Automation of production planning
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Artificial intelligence (AI) in production AI trends and innovations 2024
The production industry will also be dominated by artificial intelligence (AI) in the second half of the year. AI is fundamentally changing production processes and opening up new opportunities. From cloud-based AI models to predictive maintenance and sustainable production methods - the trends are diverse and promising.
AI-supported solutions are becoming increasingly important in production and SAP is at the forefront. The basis for the use of AI in the production environment is digitized production in order to have a corresponding database for the use of AI. With Digital Manufacturing (SAP DM), SAP provides a central MES platform that helps you to digitalize your production processes end-to-end and control them efficiently in order to make the transition to the digital factory a success.
To further optimize these digital factories, many companies rely on "AI as a Service" (AIaaS). AIaaS enables access to ready-made AI models from the cloud and their flexible adaptation to your specific requirements. AIaaS offers a scalable and adaptable solution so that you do not have to invest in your own infrastructure. According to Mordor Intelligence, the market for AIaaS is estimated to reach 15.09 billion US dollars by 2024 and is expected to grow to 72.22 billion US dollars by1 – an impressive development that highlights the importance of AIaaS for the future production landscape.
Another important trend is predictive maintenance. Digital twins combined with AI monitor the condition of your machines in real time. Digital twins are virtual models of physical plants that are continuously updated using sensor data. This technology makes it possible to plan maintenance work in advance, reducing unplanned downtime. Predictive maintenance increases productivity by 25 %, reduces downtime by 70 % and cuts maintenance costs by a quarter, according to a Deloitte position paper2.
Added value of AI in production: maximizing efficiency, costs and quality
Not only these figures show: The use of AI in the production environment brings many benefits. One of the most important is increased efficiency. AI-based systems can analyze huge amounts of data in real time and gain valuable insights from it. This enables you to continuously optimize your production processes. By automating routine tasks and accurately predicting maintenance requirements, you can maximize the productivity of your systems and increase uptime.
AI also makes a significant contribution to reducing costs. Predictive maintenance reduces unplanned downtime and the associated costs. Optimized production processes mean less waste and rework and lead to cost savings. This allows you to use your resources more efficiently and optimize material consumption. This reduces costs and environmental impact.
Flexibility and adaptability
Another advantage of AI is greater flexibility in production. AI systems react quickly to changes and enable adjustments to be made in real time. This is particularly useful in an ever-changing market where you need to respond flexibly to new demands and conditions. AI can help to dynamically adjust production plans and make optimal use of capacity.
Quality improvement
Last but not least, the implementation of AI leads to a significant improvement in product quality. AI systems can continuously monitor production processes and immediately identify quality deviations. The early identification of problems makes it possible to take countermeasures more quickly and keep the quality standards of your products consistently high.
When and for whom is it worth investing in AI?
Investing in artificial intelligence (AI) is particularly worthwhile for companies with complex production processes. These companies usually have the necessary resources to finance the implementation and maintenance of AI systems. They benefit from the fact that AI can analyze large amounts of data and make precise predictions. The targeted use of AI technologies such as predictive maintenance, digital twins and AIaaS (AI as a Service) significantly increases efficiency and reduces costs. Investing in AI is also worthwhile for small and medium-sized enterprises (SMEs). It is crucial to carefully examine the specific requirements and select the right solutions. By using AI, SMEs can make their production processes more flexible and react more quickly to market changes. AI also helps to reduce production costs by optimizing processes and using resources more efficiently.
Prerequisites for successful implementation
However, before investing in AI technologies, a thorough analysis of the current situation is essential. Make sure that your machines are suitable for the use of AI technologies, that relevant data is available and that employees are appropriately qualified.
These developments will also shape 2024
In addition to artificial intelligence, there will be other exciting technological trends in 2024 that will significantly change the production landscape. These innovations offer additional opportunities to increase efficiency and open up new ways of promoting innovation.
Efficient container management enables companies to optimize their stock levels, shorten throughput times and reduce container management costs.
A typical use case for AI in production is image and text recognition. AI-supported text recognition can be used to validate serial numbers, labels or outgoing goods documents, for example. AI-supported image recognition is used to detect anomalies. For example, the AI sounds an alarm if a bad part is detected during visual inspection or if the wrong color has been applied. IGZ uses this in its SAP DM-based worker assistance system IDA3 / Assembly-by-Motion to ensure absolute process reliability and therefore maximum efficiency and quality in assembly processes.
Virtual and augmented reality are becoming increasingly popular in production. They shorten training times and reduce the error rate during maintenance work. Employees can train in a safe environment before they start working in real production.
Sustainability is becoming increasingly important in production. AI plays a key role in making production processes more environmentally friendly. By using AI, companies can optimize resource consumption and reduce waste. For example, AI monitors and regulates the energy consumption of machines in order to maximize efficiency and minimize the ecological footprint. In addition, the precise analysis of production data identifies and eliminates inefficient processes, thereby reducing the use of materials and increasing overall efficiency. Companies that rely on sustainable production methods benefit twice over. Less waste and more efficient use of resources reduce costs and protect the environment. This strengthens your company's image as a responsible player and promotes customer loyalty and market position in the long term.
Artificial intelligence (AI) will continue to play a central role in production beyond 2024. Companies that embrace these technologies early on will secure important competitive advantages and future-proof their production processes. The integration of AI and other innovative technologies offers enormous opportunities to optimize production processes, reduce costs and operate more sustainably.
The future of production is dynamic and full of potential - actively shape it by relying on the latest technologies and securing your long-term competitiveness.
