-consuming tasks such as reporting or inventory management. Thanks to AI, they can rely on new decision-making tools. We speak more and more often of “augmented collaborator”. The latter gains in autonomy and acquires a better readability of his work environment by accessing a quality of information that he did not have before. Remote monitoring and control also become possible, providing more flexibility to the business.

AI is also at the service of employees in matters relating to their safety. Prevention of accidents, reduction of exposure to dangerous situations, reduction of physical loads are concrete examples of applications of connected solutions. Some visual aids even aim to reduce the risk of error to zero on the workspace by going through the “deep learning” process. Any deviation detected by the algorithm, compared to a “normal” situation, triggers an alert signal, making it possible to anticipate the accident (such as the presence of a hand in the cutting area or of a tool on the trajectory of a vehicle). Deviant behavior can also be analyzed to perfect the training and information of workers on good practices (wearing of personal protective equipment – ​​PPE, working time without a break, drowsiness, etc.).

Quality and environment

Quality is crucial in industry. No manufacturer wants to experience a product recall one day, seriously damaging its reputation and its business. Zero defects have become the norm and the industry must invest in technologies to reach this level of requirement. For example, Smart Kitting, the use by an operator of glasses and connected tablets capable of automatically recognizing the parts and components necessary to carry out his mission, reduces the number of human errors in the preparation of orders or supplies. , and speeds up the pace and efficiency of performing this task.

At the end of the production line, the quality controls of the finished products become automated thanks to artificial intelligence. A large volume of good quality data is needed to allow the machine and the algorithms to recognize a fault. The alert system detects production drifts in advance: almost immediate correction becomes possible. Thus the reduction of the return rate and the cost of quality control constitutes a real lever of economic performance, with the key to customer satisfaction. Quality is also at stake throughout the product’s life chain, and it is now possible to follow its path, from its manufacture to its sale. The information collected, analyzed and stored allows the continuous improvement of product quality and total traceability.

Consumer requirements are also vectors for the company’s continuous improvement. By adapting to market demand, the industry reinforces the consumer or client in their purchasing decision. And the levers are varied: intrinsic quality of the product, ecological, ethical or even societal values. The integration of connected solutions can make it possible to respond to the CSR challenges of the industrial company. On the environmental side, Artificial Intelligence is a valuable asset, in particular by making it possible to rationalize the use of raw materials and plant resources (water, energy, etc.). The consumption reduction indicators can then be collected and communicated to participate in the influence of the company’s CSR approach. Finally, industry 4.0, in its transformation, is creating new jobs, more qualified and with high added value. Working in the factory is no longer synonymous with arduous and daunting work, but has become a connected profession.